Marine Corps Operational Test and Evaluation Activity 

Ground Combat Element Integrated 

Task Force 

Experimental Assessment Report 

August 2015, Original 

Marine Corps Operational Test and Evaluation Activity 

2032 Barnett Avenue 

Quantico, VA 22134-5014 

MOORE KEITH MICHAEL ,, Oigilollyslgnedby MOORE.K£11H.MICHAE • • • ON: caUS. o.-U.S. Government, ou•OoD. ouwPKL 

ouoUSMC.cn•MOORE.KEITH.MICHA£ Approved o ••• :20I5.08.14 11:07:48.Q4"00' 

K. M. Moore 

Colonel, USMC 

Director, MCOTEA 

FOR OFFICIAL USE ONLY 

14 Aug 2015 

Date 

This document constitutes pre-decisional, deliberative opinion and recommendations. 

Not releasable under FOIA pursuant to 5 U.S.C. 552 (b) (5). 

(b)(6)

(b)(6)

(b)(6)
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ES-1 AUGUST 2015

Executive Summary

Purpose

This Experimental Assessment Report (EAR) formally records MCOTEA’s assessment 

of experimental results. 

Background

The Commandant of the Marine Corps authorized the formation of a Ground Combat 

Element Integrated Task Force (GCEITF), and the Assistant Commandant of the Marine 

Corps assigned the Marine Corps Operational Test and Evaluation Activity (MCOTEA) 

the responsibility of conducting an experiment on the GCEITF. The task force trained

female Marine volunteers in closed military occupational specialty (MOS) skills and 

integrated them into a combat arms unit, while a dedicated research team observed the 

unit’s performance in an operational environment.

Scope

The task force was built around an infantry battalion minus (-) reinforced with 

attachments in the Battalion Landing Team model as a notional ground combat element 

component. This unit formed in July 2014 and remained in place until July 2015. 

MCOTEA used data obtained from GCEITF experimental events and non-experimental

event periods to answer objectives identified in the Experimental Assessment Plan. 

Conclusions

(FOUO) The female Marines integrated into the closed MOS units demonstrated that 

they are capable of performing the physically demanding tasks, but not necessarily at 

the same level as their male counterparts in terms of performance, fatigue, workload, or 

cohesion. 

(FOUO) Integrated units, compared with all-male units, showed degradations in the time 

to complete tasks, move under load, and achieve timely effects on target. The size of 

the differences observed between units and tasks varied widely. The more telling 

aspect of the comparisons is the cumulative impacts. The pace, timing, and accuracy of 

any singular task is not necessarily important, but taken together, and in the context of 

actual combat operations, the cumulative differences can lead to substantial effects on 

the unit, and the unit’s ability to accomplish the mission.

(FOUO) Gender and MOS type are the best predictors of occupational injuries. In 

particular, we found that females are more likely to incur occupational injuries, resulting 

in reduced readiness compared to their male counterparts. Males, on the other hand, 

are more likely to incur non-occupational injuries. Additionally, Marines in vehicle MOSs 

tended to have lower injury rates than those in MOSs that march (i.e., foot mobile) or 

Artillery MOSs. 

(FOUO) No clear conclusions can be drawn from the Proficiency and Conduct ratings of 

the GCEITF volunteers.
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Experimental Assessment Report 

Ground Combat Element Integrated Task Force 

1. Purpose 

This Experimental Assessment Report (EAR) formally records MCOTEA’s assessment 

of experimental results. 

2. Background 

The expansion of roles for women in the armed forces has evolved over decades. 

Department of Defense (DOD) policy restricting women from serving in ground combat 

units was modified in 1994, and again in 2013. Under the 1994 policy, women could not 

be assigned to units below the brigade level whose primary mission was to engage in 

direct combat on the ground. This meant that women were barred from infantry, artillery, 

armor, combat engineer, and special operation units of battalion size or smaller. On 

24 January 2013, then-Secretary of Defense Leon Panetta rescinded the Direct Combat 

Exclusion Rule on women serving in previously restricted occupations (i.e., combat). 

Today, women can serve in any military unit. 

On 20 February 2014, the Commandant of the Marine Corps authorized the formation of 

a Ground Combat Element Integrated Task Force (GCEITF), and the Assistant 

Commandant of the Marine Corps assigned the Marine Corps Operational Test and 

Evaluation Activity (MCOTEA) the responsibility of conducting an experiment on the 

GCEITF. The task force trained female Marine volunteers in closed military occupational 

specialty (MOS) skills and integrated them into a combat arms unit, while a dedicated 

research team observed the unit’s performance in an operational environment. 

3. Scope 

The task force was built around an infantry battalion minus (-) reinforced with 

attachments in the Battalion Landing Team model as a notional ground combat element 

component. This unit formed in July 2014 and remained in place until July 2015. 

This report supports the assessment of the GCEITF from its inception through the final 

experimental exercises. MCOTEA used data obtained from experimental events 

(references (a) and (b)) and non-experimental event periods to answer objectives 

identified in the Experimental Assessment Plan (EAP) found in reference (c). 

The event was limited to the ground combat element mission performed by Marines in 

closed and open MOSs. Closed MOSs consist of combat arms fields, including infantry 

(03xx), armor (18xx), and artillery (08xx). Open MOSs are all others. 
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4. Objectives

Standing up a GCEITF was intended to allowed us to evaluate the physical 

performance of individual Marine volunteers in the execution of individual and collective 

tasks in an operational environment. The purpose of the experiment was to estimate the 

effect of gender1 integration in closed and open MOSs, in closed MOS units, and on 

various measures of readiness and mission success for these MOSs (e.g., physical 

capacity, fatigue, workload, tasks, etc.). The results of this assessment are reported 

here in the Experimental Assessment Report. The objective of this assessment was to

address the following research questions: 

4.1 Objective 1 (Closed MOSs) 

In support of establishing gender-neutral occupational standards, we will measure 

mission effects at various levels of gender integration. We will also investigate: 

4.1.1 Sub-objective 1.1

Whether the relationship between gender integration and mission effects varies by 

MOS.

4.1.2 Sub-objective 1.2

How gender integration affects gender distributions of fatigue and workload during 

collective tasks. 

4.1.3 Sub-objective 1.3 

Whether it is possible to isolate quantifiable individual physical characteristics that 

correlate to collective mission effects.

4.2 Objective 2 (Open MOSs in Closed MOS Units) 

In support of establishing gender-neutral occupational standards for open MOSs in 

closed MOS units, we will measure closed MOS mission (i.e., provisional rifle company 

mission) effects at various levels of gender integration. We will focus on closed MOS 

units with male and female volunteers currently serving in open MOSs. We will also 

consider:

4.2.1 Sub-objective 2.1

How gender integration affects gender distributions of fatigue and workload during 

collective tasks. 

 

1 The term gender used throughout this report refers to the sex of the individual vice the spectrum of 

masculine and feminine traits as the modern use of the word has been referenced to.
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4.2.2 Sub-objective 2.2 

Whether it is possible to isolate quantifiable individual physical characteristics that 

correlate to collective mission effects. 

4.3 Objective 3 (Personnel Readiness, Proficiency and Conduct) 

In support of establishing gender-neutral occupational standards, we will work to identify 

physical characteristics that correlate to individual readiness, proficiency, and conduct.

We will also study:

4.3.1 Sub-objective 3.1

How individual readiness, proficiency, and conduct correlate to mission effects. 

5. Deviations

A number of deviations occurred from the published EAP. MCOTEA recognizes the 

following deviations from the EAP resulting from the GCEITF experiment conducted 

from 2 March 2015 to 18 May 2015:

5.1 Reduction of Treatment Groups 

Marines participated in this experiment voluntarily and could leave the experiment at 

any time, for any reason, making the total number of human subjects available highly 

volatile. Trials were not executed if there were not enough participants to carry out the 

assigned mission and attrition affected the integration levels for the experiment. As a 

result, MCOTEA reduced the number of experimental treatment groups in cases where 

the total number of human subjects was not sufficient to conduct realistic operational 

missions at the small-unit level with all specified groups. The treatment groups were 

affected in the following MOSs: 

• Infantry Rifleman (MOS: 0311) 

• Infantry Mortarman (MOS: 0341) 

• Infantry Assaultman and Infantry Antitank Missileman (MOS: 0351/0352)

2

 

• Provisional Infantry Machine Gun (PIMG) 

• Mountaineering (Closed MOSs)

• Mountaineering (Open MOSs) 

• M1A1 Tank Crewman (MOS: 1812) 

5.2 Proficiency and Conduct Analysis

The proficiency and conduct portion of objective 3 cannot be answered with any 

meaningful analysis of the data gathered from the GCEITF experiment. Objective 3 of 

 

2 From this point forward the 0351 and 0352 MOSs will be combined and referred to as 035X.
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the research included an examination of proficiency and conduct information from 

volunteers who participated in the experiment in an attempt to correlate to individual 

proficiency and conduct to mission effects. However, the protections afforded to the 

volunteers in the plan bias the information in such a way as to make its use 

questionable at best. According to the EAP:

“Male and female open MOS volunteers participating in the provisional rifle company 

experiment as well as female volunteer participants for closed MOSs will not be 

performing in their normal MOS functions for the duration of their assignment to the 

GCE ITF. Duty proficiency marks will be assigned in accordance with the Individual 

Records Administration Manual (HQMC, 2000) and the commanding officer of the GCE 

ITF will provide due allowance for Marines who will be filling billets inconsistent with 

their grade and normal MOS skills.”

In practical terms, participation in the experiment cannot harm the participants, including 

their chances for promotion or retention. The special allowances necessary to protect 

the volunteers provided by the commanding officer of the GCEITF in the issuance of the 

proficiency and conduct ratings precludes their use in any meaningful analysis.

5.3 Modifications to Analysis 

Although readiness for each Marine can be summarized as a ratio of the number of full 

duty days to the number of total duty days, we had much more detail on individual 

volunteer outcomes and we discuss the analyses of these outcomes. The total 

summary measure of readiness may obscure some of the more detailed outcomes, 

thus, we do not analyze it as a stand-alone result. 

The original plan included analysis by integration level only; however, some tasks were 

performed by one or two persons who dominated the physically demanding aspect of 

the task. For those tasks we provide additional analysis by the gender.

5.4 Correlating Readiness to Mission Effects 

In practical terms, when individuals became injured during the conduct of the 

experiment they were removed from trials and as such, we did not directly correlate the 

impact of readiness to mission effects.

6. Assumptions

Conclusions depend on the validity of assumptions. Assumptions will be validated 

throughout the evaluation process whenever possible. These assumptions include:

6.1 Physical Demands of Experimental Tasks 

The collective tasks selected for the Marines in this assessment were considered to 

most physically demanding tasks that Marines could reasonably be expected to perform 

on a frequent basis. If gender integrated groups perform at least as well as all-male 

groups, then in theory, they would be capable of performing all MOS tasks. 
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6.2 Generalizability to Larger Units

Impacts on small (subordinate) unit effectiveness (i.e., Squads, Fireteams, Vehicle 

Crews, Gun Crews, etc.) are generalizable to larger unit effectiveness. 

6.3 System and Equipment Representativeness 

The systems and equipment used during the conduct of the experiment were 

representative (quality and type) of systems used by the Marine Corps in the conduct of 

its missions.

6.4 Volunteer Representativeness 

Marines conducting the experiment were representative of the total population within the 

Marine Corps. This allows inferences of results and conclusions to be applied to future 

physical, physiological, and performance standards.

7. Limitations

7.1 Planned versus Actual Trials 

The total number of Marine volunteers during the experiment was highly volatile for 

selected MOSs. Throughout the experiment, Marines were able to self-select to 

withdraw from the experiment (Drop on Request) or were dropped involuntarily for 

medical, legal, or command-related incidents. Trials were not executed if there were 

not enough participants to carry out the assigned mission. As a result, many tasks saw 

a reduction in sample size, some only running one third of the planned trials. Whenever 

reasonable, a comparison group (usually, the low-density group) was eliminated from 

consideration by the research team, splitting the smaller sample size between two 

different concentrations (all-male and high-density) rather than three to maintain better 

experimental power to detect differences. Still, with variation in some tasks particularly 

high among integrated groups, a larger sample size would have resulted in more 

precise estimates and more confident statements about observed differences. Each 

MOS-specific annex details the numbers of planned versus actual trials. 

7.2 Relative Difficulty of Experimental Cycle 

The assessment was designed to gather data associated with some of the most 

physically demanding tasks within each MOS. However, these tasks in isolation did not 

fully replicate life experienced by a Marine during a typical field exercise (FEX) or a 

combat environment and did not obtain the maximum cumulative workload that could be 

placed on a Marine. With limited time available, only selected tasks were assessed. 

Other tasks/duties outside the assessment were minimized due to specific experimental 

constraints and human factors. During a typical FEX or in a combat environment, it is 

common for Marines to conduct 24-hour operations that include day and nighttime 

operations/patrols, standing firewatch or a security post, and conducting continuing 
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tactical actions. Outside the assessed trials, there were minimal tasks required of the 

volunteers that demanded any degree of physical strain. 

7.3 Other Combat Arms MOSs

This event did not address the potential mission-effectiveness impacts of assigning 

women to the Reconnaissance Man (0321) and Critical Skills Operator (0372) MOSs.

Given the particularly physically demanding nature of these MOSs, future studies 

should to examine the physically demanding tasks associated with these MOSs and 

conduct a similar assessment.

7.4 Limited Number of Tasks and Missions

This event did not address all potential tasks or missions of all closed MOSs, nor did it 

address all provisional rifle company tasks that female Marines in open MOSs assigned 

to previously closed units could perform. Instead, this event focused on what were 

considered the most physically demanding tasks that Marines could reasonably be 

expected to perform on a frequent basis. Additionally, tasks were chosen that were of a 

limited duration (maximum of several hours to complete) due to the requirement that 

tasks be repeatable in the form of experimental trials. In the event that more physically 

demanding tasks are identified in the future, additional studies may be required to draw 

appropriate inferences regarding the physical capabilities necessary to conduct the 

collective tasks.

7.5 Quantity of Volunteers in Select MOSs 

The volunteers for the experiment were drawn from the active and reserve components 

of the Marine Corps. An examination of individual characteristics indicates they are a 

representative sample. Their representativeness, however, does not mitigate the fact 

that in some MOSs there is only a small quantity of males and females in these 

subgroups. In the extreme cases of the experiment, there were no more than three 

males (i.e., PIMG) and females (i.e., tanks) completing the entire experimental phase. 

Caution should be used when considering the generalizability of findings in these 

MOSs.

7.6 Volunteer Characteristics 

The volunteer population was sourced and selected from the operating forces. Our 

sourcing of volunteers from the operating forces means accepting variations in some 

important respects, such as Time in Service, Time in MOS, training levels, and 

physiological development. We cannot be certain that male and female participants 

were totally equitable in these characteristics. All of the female Marines who 

participated in the Closed MOSs & 1371s had no operating force experience in ground 

combat units. Even with the training period prior to the experimental phase designed to 

mitigate differences in training and physiological development, some differences likely 

remained. Future studies with longer time horizons would benefit from recruiting 

participants at the same entry point, such as at the Marine Corps Recruit Depots. 
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7.7 Volunteer Selection Bias 

The GCEITF experiment is likely to suffer from selection bias – the idea that the 

Marines’ decision to participate (volunteer) in the experiment may be correlated with the 

specific traits that affect the study itself. This could manifest itself in the volunteers’ 

motivation, performance, survey answers, and other aspects of the experiment. To the 

extent that we can, we try to ensure the sample was representative of the population of 

Marines, with respect to observable physical characteristics that the USMC collects and 

records. 

7.8 Explaining Group Outcomes with Individual Characteristics 

The experiment was designed to detect differences in performance of gender-integrated 

and all-male units. We also tried to determine how individual characteristics contribute 

to group outcomes in our attempt to inform gender-neutral standards. We do this using 

data on each individual volunteer in the group, sometimes combining variables, when 

sample size permitted. Ultimately, however, our models assume a very specific 

functional form: we assume that the group outcome depends on some linear 

combination of all participants’ personnel variables. Intuitively, this need not be the 

case, and the poor fit of many of our models confirms that we gain little explanatory 

power by including personnel variables. This is not to say that the variables do not have 

an impact on the outcome, just that more complex modeling may be needed to uncover 

these relationships.

7.9 Statistical Independence 

An important underlying assumption of some of the statistical analysis techniques we 

used, basic inferential statistics, is that the outcomes of each trial are statistically 

independent of each other. For many of the tasks, this assumption is justified because 

the number of volunteers was sufficient and their roles within tasks had little relationship 

to each other. Thus, when the same individual was sampled multiple times for the task 

but was performing different functions or was binned with different people, the data are 

considered sufficiently independent for the purposes of the experiment. In the case of 

provisional machine guns, tanks, and assaultman/antitank missileman that assumption 

is questionable. In these three cases, we had only three males (PIMG) and three 

females (tanks & 035X) who were able to complete the entire experiment. With so few 

people from a specific gender representing an MOS, we cannot be certain that each trial 

is necessarily independent. Caution should be used when considering the 

generalizability of results in these MOSs!

8. Methods

The specific methods for conduct of the experiment can be found in the EAP, 

reference (c). Annex R of this report describes the analysis methods used in the 

construction of the reported results. What follows in this section is a timeline and 
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description of major experimental events and milestones as shown in Figure 1. This 

section also contains an explanation of the types of groups that formed the basis for 

comparison.

Figure 1. Timeline of Major Experimental Events and Milestones

8.1 Recruitment and Selection 

The majority of recruitment, selection, and notification activities occurred during May 

through June 2014. Some recruitment took place after that timeframe, but prior to 

December 2014, to backfill volunteers who prematurely withdrew. Recruitment was 

done through formal in-person briefs, via phone, and web-based recruitment. Selection 

and notification occurred through formal message traffic.

8.2 GCEITF Unit Activation and Formal Schools 

The GCEITF was formally activated on 1 July 2014 at Camp Lejeune, NC. During the 

activation period, the unit obtained facilities, equipment, and materiel necessary to 

conduct unit training prior to the experiment phase. Concurrent with unit activation was 

female volunteer attendance at Formal Learning Centers for MOS training. MOS 

training for female volunteers for combat arms MOSs occurred in multiple locations 

beginning July 2014 and concluding mid-October 2014. 

8.3 GCEITF Unit Training Period 

The GCEITF unit training period formally began on 1 October 2014 and continued until 

mid-February 2015 when the GCEITF arrived at the Marine Corps Air Ground Combat 

Center (MCAGCC), Twentynine Palms, CA. During the unit training period, volunteers 

5/2/2014 8/14/2015

1/1/2015

5/19/2015

Experiment 

Complete

5/2/2014

Plan Approved

5/31/2014 - 6/8/2014

Formal Volunteer 

Recruitment

Window

8/14/2015

Report Complete

5/22/2014

Volunteer 

Solicitation 

Message

Released

6/16/2014

Volunteer

Selection 

Message 

Released

7/7/2014

First Female 

Volunteers to 

Formal Learning Centers

2/18/2015 - 5/31/2015

Deployed Experiment Phase

3/9/2015

Record 

Trials Begin

2/18/2015

GCEITF

Unit Training

Concludes

2/28/2015

Pilot Trials

Begin

7/1/2014

GCEITF Unit

Activation

5/1/2015

Mountain Warfare

 and 

Amphibious Phase

Begins

5/31/2015

All Volunteers

Return to 

Camp Lejeune

10/1/2014 - 2/18/2015

GCEITF Unit Training Period

10/1/2014

GCEITF

Unit Training

Period Begins

7/14/2015

GCEITF Unit

Deactivation

8/15/2014

Volunteers Begin

Arrival at GCEITF
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learned and rehearsed the live-fire and non-live-fire tasks necessary for experimental 

conduct.

8.4 Experiment Phase 

The experiment phase began on 18 February 2015 with the arrival of the GCEITF at 

MCAGCC. The first 2 weeks allowed for volunteer acclimatization, range setup, and 

rehearsals of experimental tasks and data collection. Beginning 28 February 2015, 

volunteers began pilot trials. The pilot trials were identical to record trials with one 

exception; they were not used in the analysis. Pilot trials allowed the volunteers to work 

through learning-curve issues associated with performing the task in a new environment 

and in the presence of data collection. By 9 March 2015, record trials began for the 

experiment and trials continued throughout March, April, and into mid-May. During the 

conduct of record trials, various MOSs completed their formal experimentation phase at 

MCAGCC while others transitioned from MCAGCC to the Mountain Warfare Training 

Center (MWTC) and Marine Corps Base Camp Pendleton by 1 May 2015. All record 

trials were completed by 19 May 2015 at all locations and the GCEITF transitioned all 

personnel back to the unit’s home station at Camp Lejeune, NC.

8.5 GCEITF Unit Deactivation and Reporting Period 

Upon return to Camp Lejeune, the active duty volunteers were issued follow-on orders 

to new units. Volunteers from the reserve component were deactivated and returned to 

their home of record. The GCEITF also divested the remainder of equipment and 

materiel, and formally deactivated on 14 July 2015. Data reduction and analysis took 

place during the final deactivation and volunteer transition period with formal reporting 

of results completed by mid-August.

8.6 Small Unit Group Compositions 

In support of research objectives, the MCOTEA team took measurements as 

participants of the GCEITF performed operationally relevant tasks in groups. The 

experimental plan specified that for each MOS, one experimental group would be allmale (control group), one would contain a low-density of females, and the third would be 

high-density. However, as volunteers left the experiment, some concentration levels 

had to be changed or dropped from evaluation altogether. For each MOS, trials were 

run for at least the control group and one of the integrated concentrations. The result of 

each trial for each of these units constitutes one observation for the collective tasks 

analysis. The final male-female concentrations, per MOS, are displayed in Table 1. 
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Table 1. Group Size and Female Concentration Levels by MOS

MOS Total in Group

Number of Females in 

Low-Density Group

Number of Females in 

High-Density Group

0311 12 NA 2

0313 3 1 2

0331 3 1 2

0341 4 NA 2

035X 4 NA 2,3,4

PI 12 2 4,5

PIMG 3 NA 3

0811 6 1 2

1812 2 1 NA

1833 3 1 2

1371 8 2 4

Mountaineering 

Closed MOS 12 NA 6 

Mountaineering

Open MOS 12 NA 6 

8.7 Small Unit Leadership 

Each small group defined in Table 1 had some level of military leadership. The Marines 

in leadership positions were non-volunteers of sufficient rank and experience to ensure 

tactically sound and safe operations during the conduct of the experiment. As an 

example, the 0311 MOS had 12 Marine volunteers and a squad leader who was not a 

volunteer for a total of 13 Marines in the rifle squad. 

The non-volunteer leadership Marines did not materially participate in the conduct of 

tasks. Even with non-participation, the influence of leadership can have an impact on 

the outcome of military effects. To mitigate this effect, we applied appropriate 

randomization of volunteers under different leaders as a control measure during 

conduct of the experiment. 

9. Results

(FOUO) This section of the report covers results for each experimental objective. 

Contained within each objective are the MOS tasks that begin with an operational view 

and task description followed by the results observed. The results are presented in 

terms of whether or not statistically significant differences are observed between 

groups, and occasionally by gender. In the majority of the results, the numerical details 

are left to the Annexes of this report, except where it was necessary to illustrate 

performance compared to an existing standard or to illustrate trends observed, as a 

results of basic inferential statistics. Unless otherwise stated in the results, we consider 

significant differences observed and reported to have at least some relevant operational 

impact, either by themselves or when taken together with other tasks in the context of 

actual combat operations. 
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9.1 Objective 1 

9.1.1 Infantry

(FOUO) The infantry assessment was a 2-day scheme of maneuver intended to 

replicate offensive and defensive tasks. The infantry assessment included Infantry 

Rifleman (MOS 0311), Machine Gunners (MOS 0331), Mortarman (MOS 0341), and 

Assaultman/Antitank Missileman (MOS 035X). All Marines, regardless of task, wore the 

fighting load (35 lb) and carried a personal weapon (6.4 lb, 7.9 lb, or 10.5 lb, depending 

on weapon type).

9.1.1.1 Trial Cycle Day One

(FOUO) The first day of the infantry assessment was a coordinated, live-fire squad 

attack employing the rifle, machine gun, mortar, and assault squads. The coordinated 

attack allowed for simultaneous employment of all squads in close proximity on the 

same range for operational realism, but with offsets in battlespace geometries of fire to 

allow for independent observation and measurement of mission effects, fatigue, and 

workload. In general terms, the coordinated attack began with an initial movement,

followed by an enemy engagement and consolidation on the objective, and concluded

with a casualty evacuation. Day one was a fluid scenario that allowed the Marines to 

flow from beginning to end without interruption or breaks. Figure 2 is an illustration of 

the infantry live-fire attack. At the conclusion of the casualty evacuation the Marines 

operated under the guidance of their Company leadership, performing tasks that 

required minimal physical demands, and then bivouacking in the field, sleeping in 2-man 

tents. 
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Figure 2. Infantry Day-One Scheme of Maneuver

9.1.1.1.1 Initial Movement

(FOUO) The assault began from an assembly area with a rapid movement to assault 

position. The initial movement was approximately 1 km to the mortar firing point 

(0341s), support by fire position (0331s), and assault position (0311s & 035Xs). Each 

squad moved this distance as quickly as possible while carrying an assault load (30 lb). 

In addition to the assault load, the following additional equipment was carried by non0311 squads:
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• 0331s: The M240B machine gun, tripod, spare barrel, and ammunition (600 

rounds of 7.62 mm) divided among the three members of the squad (additional 

28 – 40 lb per person)

• 0341s: Two 60-mm mortar tubes, two M8 auxiliary baseplates, and six 60-mm 

mortar rounds divided among the four members of the squad (additional 28 – 

35 lb per person)

• 035Xs: Two SMAW launchers and four rockets divided among the four members 

of the squad (additional 26 – 42 lb per person)

The all-male squads, regardless of MOS, were significantly3 faster than the integrated 

squads. The differences observed between all-male and integrated squads were more 

pronounced in non-0311 squads that carried the assault load plus the additional weight 

of crew-served weapons and ammunition. Figure 3 shows the percent increase in 

average times when comparing integrated groups to all-male groups. Only the 0331 

squads had low- and high-density squads to compare to all-male squads. The 

remaining MOSs had only enough volunteers for high-density squads to compare to allmale squads.

 

Figure 3. Percent Increase in Initial Movement Times for 

Integrated Squads Compared to All-male Squads

9.1.1.1.2 Negotiate Obstacles

(FOUO) Upon arrival at the assault position, the 0311s and 035Xs Marines were 

required to negotiate an 8-ft wall by getting all Marines and equipment over as quickly 

 

3 In this report the term “significant” is shorthand for statistically significant. In layman’s terms, we say that 

something is statistically significant if it has a low likelihood of being due to random chance or error. The 

cut-off point for that likelihood is 10%. In technical terms, that means statistically significant with at least a 

one-sided p-value ≤ 0.10.
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as possible. The squads were allowed to negotiate the obstacle any way they chose, 

as long as they maintained the appropriate tactical posture. The differences that 

resulted when comparing 0311s and 035Xs are largely a result of the technique used 

and the quantity of individuals within a squad (12 for Rifle Squads, 4 for Assault 

Squads). 

When comparing integrated 0311 squads to all-male 0311 squads we saw no significant 

differences in times. There was, however, an issue with getting assault packs over the 

wall. Prior to negotiating the wall, 0311 Marines doffed their assault packs and 

individually threw them onto the top of the 8-ft wall prior to climbing. Females in 

integrated squads were noted as having required assistance from male squad members 

to get their packs onto the wall. Male Marines in the squad did not require the same 

assistance. 

Unlike the 0311 integrated squads, the integrated 035X squads took significantly longer 

to negotiate the wall obstacle than all-male 035X squads. The assault squads were 

formed by combining teams, each with two Marines. When both teams in a squad were 

all-female, the 035X squad used their belts as a ladder to help the last Marine over the 

obstacle. When there was at least one male in the high-density squad, this technique 

was not required. 

9.1.1.1.3 Fire and Movement

(FOUO) While the 0311s and 035Xs were negotiating the wall obstacle, the 0341s and 

0331s were occupying their respective mortar firing points and a support-by-fire position

to suppress enemy targets and prepare the objective for the rifle squad. 

9.1.1.1.3.1 Indirect Fire - Mortar Squad 

(FOUO) The 0341s on the right flank typically began the attack by using indirect fire to 

suppress the enemy and to prepare the objective for the rifle squad to locate, closewith, and destroy the enemy by fire and maneuver. When the attack was conducted, 

60-mm mortars were employed in the handheld method. Each two-Marine mortar team 

engaged one target from two different mortar-firing points with three rounds per point

and finally moved to a limit of advance. In this attack, the integrated 0341 squads were 

significantly slower than the all-male 0341 squads at providing indirect fires. The attack 

started with integrated and all-male 0341 squads performing similarly at the first mortarfiring point, but as the scenario continued, the differences among group results 

emerged, with the integrated groups falling behind (i.e., taking longer) at the second 

firing point and on the movement to the limit of advance.

9.1.1.1.3.2 Suppressive Fire - Machine Gun Squad 

(FOUO) The 0331 machine gun squad operated on the left flank and their timing for 

movement closely followed the 0341 squads. The machine gun squad occupied a 
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position of overwatch and provided support-by-fire for the rifle squad. From the supportby-fire position, the machine gun squad had to rapidly get its gun into action, acquire 

targets, and accurately engage the enemy. 

The movement and emplacement of the machine gun took significantly longer with both 

low- and high-integrated groups when compared to all-male groups; but there was no 

significant difference in effects (i.e., hits and near misses) on target once emplaced. 

9.1.1.1.3.3 Rifle Squad Attack and Counterattack

(FOUO) The mission of the rifle squad is “to locate, close-with, and destroy the enemy 

by fire and maneuver, and repel the enemy’s assault by fire and close combat.” Having 

negotiated the 8-ft wall obstacle, the rifle squad deployed into an on-line formation to 

maximize firepower in the direction of the enemy and then moved with weapons at the 

ready expecting imminent contact. Upon contact with the enemy (targets being 

presented), the Marines established a heavy volume of fire to gain fire superiority. They 

then began buddy rushes to close-with the enemy objective. Each squad conducted 

approximately 300 meters of buddy rushes, engaging a total of 12 targets with direct-fire 

weapons and three machine gun bunkers with the M16A4 with M203 grenade launcher 

attached. After all targets were destroyed (no targets remaining), the squad moved 

another 125 meters to a limit of advance and prepared for an enemy counterattack. 

(FOUO) At the conclusion of every assault, the attacking unit must be prepared for the 

enemy to regroup and organize a counterattack. Upon consolidation at the limit of 

advance, the squad oriented its weapons in the direction of the enemy’s retreat. Upon 

target presentation, the counterattack commenced for 90 seconds. 

(FOUO) The principle measurement of the squad’s ability to destroy the enemy by fire 

during the attack and counterattack was hits on target. When comparing integrated 

0311 squads and all-male squads, the integrated 0311 squads had a significantly lower 

probability of hit. The squad attack involved all 12 Marines engaging targets. Each 

Marine can, and often does, engage some of the same targets because of overlapping 

sectors of fire. To uncover whether or not a gender effect existed in accuracy at the 

individual level, individual shots recorded by targets were correlated back to shooters. 

This enabled an investigation of gender differences by weapon system (i.e., M4, M27, 

and M16A4/M203). 

(FOUO) Analysis of shot accuracy by gender and weapon reveals that there is a 

significant difference between genders for every weapon system within the 0311 

squads, except for the probability of hit & near miss4 with the M4. 

 

4 Hits are shots that impact the E-silhouette target. Near misses are shots that are detected within 1-

meter of outside edge of E-silhouette target that may have some suppressive effect on the enemy.
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(FOUO) Figure 4 and Figure 5 depict accuracy results for males versus females by 

weapon type. The overall accuracy declined and the percent difference increased as 

the weight of the weapon system increased. The M4 was the lightest weapon and 

yielded the most accurate results, while the M16A4/M203 was the heaviest weapon and 

yielded the least accurate results. 

(FOUO) One might think that experience level of the Marines (male vs. female) 

influenced the results observed in the 0311s. However, the male Provisional Infantry 

(PI) results do not support this conjecture. PI males had no infantry experience and, in 

this regard, were similar to female 0311s prior to the experiment. The PI males had a 

further disadvantage because they had not completed the 0311 MOS course. Despite 

these differences, the PI males had higher hit and near-miss percentages than the 0311 

females, as shown in Figure 4 and Figure 5. 

Figure 4. Accuracy Comparison by Gender and Weapon Type for Hits
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Figure 5. Accuracy Comparison by Gender and Weapon 

Type for Hits and Near Misses Combined

9.1.1.1.3.4 Assault Squads 

(FOUO) An assault squad often accompanies a rifle squad into an attack. The assault 

squad provides high-explosive rocket fires to reduce fortifications or destroy other 

designated targets. When employing the Shoulder-launched Multipurpose Assault 

Weapon (SMAW), the squad prepared their rockets from a covered position, commonly 

referred to as a cold position. Then they moved to an exposed position, approximately 

50 meters, with a good line of sight to the enemy, commonly referred to as a hot 

position. Once at the hot position, they engaged an armored vehicle, conducted a rapid 

reload, engaged a second armored vehicle, and displaced back to the cold position.

(FOUO) The integrated 035X squads took significantly longer to engage targets and got 

significantly fewer hits on target as compared to the all-male squads during the 

engagements. The combination of the two results makes the integrated squads more 

vulnerable and less lethal than their all-male counterparts. 

9.1.1.1.4 Movement to Limit of Advance

(FOUO) The ability to close with the objective after conducting a live-fire attack is crucial 

to maintaining momentum during offensive operations. At the conclusion of the live-fire 

attack, the 0311 squads moved 125 meters to a limit of advance. The 0331 and 0341 

squads also conducted a displacement to a limit of advance, but the distance was 300 
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meters. The integrated 0311, 0331, and 0341 squads took significantly longer than their 

all-male counterparts to complete their movement to the limit of advance. The late 

arrival reduces the time to prepare for, or respond to, the counterattack launched by an 

enemy force. 

9.1.1.1.5 Casualty Evacuation

(FOUO) Casualties are an inevitable part of conducting combat operations. Units train 

to become proficient in the triage, handling, and transport of a casualty. After a Marine 

is injured, it is essential to move the casualty to the appropriate level of care as quickly 

as possible. Each 0331, 0341, and 035X squad was assigned one casualty to evacuate 

upon conclusion of the live-fire attack and counterattack. Rifle squads (0311) had 12 

Marines in a squad as compared to 4 or 3 for the other squads. Because the rifle 

squads had three times the number of Marines, each rifle squad had three casualties to 

evacuate (i.e., one casualty for every three to four Marines). 

(FOUO) The casualty was a dummy5 wearing combat equipment that had to be moved 

a distance of 100 meters to a casualty collection point along with the weapons and gear 

of the Marines performing the transport. The Marines could use a variety of techniques 

for transport, but had to carry the dummy off the ground (not drag any part) and could 

not drop the casualty. 

(FOUO) The differences between integrated squads and all-male squads vary

substantially by MOS (Figure 6). The 0341s showed no significant differences in 

evacuation times while the 035Xs showed the largest significant observed difference in 

the entire experiment. The only commonality across the casualty evacuation for the 

four MOSs was the casualty itself. Each MOS had one or more techniques for carrying 

out the evacuation that depended upon the abilities of the Marines carrying out the task. 

 

5 The dummy was a full-scale anthropomorphic test device that simulated the dimensions, weight 

proportions, and articulations of the human body. The dummy’s weight was equivalent to an average 

Marine (174 lb). When combat equipment (Marine Corps Combat Utility Uniform, boots, Kevlar helmet, 

plate carrier vest with small arms protective insert plates, and M16A4) was added to the dummy, the total 

weight increased to 220 lb. 
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Figure 6. Percent Increase in Casualty Evacuation

Times by MOS and Integration Level

9.1.1.1.5.1 Mortar Squad Casualty Evacuation

(FOUO) The 0341s had the smallest difference in average time between integrated and 

all-male squads, and the difference in time was not significant. However, the method of 

employment used by this group explains why differences in times may not be 

significant. The 0341s largely employed a single-Marine fireman’s carry to move the 

casualty. Furthermore, in a majority of the integrated trials, the person carrying the 

casualty using the single fireman’s carry technique was male, not female. 

9.1.1.1.5.2 Rifle Fireteam Casualty Evacuation

(FOUO) The 0311 results were analyzed by 4-person fireteams instead of by squad for 

this task because the effort was conducted independently between fireteams. The 

integrated fireteams were significantly slower than the all-male fireteams. At the 

discretion of each fireteam, Marines used a 2-Marine, 3-Marine, or 4-Marine carry to 

move the casualty. 

9.1.1.1.5.3 Machine Gun Squad Casualty Evacuation

(FOUO) The all-male 0331 squads were significantly faster than high-density integrated 

squads, but not significantly faster than low-density integrated squads. The 0331 

squads used a mix of techniques to carry the casualty, which explains some of the 

variability in the observed results. The most prominent explanation of why differences 

may not be significant between all-male and low-density 0331 squads is the use of the 

single fireman’s carry. The top one-third of results of the low-density squads were 

almost exclusively male fireman’s carry results.
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9.1.1.1.5.4 Assault Squad Casualty Evacuation

(FOUO) The largest difference observed in the experiment occurred in the 035X 

casualty evacuation where the all-male 035X squads were significantly faster than the 

integrated squads. The 035X squads used a mix of techniques to include a 2-Marine, 

3-Marine, and 4-Marine carry. In this task, like other 035X tasks, the all-male squads 

were almost always compared to all-female squads. 

9.1.1.1.6 Infantry Day One Fatigue and Workload

9.1.1.1.6.1 Comparing Male Responses to Female Responses

(FOUO) Two self-report surveys (fatigue and workload) were administered to all 

volunteers at the end of trial activities on day one of the trial cycle. The surveys were 

intended to provide insights into Marines’ perceptions of their own level of fatigue and 

workload level during the course of offensive trials. 

(FOUO) Overall, males tended to report lower levels of fatigue and workload when 

compared to females in the 0311, 0331, and 035X squads. In 0341 squads, females 

actually reported lower levels of fatigue and no differences in workload when compared 

to males. 

9.1.1.1.6.2 Comparing Male Responses in Integrated Squads to All-male Squads

(FOUO) In addition to comparing male and female fatigue and workload self-reports, we 

also examined whether responses from males remained consistent at different 

integration levels. 

(FOUO) The reported fatigue levels of males did not appear to change depending on 

integration of the squad with the exception of 0331 males. Males in high-density 

integration squads actually reported lower levels of fatigue than when they participated 

in all-male or low-density integrated squads. 

(FOUO) Male opinions on workload were more mixed than male fatigue results. Males 

in 0311 and 0331 squads reported lower workload results when in integrated squads 

when compared to all-male squads. Males in 0341 and 035X squads reported no 

differences based on integration level. 

9.1.1.2 Trial Cycle Day Two

(FOUO) The second day of the infantry assessment focused on an approach march for 

all squads, defensive actions of the rifle squad, and heavy weapons employment of the 

machine gun, mortar, and anti-armor squads, as shown in Figure 7. At the conclusion 

of the defense and weapons employment, the Marines operated under the guidance of 

their Company leadership, performing tasks that required minimal physical demands, 

and then bivouacking in the field, sleeping in 2-man tents.
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Figure 7. Infantry Day-Two Scheme of Maneuver

9.1.1.2.1 Approach March

(FOUO) The beginning of day two started with a march carrying the approach load

(55 lb)6. Moving under a load is one of the most fundamental tasks of an infantry unit; it 

is both physically and mentally demanding. Units train by conducting tactical marches 

with an approach load at increasing distances. The Infantry Training & Readiness 

Manual states: “the approach march load will be such that the average infantry Marine 

will be able to conduct a 20-mile hike in 8-hours with the reasonable expectation of 

maintaining 90% combat effectiveness.” Each squad moved a distance of 7.20 km

carrying the approach load and personal weapons. In addition to the approach load, the 

following additional equipment was carried by non-0311 squads:

• (FOUO) 0331s: The M240B machine gun, M122A1 tripod, spare barrel, and 

ammunition (4 cans of 7.62 mm) divided among the three members of the squad

(additional 28 – 40 lb per person). 

 

6 The approach load is in addition to the fighting load (35 lb) and personal weapon (6.4 lb, 7.9 lb, or 10.5 lb 

depending upon weapon type assigned).
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• (FOUO) 0341s: 81-mm mortar tube, baseplate, bipod, and box sight divided 

among the four members of the squad (additional 28 – 35 lb per person). 

• (FOUO) 035Xs: Two SMAW launchers and four rockets divided among the four 

members of the squad (additional 26 – 42 lb per person). 

(FOUO) The all-male squads, regardless of MOS, were significantly faster than the 

integrated squads. The differences observed between all-male and integrated squads 

are more pronounced in non-0311 squads, which corresponds to an increase in carried 

weight of crew-served weapons and ammunition in addition to the approach load. 

Figure 8 shows the percent increase in average times when comparing integrated 

groups to the all-male groups. 

Figure 8. Percent Increase in Approach March Times for

Integrated Squads Compared to All-male Squads

(FOUO) The differences illustrated in Figure 8 follow the same pattern observed in the 

initial movement. The march with approach load has an applicable standard that can be 

used to provide a second frame of reference. Movement over 20 miles in 8 hours 

equates to a pace of 4 kilometers per hour (km/h). Figure 9 shows a conversion of the 

average squad times over the 7.2-km distance to pace. This conversion enables a 

comparison to the 4-km/h required to meet the standard. As shown in the figure, the

only integrated squad to achieve the standard is the integrated (high-density) 0311 

squad. Regardless of MOS, the all-male squads surpassed the 4-km/h standard. The 

figure is also illustrative of the impact that additional weight has on pace. There is a 

corresponding decrease in the pace as weight of the carried load increases. 
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Figure 9. Conversion from Average Elapsed Time for the 7.2-km 

March to Pace for the 03XX Approach March

9.1.1.2.2 Defensive Fighting Positions & Heavy Weapons Employment

(FOUO) Upon completion of the approach march and after a brief rest period, the 

infantry moved into the defense. The 0311 Infantry Marines moved into the preparation 

of defensive fighting positions while the other MOSs (0331, 0341, and 035X) moved into

heavy weapons employment.

9.1.1.2.2.1 Fireteams Preparing Defensive Fighting Positions

(FOUO) Protection is vital to infantry units, especially in a defensive posture. Infantry 

units commonly construct fighting positions to conceal positions and minimize exposure 

to enemy fire. There are many characteristics to constructing a doctrinal fighting 

position, but the most physically demanding aspect is digging out the fighting hole. The 

terrain where the fighting holes were dug consisted of hard, compact sand and rocks. 

Each 0311 fireteam dug two 2-man fighting holes in a time limit of 2 hours, maintaining 

50% security, meaning two Marines dug while two provided security in the prone 

position. The Marines swapped positions every 15 minutes. During the course of this 

task, the earth was scooped into buckets and weighed. 

(FOUO) The average weight of earth moved by the integrated 0311 fireteams was not 

significantly different than the weight moved by the all-male groups. 
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9.1.1.2.2.2 Squad Employment of M2 Machine Gun 

(FOUO) Providing defensive fires with the M2 heavy machine gun entails moving the 

system to a position of advantage, engaging the enemy, and conducting a rapid 

displacement. After completing the approach march, the 0331 squads dismounted the 

M2 heavy machine gun from a vehicle platform, moved and emplaced the weapon, 

engaged targets, displaced, and mounted the weapon onto a vehicle platform. 

(FOUO) To dismount the weapon system, the squad worked together to manually 

disassemble and lower each component to the ground from a High-Mobility MultiWheeled Vehicle (HMMWV). To mount the weapon system on the HMMWV, the 

process was reversed. This task determined the time for a squad of three Marines to 

fully dismount and mount the M2 from a tactical vehicle and required the strength to lift, 

manipulate, and lower heavy components. 

(FOUO) The integrated 0331 squads’ average time was not significantly different than 

the average time for all-male groups, for either mounting or dismounting the M2 heavy 

machine gun. 

(FOUO) During the assessment, each machine gun squad emplaced the M2 on a tripod 

at a specified firing location. The squad engaged targets as they began to be exposed 

while hits on, and around, the target were recorded by sensors. The assessment began 

with targets exposed and engaged by the squad. 

(FOUO) The high-density integrated 0331 squads had significantly more hits on target 

than the all-male squads. The low-density 0331 squads also had more hits on target 

than the all-male squads, but the difference was not significant. Figure 10 shows the 

percentage of hits and near misses7 on the machine gun targets. The finding that 

integrated groups have a higher percentage of hits on target is somewhat unusual given 

the findings from 0311 hit percentages. To see if there is a consistent finding, the 

results of provisional machine gunners were compared to the 0331 squads. As shown 

in Figure 10, the trend of integrated groups outperforming all-male groups is repeated 

and consistent. 

 

7 For experimental purposes, a hit or near miss for a machine gun target is defined as any detectable 

round within a 3-meter radius from the center of the target.
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Figure 10. M2 Heavy Machine Gun Hits and Near 

Misses by MOS and Integration Level

(FOUO) After an engagement, a machine gun squad must be able to break down their 

weapon system and move to a position of cover as rapidly as possible. Immediately 

upon completing target engagement, the 0331 squad took the gun out of action and 

displaced 100 meters from the firing line to a designated location, moving a heavy load 

a short distance, manipulating the weapon while fatigued. 

(FOUO) The high-density integrated 0331 squad took significantly longer to displace 

from the firing line compared to both the all-male and low-density integrated 0331 

squads. 

9.1.1.2.2.3 Squad Employment of 81mm Mortar 

(FOUO) Indirect fire is used to suppress the enemy from outside the direct-fire weapon 

range and prepare the battlefield to allow the rifle squad to complete its mission of 

locate, close-with, and destroy the enemy by fire and maneuver. After completing the 

approach march, the 81-mm mortar squad conducted an emplacement of the crewserved weapon, engaged two different targets with five 81-mm rounds each, and 

conducted a displacement of the mortar system. The mortar team engaged the targets 

using the direct-lay method and visually acquired and adjusted all rounds during each 

fire mission.

(FOUO) The focus of the mortar squad is their ability to move an 81-mm mortar system 

and 10 mortar rounds approximately 100 meters from an operational rally point to a 

mortar firing position (MFP), get the mortar system fire capable (FIRECAP), and 

conduct a displacement back to the rally point. Although the mortar squads engaged 

two targets with five rounds each after the mortar system was FIRECAP, accuracy was 

not assessed because of the heavy dependence on skill and meteorological conditions.
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(FOUO) The integrated 0341 squads had no significant differences compared to the allmale 0341 squads with respect to emplacement and displacement times. What the 

times did not capture was a masking effect that occurred within the emplacement 

portion. The initial movement portion of this task (a physical-based capacity) was 

masked by the time it took to assemble the mortar and sight in on the target (a skillbased capability). 

(FOUO) For example, it was observed that when slower members of the squad fell back 

during the initial movement, their delay was masked (not captured) by the fact that the 

rest of the team began emplacing the 81-mm mortar system concurrently. By the time 

the weapon system was FIRECAP, all members had arrived at the MFP. Therefore, a 

squad that moved quickly versus a squad that got spread out was diffused by the time it 

took to sight-in on the target because the movement distance was only 100 meters. 

9.1.1.2.2.4 Squad Employment of Tube-launched, Optically tracked, Wire-guided (TOW) Missile 

System

(FOUO) The TOW missile fired out of the Saber system is generally employed from a 

mounted platform, such as an HMMWV. Members of an anti-armor squad must mount 

and dismount the Saber system to an HMMWV. During the mounting of the Saber 

system, the calibration process was not performed due to its technical nature and the 

time required. The mounting and dismounting tasks were selected due to the physical 

strength required to lift, curl, and press the Saber components up and lower them down 

by members of the squad without damaging the system. 

(FOUO) The challenging aspect of mounting and dismounting the Saber system is the 

weight of the components. The integrated 035X squads performed the mount and

dismount significantly more slowly than the all-male 035X squads. When mount and 

dismount were examined separately, the integrated 035X squads were significantly 

slower in both tasks. 

(FOUO) The more challenging method of employing the TOW missile is from a tripod to 

provide defensive fires. During the assessment, a precalibrated Saber system was 

mounted on a tripod at a designated firing position. Each anti-armor squad moved four 

TOW missiles to the firing line and engaged two designated targets, firing each missile 

in sequence. One missile reload per team was conducted between the first and second 

shots. 

(FOUO) This task was chosen due to the strength required to move each missile and 

the ability to employ the TOW while fatigued. The integrated 035X squads took 

significantly longer to engage targets when compared to the all-male 035X squads, but 

the hit percentage showed no significant differences. The combination of increased 
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engagement times, but similar hits on target makes the integrated squads more 

vulnerable than their all-male counterparts. 

9.1.1.2.3 Infantry Day Two Fatigue and Workload

9.1.1.2.3.1 Comparing Male Responses to Female Responses

(FOUO) Two self-report surveys (fatigue and workload) were administered to all 

volunteers at the end of trial activities on day two. The surveys were intended to 

provide insights into Marines’ perceptions of their own level of fatigue and workload 

level during the course of defensive trials. 

(FOUO) Overall, males tended to report lower levels of fatigue and workload when 

compared with females, with the exception being 0331 and 0341 squads. In the 0331 

squads, males and females reported similar fatigue levels. In the 0341 squads, males 

and females reported similar fatigue and workload results. 

9.1.1.2.3.2 Comparing Male Responses in Integrated Squads to All-male Squads

(FOUO) In addition to looking at how fatigue and workload self-reports compared 

between males and females, we also examined whether males responses remained 

consistent at different integration levels. 

(FOUO) Overall, the reported fatigue and workload levels reported by males tended to 

decrease when in integrated squads. Initially, this may appear to be a counterintuitive 

finding, until the results are considered in the context of the task performance. On day 

two, the common task for all 03XX squads is the 7-km approach march. When males 

were in integrated squads, they tended to move at a slower pace when compared to allmale squads. The slower pace for males in integrated squads was likely a factor for 

reduced fatigue and workload. 

9.1.1.3 Mountain Warfare (Infantry)

(FOUO) The mountaineering assessment replicated a logistical resupply of a forwardstaged squad while moving in a mountainous environment. Each 12-Marine squad 

departed an assembly area located at a lower base camp where they hiked 4.6 km with 

a 75-lb pack and personal weapon (M4) to an objective rally point. The route for this 

movement was on an unimproved, hilly surface; the terrain was hard and rocky, and 

uphill, with an approximate gain in elevation of 175 meters, as shown in Figure 11. 
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Figure 11. Elevation Change in Meters over 4.6-km Hike Distance

(FOUO) From the objective rally point, the squad crossed a 200-ft gorge via two singlerope bridges. Once across, the squad pulled their packs across and made a short 

movement to a location requiring a cliff ascent. Each Marine executed a 40-ft cliff 

ascent using two climbing lanes. The final action was to conduct a return foot-march to 

lower base camp. The return march was 5 km while wearing the 75-lb pack and 

personal weapon across terrain similar to the ascent, but downhill. The entire resupply 

mission took approximately 5 hours to complete.

(FOUO) The mountaineering tasks were non-MOS-specific tasks. Due to the non-MOSspecific nature of the tasks, all Marines from 0311, 0331, 0341, 0351, and 0352 MOSs 

were combined for the purposes of forming 12-Marine squads. Two types of squads 

were formed each day, all-male and high-density integration squads8

. 

(FOUO) Every Marine received 1 day of recovery after each execution day over the 

course of 15 days. At the end of a day and during off-days, the Marines lived in squad 

bays at lower base camp and operated under Company leadership, performing tasks 

that required minimal physical demands. 

(FOUO) The all-male squads were significantly faster than integrated squads on hikes, 

gorge crossings, and cliff ascents. 

(FOUO) Fatigue and workload self-report surveys were also administered at the end of 

mountain warfare activities, in particular after the ascent hike and upon return to lower 

base camp. When comparing males to females, males reported lower fatigue and 

workload. Males also reported lower fatigue and workload when in integrated squads 

compared with when they were in all-male squads. This finding is similar to the infantry 

day two survey results, where movement under load dominated the task activities. 

 

8 High-density integrated squads had six females per squad.
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9.1.1.4 Infantry Summary

Figure 12 presents a summary of the differences observed when comparing all-male 

squads to integrated squads. The horizontal bars depict the percentage change 

observed when comparing the average all-male squad result to an average integrated 

squad result. The numerical percentage presented adjacent to the bar is indicative of 

statistical significance. Statistical significance is related to the size of the difference, 

variation, and the number of trials for that task. This explains why some larger bars 

show no significance. 

When a bar shifts to the right of the centerline the all-male group’s average is better 

than the integrated group’s. When a bar shifts to the left the integrated group’s average 

is better than the all-male’s. Most of the horizontal bars are shifted to the right for each 

MOS indicating that all-male groups typically outperform integrated groups.

Figure 12. Infantry Summary Comparison of Percentage Change of All Tasks
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9.1.2 Artillery

(FOUO) The Artillery assessment was a 1-day scheme of maneuver intended to 

replicate fire support to a maneuver element. 

9.1.2.1 Scheme of Maneuver

(FOUO) The daily scheme of maneuver was designed around the mission of Marine 

Artillery and its function in a tactical environment. The mission of Marine Artillery is to 

furnish close and continuous fire support by neutralizing, destroying, or suppressing 

targets that threaten the success of the supported unit. The design was to mirror an 

artillery section, providing timely, accurate, and continuous-fire support. 

(FOUO) The artillery Marines operated on a 6-days-on/1-day-off schedule. During the 6 

days they were executing the daily scheme of maneuver, the Marines bivouacked in the 

training area, staying in 2-man tents. All Marines, regardless of task, wore the fighting 

load (35 lb). On the 1 day off, the Battery redeployed to base camp for 24 hours. All 

normal battery operations, such as logistics resupply and dunnage removal, were 

completed by the cannoneers. 

9.1.2.2 Howitzer Emplacement

(FOUO) Emplacement is the method by which a howitzer is changed from its towed 

configuration while attached to a prime mover truck, to a detached position where the 

howitzer is seated on the deck and capable of firing. Emplacement involves 

dismounting the prime mover, placing the trident bar (58 lb) on the deck, manually 

manipulating the trail arms (204 lb), entrenching the spades, and setting up the aiming 

stakes 100 meters away. The Marines performed two emplacements per day during the 

scheme of maneuver. 

(FOUO) The data show that there is no significant difference on the first or second 

emplacement between the all-male gun crews and the integrated gun crews.

9.1.2.3 Ammunition Preparation

(FOUO) Prior to commencing fire missions, the Marines must offload ammunition from 

either the prime mover truck or the ammunition truck, and move it to the ammunition pit. 

One such offload is for emergency fire missions that require an immediate response 

after a hasty emplacement. In this offload, two cannoneers offloaded three M795 High 

Explosive Rounds (105 lb per round) from the Loose Projectile Restraint System (LPRS)

in the bed of the prime mover. The #3 cannoneer was located in the back of the prime 

mover and moved the rounds from the LPRS to the #4 cannoneer on the ground. The 

#4 cannoneer then moved the round from the back of the prime mover to the 

ammunition pit 10 yards away. 
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(FOUO) The data show that there is no significant difference between the all-male gun 

crews and the integrated gun crews when this task was analyzed by integration level, 

and no significant difference when it was analyzed by the gender of the Marines 

performing the critical billets (Cannoneer #3 and #4). 

(FOUO) The second type of ammunition offload is more deliberate, entails more rounds, 

and is sourced from the ammunition truck vice the prime mover truck. The ammunition 

truck offload consisted of four cannoneers offloading 20 M795 High-Explosive rounds 

and 6 M825 Smoke Rounds from the bed of the ammunition truck to an ammunition pit 

on the ground 10 yards away. The M795 and M825 are ballistically and dimensionally 

similar, and offer the same experience in moving the projectile manually. 

(FOUO) The data show that there is no significant difference between the all-male gun 

crews and the integrated gun crews when deliberately offloading ammunition.

9.1.2.4 Fire Missions

(FOUO) Five fire missions were executed by a howitzer section during each 1-day 

cycle. The missions were: a 3-round low-angle High-Explosive (HE), 3-round highangle white-phosphorus (WP) smoke, 9-round low-angle HE, 3-round low-angle smoke 

out of traverse limits, and finally another 3-round low-angle HE from the supplemental 

position. There is no ostensible difference at the gun-section level between a HE and 

WP mission.

(FOUO) Each fire mission began with the Fire Direction Center (FDC) starting the event. 

Procedures for each fire mission were largely the same, regardless of shell and fuze 

combination or angle of fire. While the gun was receiving the firing data from the FDC, 

the crews were simultaneously aiming the howitzer by traversing left or right and 

adjusting the quadrant elevation up and down. The loader, or #4 cannoneer, picked up 

a projectile from the ammunition pit, held it to allow the section chief to inspect the 

round, and then placed the round on to the loading tray. Cannoneer #4 then joined the 

driver and rammed the round into the breech. The #2 cannoneer then loaded the 

powder increments into the breech powder chamber and closed the breech. Finally, the 

howitzer was fired by the #1 cannoneer on the section chief’s command. 

(FOUO) In the case of a high-angle mission, the loading of the projectile occurred prior 

to fully elevating the howitzer, a minor departure in procedure from the low-angle 

missions. The tube would be depressed between shots to facilitate loading.

(FOUO) For all five fire missions, the data show that the all-male gun crews were faster 

and the difference when compared to the higher-integration gun crews (4 male Marines 

and 2 female Marines) was significant, but not when compared to low-integration gun 

crews. 
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9.1.2.5 Ammunition Resupply

(FOUO) A significant portion of a cannoneer’s time in the field is spent moving 

ammunition. This task is physically demanding, as it requires the Marines to pick up a 

155-mm round, weighing 105 lb, from the ground to their shoulder and maintain positive 

control while transporting the round. In a field environment, the ammunition resupply 

truck is often centrally located within a section of howitzers. The typical distance from 

the ammunition truck to an individual howitzer is approximately 100 meters. In the 

ammunition resupply task, all volunteers were required to carry two individual projectiles 

for 100 meters. 

(FOUO) The data show the all-male gun crews were faster and the difference when 

compared to the higher-integration gun crews (4 male Marines and 2 female Marines) 

was significant, but not when compared to low-integration gun crews.

9.1.2.6 Speed Shifts

(FOUO) Deployed howitzer sections often support multiple units in the battlespace. 

Once the howitzer is emplaced, the crew’s ability to respond to a fire mission is 

restricted by the left and right traverse limit forming a 45-degree cone of fire. To engage 

targets outside this cone, the crew performs a speed shift by pumping up the 

suspension and pivoting the howitzer on its wheels by pushing the tube left or right as a 

team. Once aligned in the direction of the target, the crew emplaces the howitzer by 

digging in the trail arms and preparing for the fire mission. 

(FOUO) This task occurred twice during a cycle. Furthermore, while all six cannoneers 

performed this task, the task was analyzed both by integration level and by critical billet. 

The preponderance of the work during this task falls to the #1 and #2 cannoneers, who 

are responsible for manually pumping up the howitzer’s suspension. While there was 

no significance between the all-male gun crews and the integrated gun crews, the 

analysis by critical billet revealed that the differences became significant when the #1 

and #2 cannoneer were assigned as a Male-Female and Female-Female combination. 

This proved to be the same for both speed shifts.

9.1.2.7 Howitzer Displacement

(FOUO) Quick displacement enables a battery to deliver fire support to maneuver units 

and move to the next firing point before the enemy has the opportunity to conduct 

counterbattery fire. During this task, which occurred twice per day, volunteers 

dismantled the ammunition pit, attached the trident bar, pumped the howitzer to ride 

height, and dislodged the howitzer’s dug-in trail arms. The howitzer was transitioned 

from a firing configuration to a towed configuration. 
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(FOUO) The data show the all-male gun crews were faster, and that that the difference 

when compared with the higher-integration gun crews (4 male Marines and 2 female 

Marines) was significant.

(FOUO) Also required was an ammunition upload. Ammunition upload requires 

Marines to pick up a 155-mm round, weighing 105 lb, maintain positive control, and 

push the ammunition up (62 inches) onto the bed of the prime mover truck to stow it for 

transport. Unlike the offload task, this task works against gravity.

(FOUO) The uploading of ammunition took significantly longer with both low- and highintegrated crews when compared with all-male crews. 

9.1.2.8 Artillery Fatigue and Workload

(FOUO) Two self-report surveys (fatigue and workload) were administered to all 

volunteers at the end of the day’s trial activities. The surveys were intended to provide 

insights into Marines’ perceptions of their own level of fatigue and workload during the 

course of offensive trials.

(FOUO) Overall, males tended to report lower levels of fatigue and workload when 

compared to females. However, the reported fatigue and workload levels of males do 

not appear to change depending on integration of the gun crew. This means that the 

presence of females on the gun crews did not affect males’ perceptions of workload and 

fatigue levels. This is likely a consequence of the individualized duties of each 

cannoneer and the inability to spread load tasks between individuals on a crew. 

9.1.2.9 Artillery Summary

Figure 13 presents a summary of the differences observed when comparing all-male 

gun crews to integrated gun crews. The figure does not illustrate the differences 

observed when comparing the males to females in critical billets. The horizontal bars 

depict the percentage change observed when comparing the average all-male crews 

result to an average integrated crew result. The numerical percentage presented 

adjacent to the bar is indicative of statistical significance. Statistical significance is 

related to the size of the difference, variation, and the number of trials for that task. This 

explains why some larger bars show no significance. 

When a bar shifts to the right of the centerline the all-male group’s average is better 

than the integrated group’s. When a bar shifts to the left the integrated group’s average 

is better than the all-male’s. Most of the horizontal bars are shifted to the right for each 

MOS indicating that all-male groups typically outperform integrated groups.
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Figure 13. Artillery Summary Comparison of Percentage Change of All Tasks

9.1.3 Combat Vehicles

(FOUO) The combat vehicle assessment includes M1A1 Tank Crewmen (MOS 1812), 

Assault Amphibious Crewmen (MOS 1833), and Light-Armored Vehicle Crewmen (MOS 

0313). The combat vehicle assessment was a 3-day scheme of maneuver. Two of the 

three days included live-fire tasks and non-live-fire tasks where crew performance was 

measured. The remaining day included no measured tasks, but was required for 

routine preventive maintenance and repairs to ensure that the unit’s vehicles and 

equipment remained fully operational and to improve the operational realism of the 

experiment. 

(FOUO) The measured tasks for combat vehicles were intended to replicate the tasks 

required to prepare for combat, engage the enemy, conduct casualty evacuations, 

perform field maintenance, and, ultimately, perform follow-on maintenance actions. The 

combat vehicle units participating in the assessment received 1 rest day after 

completing 4 cycles, resulting in an operational tempo of 12 days on and 1 day off. The 

majority of the tasks took place aboard the MCAGCC, Twentynine Palms, CA with 

follow-on tasks for assault amphibious crewmen conducted at Camp Pendleton, CA. 
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(FOUO) The combat vehicle crews all wore a standard vehicle fighting load while 

conducting all tasks. This included a combat vehicle crewman (CVC) protective suit, an 

improved plate carrier (IPC) with small-arms protective insert (SAPI) plates, a Kevlar or 

CVC helmet, and an M4 Carbine. This gear weighed approximately 35 lb. Prior to any 

trial day with observed tasks, the Marines bivouacked at a platoon position on their 

vehicles. 

9.1.3.1 Prepare for Combat

(FOUO) The capability of combat vehicles to respond to a mission depends on the 

ability of the crews to rapidly prepare vehicles for combat operations. Physically 

demanding aspects of preparing vehicles for combat include loading and stowing 

ammunition, readying weapons stations for operation, and securing/unsecuring 

vehicles. Readying a weapon station for operation, although discussed as a 

preparatory task, is also important because it is similar to what would be required to 

troubleshoot and correct a malfunction that occurs while employing the weapon in a 

combat situation.

(FOUO) To prepare vehicles for combat crews must: 

• (FOUO) Tank - Crews must prepare the commander’s M48 .50-caliber machine 

gun (84 lb) and upload a full complement of ammunition onto the vehicle from a 

field ammunition supply point.

9

• (FOUO) LAV - Crews must prepare the M240 coaxially mounted machine gun

(26 lb), the M242 Bushmaster Cannon (263 lb), and load 630 rounds of 25-mm 

ammunition (720 lb) into the vehicle with upload to the feed chutes. 

• (FOUO) AAV - Crews must load and install the M2 .50-caliber machine gun 

(84 lb) and the MK-19 40-mm grenade launcher (78 lb) with ammunition. In 

addition to the weapons, the crews loaded two cans of .50-caliber ammunition 

(35 lb per can) and three cans of 40-mm grenades (45 lb per can) via the 

lowered ramp of the AAV. Loading and installation, depending on the situation, 

can be done externally or internally. When deploying from naval shipping, the 

crews also secure and unsecure vehicles in preparation for amphibious 

operations.

(FOUO) Preparing the Tank Commander’s M48 weapon and the LAV M240/M242 were 

tasks performed almost exclusively by individuals vice the entire crew. Due to the 

individual nature of these tasks, gender of the Marine in the critical billet was used for 

comparison instead of crew integration level. There was no significant difference 

between male and female tank crewmembers when preparing the M48, but male LAV 

 

9 The tank ammunition resupply was not evaluated (see deviations in Annex I) due to substantial 

participation by non-volunteer Marines.
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crewmembers performed M240 and M242 preparatory tasks significantly faster than 

female crewmembers. Loading and stowing ammunition, including upload into feed 

chutes, in the LAVs was a crew-level task that showed no differences when comparing 

integrated crews with all-male crews.

(FOUO) In the AAVs, mounting weapons and loading ammunition was combined into an 

overarching task performed by the entire crew. In this task, all-male crews were 

significantly faster at external loading of weapons and ammunition compared with

integrated crews. All-male crews were also faster at internal loading of the M2 .50 

caliber machine gun when compared to high-density integrated crews, but not when 

compared to low-density integrated crews. 

(FOUO) The AAV crews also had to perform secure/unsecure tasks as part of preparing 

for combat, as would be required when deploying from naval shipping. In the conduct of 

this task, the crews had to move eight sets of chains and dogging brackets from its

stowage area and secure the AAV to the deck of a naval vessel. Upon arrival at the

objective, the crews reversed the process by unsecuring the AAV and returning the 

chains to their appropriate stowage areas. 

(FOUO) There were no significant differences in securing and unsecuring when 

comparing all-male crews with integrated crews. 

9.1.3.2 Engage Enemy Targets

(FOUO) Combat vehicle crews must be capable of acquiring and engaging targets in 

both offensive and defensive engagements under operational conditions and 

environments. To assess crews’ ability to engage enemy targets, gunnery qualification 

tests were adapted for the assessment and included offensive and defensive 

engagements. The engagements included reloading, manual manipulation in the event 

of malfunction, and remedial actions necessary to keep the weapon stations in 

operations.

9.1.3.2.1 Tank Engagements

9.1.3.2.1.1 Load and Arm Main Gun

(FOUO) Tank crews engaged a series of main gun targets and machine gun targets

from a defensive fighting position. Crews also engaged gun targets while in the offense, 

similar to the defense, except that the tank was maneuvering downrange while 

engaging the targets rather than engaging targets from a stationary defensive fighting 

position. 

(FOUO) With the exception of the loader’s M240, accuracy of engagements was not the 

focus. The focus for the assessment was on driver and loader, the more physically 

demanding positions. 
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(FOUO) The loader has a vital role in the lethality and survivability of the tank. During 

main gun engagements, the loader must remove a round weighing 52.8 lb from a 

stowage compartment approximately 3 to 5 feet off the ground. Then the loader must 

flip over the round and load it into the breach while balancing inside a stationary or 

moving vehicle. Because the tank is manually reloaded, the rate of fire is limited by the 

speed at which the loader can manually reload the main gun. In a static environment, 

prior to entering the live-fire range, male and female loaders performed the task of 

loading and arming the main gun. This was done as an individual effort for comparison 

because no assistance from other crewmembers is possible inside the tank. 

(FOUO) In the static environment, female loaders were significantly slower than their 

male counterparts. The average time for males (6.45 seconds) was within the 

prescribed standard of 7 seconds, but the average time for females (7.45 seconds) was 

not, by a fraction of a second. 

(FOUO) To take a more operational view of loading and arming the main gun, this 

reloading task was measured on the live-fire range in both offensive and defensive 

engagements. To minimize the rest time for the loader between reloads under 

strenuous operational conditions, targets were chosen at close ranges and azimuths 

that facilitated quick acquisition and engagement of subsequent targets. Because 

vehicle movements play a role in engagements, the task was examined by crew 

integration level and the gender of the loader. 

(FOUO) Regardless of offensive or defensive engagements, all-male crews and male 

loaders were significantly faster than their integrated crews, and female loaders 

performed similarly to what was observed in the static environment.

9.1.3.2.1.2 Manual Turret Engagement

(FOUO) The turret and main gun of the M1A1 are primarily operated by electric and 

hydraulic systems. As a backup, they can be manipulated manually using crank 

handles located in the gunner’s station. These backups provide a way for the crew to 

continue the fight in the event of a hydraulic or electrical malfunction. This task required 

a single crewmember to manually traverse and elevate the turret.

(FOUO) Male crewmembers performed this task significantly faster than female 

crewmembers.

9.1.3.2.1.3 Ammunition Transfer

(FOUO) When the ready ammunition stowage compartment is low on ammunition, the 

loader transfers ammunition into it from the semi-ready ammunition stowage 

compartment. The loader is required to transfer 16 rounds, each weighing 52.8 lb from 

the semi-ready ammunition stowage compartment to the ready ammunition stowage 

compartment. Transfer, like reloading, is an individual task. 
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(FOUO) In this task, male loaders performed the task significantly faster than female 

loaders.

9.1.3.2.1.4 Employing Loader’s M240

(FOUO) The loader’s weapons system was an M240 medium machine gun pintlemounted adjacent to the loader’s hatch. 

(FOUO) The loader’s M240 is primarily used for close defense of the tank. This task 

required the loader to engage a group of four man-sized targets at a range of 250 

meters, pausing to reload the weapon during the engagement. The targets were set to 

continuously reappear so that the loader would run out of ammunition and be forced to 

conduct the reloading portion of the task. 

(FOUO) Employing secondary weapons and reloading were individual tasks where male 

crewmembers were compared to female crewmembers. Male crewmembers took 

significantly less time to get first hits on target, and got significantly more total hits on 

target; however, female crewmembers were able to reload the M240 significantly faster 

than male crewmembers. The loader’s M240 on a M1A1 takes a great deal of physical 

strength to employ accurately. Unlike the common M240B variant, the loader’s M240 

has dual-spade grips and a butterfly trigger instead of a buttstock and pistol grip. It is 

also pintle-mounted on a skate ring and has no bipods for support. While these 

modifications greatly increase the quick maneuverability of the weapon and enable the 

loader to cover a 180-degree sector of fire, they also necessitate the application of a 

significant amount of force to keep the weapon on target while firing. 

9.1.3.2.1.5 Reloading Commander’s Weapon Station

(FOUO) The Commander’s weapon system is the M48 heavy machine gun that can be 

operated inside the tank, but must be reloaded from an exposed position outside the 

tank armor. Stationary tank engagements with the heavy machine gun forced a reload 

of the Commander’s M48 heavy machine gun during live fire. 

(FOUO) Male crewmembers reloading the commander’s M48 were not significantly 

faster than their female crewmembers. 

9.1.3.2.2 AAVs

9.1.3.2.2.1 Offensive and Defensive Engagements

(FOUO) The AAV crews engaged multiple targets ranging from 400 to 1500 meters 

from multiple defensive and offensive positions. Employing both weapons systems in 

an AAV turret is a physically strenuous task for the Turret Gunner, especially in the case 

when immediate or remedial action is required. Although the other crew members are 

not directly involved in the employment of the Up-Gunned Weapons Station (UGWS), 

the driver’s performance spotting targets and maneuvering the vehicle to allow the turret 
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gunner to safely engage those targets can have a significant effect on the Turret 

Gunner’s ability to identify and engage targets. 

(FOUO) The potential interdependency of driver and turret gunner necessitates an 

examination by integration level, first by comparing integrated crews with all-male 

crews. Integrated crews showed no significant difference in offensive or defensive 

effects when compared to all-male crews. A second examination was done using the 

gender of the turret gunner as the comparative factor. In both offensive and defensive 

engagements, male turret gunners performed significantly better than female turret 

gunners. Experience with the weapon station may have played a causal role in the 

disparity, as could the interdependency between the driver and turret gunner. 

9.1.3.2.2.2 Interior and Exterior Reloads

(FOUO) In combat operations, faster reload times (even measured in fractions of a 

second) are highly desirable. Faster reloading increases the combat effectiveness and 

survivability of an AAV crew. Interior and exterior reloads require the AAV Turret 

Gunner and Rear Crewman to conduct a reload of 200 rounds of .50-caliber ammunition 

and 64 to 96 rounds of 40-mm grenade rounds. A loaded can of .50-caliber ammunition 

weighs approximately 35 lb and a loaded can of 40-mm grenade rounds weighs 

approximately 45 lb. 

(FOUO) For interior reloads, the Rear Crewman assisted the Turret Gunner by moving 

boxes of ammunition from the appropriate troop-compartment stowage spaces and 

handing them to the Turret Gunner, who sat in the vehicle turret. Interior reloads were 

performed twice during an engagement. 

(FOUO) Interior reloads showed no significant differences when comparing all-male to 

integrated groups, with the exception of all-males, who were faster than high-density 

integrated crews on the second interior reload. A gender comparison was done based 

on the gender of the crewmembers occupying the turret gunner and rear crewman 

positions leading based on the combinations in Table 2. 

Table 2. Gender Combinations by Billet for Analysis

Critical 

Billet 

Combination

Rear 

Crewman 

Gender

Turret 

Gunner 

Gender

MM Male Male

MF Male Female

FM Female Male

FF Female Female
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(FOUO) When examining the critical billet holders for interior reloads, there was no 

significant difference in reload times, even when comparing the all-male combination to 

the all-female combination of critical billet holders.

(FOUO) Exterior reloads showed a much different result than interior reloads. Exterior 

reloads were performed once during an engagement. The Rear Crewman assisted the 

Turret Gunner by moving boxes of ammunition from the appropriate troop-compartment 

stowage spaces to the top of the vehicle and into the turret from the exterior. All-male 

AAV crews were significantly faster at exterior reloads than high-density crews, but not 

low-density crews. Similar to interior reloads, analysis was performed by gender of the 

critical billet holders in the task using the combinations in Table 2. The all-female turret 

gunner/rear crewman combination is significantly slower than the all-male combination. 

In addition, any time a female served as a rear crewman lifting ammunition cans up to 

the turret gunner, there appeared to be a corresponding increase in time when 

compared to other combinations.

9.1.3.2.2.3 Manual Turret Manipulation

(FOUO) Similar to the tank crewmen, the AAV Turret Gunner must be able to manually 

traverse, elevate, and depress the vehicle turret UGWS, using the manual traverse and 

elevation controls within the turret in the event of a loss of electrical power supply. 

Manual manipulation of the turret allows the turret gunner to continue to scan and 

engage targets in the event of degraded system operation.

(FOUO) At the crew level, this task only appears to show significance between all-male 

and high-density integrated crews. This task, however, is an individual task. Examining 

the task by gender reveals that male crewmembers are significantly faster than female 

crewmembers at manual manipulation of the turret. 

9.1.3.2.3 LAVs

9.1.3.2.3.1 Offensive and Defensive Engagements

(FOUO) The LAV crews engaged multiple vehicle and personnel targets using the main 

gun and the coaxially mounted machine gun from both offensive and defensive 

positions. The final engagement was a manual engagement that required the gunner to 

use the manual traverse and elevation controls within the turret to acquire and destroy a 

vehicle target.

(FOUO) All offensive and defensive engagements, with the exception of the manual 

engagement, were evaluated at the crew level. The comparisons were made based on 

their time to engage and kill a target. In both offensive and defensive engagements, 

integrated crews performed similarly to all-male crews with respect to effects on target. 
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(FOUO) The most physically challenging of the engagements was manual engagement. 

Manual engagements were evaluated by time and percent kills. In manual 

engagements, there was no significant difference between male and female gunners on 

either the time, or the percent kills. 

9.1.3.2.3.2 Main Gun Remediation

(FOUO) In the event of a misfire on the main gun, the gunner, with assistance from the 

vehicle commander and driver, must perform remedial actions to get the vehicle back in 

the fight. Remedial action of the main gun requires the crew to download the 

ammunition from the main gun, remove the feeder assembly, ensure that it was 

correctly timed and reinstalled, and upload ammunition. 

(FOUO) The Vehicle Commander and Driver were able to assist in main gun 

remediation, but due to the nature of crew responsibilities and the position of the gun in 

relation to the crewmembers, the Gunner bore most of the physical workload. 

Comparisons were made based on gender of the gunner vice crew integration level. 

Male gunners were significantly faster than female gunners at both disassembly and 

reassembly with the larger difference on reassembly. Reassembly tends to take longer 

than disassembly due to the fact that the gunner must work against gravity to lift in 

place components of the weapon without damage. 

9.1.3.2.3.3 Manual Turret Manipulation

(FOUO) Similar to the tank and AAV crewmen, the LAV Turret Gunner must be able to 

manually traverse, elevate, and depress the vehicle turret, using the manual traverse 

and elevation controls within the turret in the event of a loss of electrical power supply. 

Manual manipulation of the turret allows the turret gunner to continue to scan and 

engage targets in the event of degraded system operation.

(FOUO) Manually traversing the turret is an individual task. Comparisons were made 

by integration level of the crew, which showed all-male groups were faster than 

integrated groups. Given the individual nature of the task, however, the most 

appropriate comparison was by gender of the gunner. When comparing male gunners 

to female gunners, the male gunners were significantly faster at manually traversing and 

elevating/depressing the turret. 

9.1.3.3 Crew and Casualty Evacuations

(FOUO) Personnel casualties should be an expected result of enemy engagements. All 

vehicle crews conducted casualty evacuations. Tanks and LAVs focused on a single 

incapacitated crewmember evacuation from the most difficult position and also 

exercised crew evacuations. AAV crews conducted three different types of 

incapacitated crewmember evacuations, one of them while at sea. 
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(FOUO) Each vehicle platform presents its own set of unique challenges and specific 

operational context, but the one commonality among the vehicles is the casualty 

dummy. Similar to the infantry casualty, the dummy weighed 174 lb, the average weight 

of a Marine. The casualty dummy was anatomically correct with natural joint 

articulation, and was dressed in combat vehicle clothing and equipment similar to the 

Marines bringing the total weight up to 205 lb. 

(FOUO) In each case, at least one or more vehicle crewmembers were responsible for 

removing the casualty from a vehicle station (e.g., gunner’s station). For Tanks and

LAV crews, an additional step was required to move the casualty to a rally point that 

was between 25 and 50 meters from the vehicle. Performing this task quickly enables 

the casualty to receive medical attention as soon as possible. 

9.1.3.3.1 Tanks

9.1.3.3.1.1 Crew Evacuation 

(FOUO) A combat-loaded M1A1 contains several hundred gallons of flammable fuel 

and hydraulic fluid, and several hundred pounds of HE ordinance. In the event of a fire 

or other emergency, the survivability of the crew depends on a quick evacuation of the 

tank. 

(FOUO) The crew evacuation task was performed with all crewmembers starting at 

crew stations with safety guards installed and hatches closed and locked. Upon 

receiving the command to evacuate, the crew exited their stations and moved to a rally 

point behind the vehicle. Opening the crew hatches required lifting a 40- to 65-lb hinged 

door in an upward motion, away from the crewman. All crewmen exited the vehicle 

safely and moved as a crew to the rally point 50 meters away. Marines wore fighting 

loads and carried individual weapons, as would be expected when evacuating a vehicle 

in a tactical environment. No significant difference in times was shown between 

integrated crews compared to all-male crews.

9.1.3.3.1.2 Casualty Evacuation

(FOUO) Onboard the tank, the casualty was staged in the gunner’s station leaving only 

three crewmembers to participate in the evacuation. The gunner’s station within a tank

is the most difficult location from which to evacuate a Marine because of its 

inaccessibility and limited workspace. To perform the casualty evacuation, three 

crewmembers lifted the dummy out the loader’s hatch and onto the roof of the turret, 

and carried the casualty to a rally point 50 meters behind the vehicle. No significant 

difference in times was shown between integrated crews compared to all-male crews.
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9.1.3.3.2 AAVs

9.1.3.3.2.1 Evacuation on Land

(FOUO) The casualty onboard the AAV was staged in the turret for land evacuation 

leaving only two crewmembers to participate in the evacuation. The evacuations on 

land were conducted in two different ways to replicate different tactical scenarios. One 

method was the exterior evacuation and the other was the interior. For the exterior 

evacuation, the casualty was placed in the turret and had to be pulled out and placed on 

top of the vehicle. The interior evacuation also started with the casualty in the turret, 

with subsequent movement to the floor of the troop compartment while still remaining 

inside the vehicle. 

(FOUO) The rear crewman began the turret evacuation with follow-on assistance 

provided by the driver after a 60-second delay that allowed the driver to radio a casualty 

evacuation report. If the crew had not evacuated the casualty after 6 minutes had 

passed, then a third crewman from a separate vehicle provided assistance. 

(FOUO) Exterior casualty evacuations from the turret showed significant differences 

between all-male crews and high-density integrated crews with all-male crews 

performing the task faster than high-density crews, but not low-density crews. 

(FOUO) To investigate further, the gender of the Marines occupying rear crewman and 

driver positions were analyzed. When a female occupied the rear crewman and driver 

positions simultaneously, the performance was significantly slower than when either one 

or both of those positions was occupied by a male. The position of a female in the twoperson combination also explains why at the crew level, low-density integrated crews 

were not significantly different from all-male crews. 

(FOUO) When a male occupied the rear crewman position, the evacuation times were

not significantly faster than all-male crews. However, when a female occupied the rear 

crewman position, the difference was significant. The reason is explained by the fact 

that the rear crewman begins the evacuation without any assistance until the driver 

completes the casualty report. More progress is made in the evacuation when the male 

began the effort than when the female did. 

(FOUO) The results for the interior evacuation are not as telling as the exterior 

evacuation. Interior evacuations showed no significant differences when comparing allmale to integrated crews. When examined by gender of the rear-crewman and driver, 

having a female begin the evacuation again played a role in longer evacuation times, 

but the result is less definitive. One reason for the differing results between exterior and 

interior evacuations relates to with the direction of the evacuation. For exterior 

evacuations, the casualty must be lifted out of the turret, whereas interior evacuations 

require the casualty to be pulled down into the troop compartment. 
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9.1.3.3.2.2 Evacuations on Water

(FOUO) Crew evacuations on water have an added emphasis and complexity. 

Operating on a platform that pitches and rolls with the waves makes the task more 

difficult. If the cause for the evacuation is a sinking vehicle, then time is of critical 

importance to the casualty’s survival chances. For casualty evacuations on water, the 

turret gunner and driver were required to lift the casualty from the floor of the troop 

compartment to the top of the vehicle through the starboard, right cargo hatch. 

(FOUO) Water evacuation results were similar to exterior evacuation results. In water 

evacuations, all-male crews were significantly faster than high-density integrated crews, 

but not significantly faster than low-density crews. 

9.1.3.3.3 LAVs

9.1.3.3.3.1 Crew Evacuation

(FOUO) All crewmen were required to exit the vehicle safely and move as a crew to the 

rally point 25 meters away. Marines wore fighting loads and carried individual weapons, 

as would be expected when evacuating a vehicle in a tactical environment. 

(FOUO) The all-male LAV crews evacuated the vehicle significantly faster than the highdensity integrated crews, but not significantly faster than the low-density integrated 

crews. Operationally, the time difference for this task, taken in isolation, is not 

meaningful. This difference only becomes meaningful when combined with other tasks, 

such as follow-on casualty evacuations. 

9.1.3.3.3.2 Casualty Evacuation

(FOUO) The LAV casualty was placed in the vehicle commander’s station, the most 

difficult position to evacuate, leaving the two remaining crewmen to conduct the 

evacuation. The crewmen evacuated the casualty from the vehicle by extracting it from 

the turret and placing it on the front of the vehicle, then moving the casualty to the rally 

point 25 meters away. If removing the casualty took too long, other vehicle crewman 

from a different vehicle, or vehicle scouts, were pulled from a supplementary position 

and were allowed to assist in the evacuation. 

(FOUO) LAV casualty evacuations from the turret showed significant differences 

between all-male crews and high-density integrated crews, but not low-density crews. 

High-density integrated crews were significantly slower at both extraction and 

movement to the rally point when compared with all-male crews.

9.1.3.4 Field Expedient Maintenance

(FOUO) In a combat environment, a quick recovery of a disabled vehicle denies the 

enemy the opportunity to maneuver or employ fires against a combat vehicle. In the 
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event that a vehicle becomes disabled, crews are equipped and trained to perform 

actions, repairs, and self-recovery to enable missions to continue. 

9.1.3.4.1 Tanks

9.1.3.4.1.1 Vehicle Recovery

(FOUO) In the event that a tank becomes disabled, tank sections are equipped and 

trained to perform self-recovery. Performing tank recovery involves crewmembers from 

each tank dismounting from their vehicles, removing the 300-lb tow bars from the 

stowage position on the operational tank, mounting them on the front of the disabled 

tank, and then holding the tow bars in place approximately 3 feet off the ground while 

the operational tank maneuvers into position to connect the tow bar’s lunette eye to a 

pintle hitch.

(FOUO) All-male crews showed no significant difference in recovery times when 

compared with integrated crews.

9.1.3.4.2 AAVs

9.1.3.4.2.1 Manual Ramp Raise

(FOUO) A malfunction of the AAV ramp can leave a vehicle vulnerable and incapable of 

operations at sea. To correct malfunctions of an AAV ramp, crews are required to 

manually raise the ramp with a ramp jack. 

(FOUO) The all-male AAV crews raised the vehicle ramp significantly faster than the 

high-density integrated crews, but not the low-density integrated crews. The difference 

in time to conduct this task, although statistically significant, is not operationally relevant

because the time difference is small. 

9.1.3.4.2.2 Vehicle Recovery on Water and Land

(FOUO) AAV crews performed water and land recovery of disabled AAVs with like 

vehicles. The crews of the recovery and disabled AAVs worked together for each 

portion of the recoveries. The water recovery required the Turret Gunner and the Rear 

Crewman from each vehicle to throw water-tow ropes to the recovery vehicle or use a 

boat hook to secure the thrown ropes. The crews then connected both vehicles sternto-stern and towed the disabled vehicle in the water.

(FOUO) Once on land, towing required both crews to manipulate the two vehicles and 

the land tow bar, which weighed approximately 150 lb, and attach it to two points on the 

disabled vehicle. The operational vehicle then backed up until the tow pintle seated 

properly. Once the vehicle was attached, both crews loaded into the recovery vehicle 

and the recovery vehicle began to tow. 
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(FOUO) Neither water nor land recovery operations showed any significant differences 

in times when comparing all-male crews to integrated crews.

9.1.3.4.3 LAVs

9.1.3.4.3.1 Rig for Recovery and Tow

(FOUO) LAV crews performed recovery and towing operations with notionally mired and 

disabled LAVs. Rigging for recovery employed an LAV Logistics (LAV-L) variant 

connected via winch cable to a mired LAV-25 variant. The crews maneuvered the 

LAV-L variant 10 meters away, paid out the winch cable, and connected the two 

vehicles with two 75-lb snatch blocks to create a three-point recovery system. 

(FOUO) With the mired vehicle recovered, the crew rigged the disabled vehicle for 

towing using the 175-lb tow bar located on the side of the LAV-L variant. With the two 

vehicles still spaced 10 meters apart, the crewmen detached the tow bar from the 

LAV-L and connected it to the tow points on the LAV-25. The crew ground-guided the 

Logistics variant and, with one crewman holding the tow bar, attached the eye of the 

tow bar to the tow pintle of the LAV-L variant. 

(FOUO) There were no significant differences in the time to rig for recovery or towing 

when comparing all-male crews with integrated crews. 

9.1.3.4.3.2 Remove and Install Tire

(FOUO) The ability to rapidly change a tire has critical implications to ensuring mission 

accomplishment. Depending on the terrain, it would not be unusual for a vehicle crew 

to change multiple tires throughout the course of an operation. 

(FOUO) To perform a tire change, the LAV crew removed the spare tire, which weighed

200 lb, from the side of the vehicle. The crew jacked up the vehicle, removed a vehicle 

tire, mounted the vehicle’s spare tire, and tightened the lug nuts. Finally, the crew 

returned the damaged tire to the side of the vehicle on the spare mounting bracket. 

(FOUO) There were no significant differences in the time to change a tire when 

comparing all-male crews with integrated crews. 

9.1.3.5 Follow-on Maintenance

(FOUO) Vehicle crewmen in the operating forces typically spend a significant 

percentage of available man hours performing routine maintenance. This work is often 

physically demanding because the parts, tools, and equipment that are organic to a 

combat vehicle unit are large and heavy. A proficient and effective vehicle crewman is

capable of performing multiple hours of preventative maintenance or repairs each day. 

This is operationally realistic and an indispensable part of every vehicle crewman’s job.
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9.1.3.5.1 Tanks

(FOUO) The follow-on maintenance task for tank crewmen involved separating the tank 

track, removing and replacing a track section, and reinstalling the track. Maintenance 

tasks similar to this are commonly required to repair damage sustained during 

operations. When a tank sustains damage to its track or suspension during a mission, 

the crew will perform repairs encompassing some or all of the performance steps 

required for this task. In a combat environment, it is critical to perform repairs and 

regain mobility quickly, denying the enemy the opportunity to attack a stationary target.

(FOUO) In this task, all-male crews performed the repairs significantly faster than 

integrated crews.

9.1.3.5.2 AAVs

9.1.3.5.2.1 Break and Reassemble Track

(FOUO) The follow-on maintenance task for AAV crews involved separating the track, 

removing and replacing a track section, and reinstalling the track. Maintenance tasks 

similar to this one are commonly required to repair damage sustained during operations. 

When an AAV sustains damage to its track or suspension during a mission, the crew 

will perform repairs that encompass some or all of the performance steps required for 

this task. In a combat environment, it is critical to perform repairs and regain mobility 

quickly, denying the enemy the opportunity to attack a stationary vehicle target.

(FOUO) Breaking and reassembling track showed significant differences between allmale crews and high-density integrated crews, but not low-density crews. To 

investigate further, the gender of the Marines occupying the rear crewman and turret 

gunner positions was examined. When a female occupied the rear crewman and turret 

gunner positions, simultaneously, the performance was significantly slower than when 

both positions were occupied by males. 

9.1.3.5.3 LAVs

9.1.3.5.3.1 Remove and Replace Armor Panels

(FOUO) Removing armor panels, while not conducted as regularly as other 

maintenance actions, is required should the panels be damaged in combat operations, 

or during wash-downs and cleaning after extended operations. The armor panels are 

composite-armor, mounted on the back and side of the vehicle. The two side-armor 

panels weigh 60 lb each and the two rear scout-hatch armor panels weigh 125 lb each. 

(FOUO) Removing and replacing the lighter front armor panels showed no significant 

differences between all-male and integrated groups, but as the panel weight increased, 

so did the differences. The removal and replacement of the heavier scout-hatch panels 
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took significantly longer with high-density integrated crews when compared with all-male 

crews, but not when compared with low-density crews. 

9.1.3.6 Combat Vehicles Fatigue and Workload

(FOUO) Two self-report surveys (fatigue and workload) were administered twice to all 

volunteers. The first administration occurred at the conclusion of the tasks on non-livefire days, which included crew and casualty evacuation, field expedient maintenance, 

and follow-on maintenance activities. The second administration was after the 

conclusion of live-fire tasks, which included preparing for combat and engaging enemy 

targets. The surveys were intended to provide insights into Marines’ perceptions of their 

own level of fatigue and workload level during the course of offensive trials.

9.1.3.6.1.1 Non-Live-Fire Fatigue and Workload

(FOUO) Overall, males and females reported similar fatigue and workload levels across 

all three combat vehicle platforms with one exception: male tank crewmen. Male tank 

crewmen reported lower workload results than female tank crewmen. 

(FOUO) The reported fatigue and workload levels of males do not appear to change 

depending on integration of the crew with the exception of male LAV crewmen. Male 

LAV crewmen report higher fatigue and workload levels when part of integrated crews. 

Non-live-fire days included maintenance tasks conducted by the entire crew, which 

allowed for more opportunities for compensation to occur. 

9.1.3.6.1.2 Live-Fire Fatigue and Workload

(FOUO) On live-fire days, the fatigue and workload results are mixed. Male LAV 

crewmen reported lower levels of fatigue than female LAV crewmen, but the same 

cannot be said for Tank and AAV crewmen; male and female Tank and AAV crewmen 

reported similar fatigue levels on live-fire days. The reverse is true for workload. On 

live-fire days, male and female LAV crewmen reported similar workload levels while 

male Tank and AAV crewmen reported lower workloads than their female counterparts.

(FOUO) The reported fatigue and workload levels of males do not appear to change 

depending upon integration of the crew, with the exception of male tank crewmen. Male 

tank crewmen reported higher workloads when in integrated crews compared to when 

they were in all-male crews. There were a small minority of extreme male survey 

responses that impact this answer. When adjusting for a few extreme observations, the 

results change to being similar between all-male and integrated. 

9.1.3.7 Combat Vehicles Summary

Figure 14 presents a summary of the differences observed when comparing all-male 

gun crews to integrated gun crews. The figure does not illustrate the differences 

observed when comparing the males to females in critical billets. The horizontal bars 
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depict the percentage change observed when comparing the average all-male crews

result to an average integrated crew result. The numerical percentage presented 

adjacent to the bar is indicative of statistical significance. Statistical significance is 

related to the size of the difference, variation, and the number of trials for that task. This 

explains why some larger bars show no significance. 

When a bar shifts to the right of the centerline the all-male group’s average is better 

than the integrated group’s. When a bar shifts to the left the integrated group’s average 

is better than the all-male’s. Most of the horizontal bars are shifted to the right for each 

MOS indicating that all-male groups typically outperform integrated groups.

Figure 14. Combat Vehicles Summary Comparison of Percentage Change of All Tasks
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9.2 Objective 2 

9.2.1 Provisional (Infantry and Machine Guns) 

(FOUO) The provisional infantry assessment was a 2-day scheme of maneuver 

intended to replicate offensive and defensive tasks. The provisional infantry 

assessment included Provisional Infantry (PI) Riflemen and Provisional Machine 

Gunners (PIMG) who could be sourced from any MOS except 03XX, 08XX, or 18XX

family of MOSs. All Marines, regardless of task, wore the fighting load (35 lb) and 

carried a personal weapon (6.4 lb, 7.9 lb, or 10.5 lb, depending upon weapon type).

9.2.1.1 SOM Overview

9.2.1.2 Trial Cycle Day One

(FOUO) The first day of the infantry assessment was a coordinated, live-fire squad 

attack employing the rifle and machine gun squads. The coordinated attack allowed for 

simultaneous employment of the squads in close proximity on the same range for 

operational realism, but with offsets in battlespace geometries of fire to allow for 

independent observation and measurement of mission effects, fatigue, and workload. 

(FOUO) In general terms, the coordinated attack began with an initial movement, 

followed by an enemy engagement, consolidation on the objective, and, finally, a 

casualty evacuation. 

(FOUO) Day one was a fluid scenario that allowed the Marines to flow from beginning to 

end without interruption or breaks. Figure 15 illustrates infantry live-fire attack. At the 

conclusion of the casualty evacuation, the Marines operated under the guidance of their 

Company leadership, performing tasks that required minimal physical demands, and 

then bivouacking in the field, sleeping in 2-man tents.
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Figure 15. Provisional Infantry and Machine Guns Day-One Scheme of Maneuver

9.2.1.2.1 Initial Movement

(FOUO) The assault began from an assembly area with a rapid movement to assault 

position. The initial movement was approximately 1 km to the support-by-fire position 

(PIMG) and assault position (PI). Each squad moved this distance as quickly as 

possible while carrying an assault load (30 lb). In addition to the assault load, the 

following additional equipment was carried by PIMG squads:

• (FOUO) PIMG: The M240B machine gun, tripod, spare barrel, and ammunition 

(600 rounds of 7.62 mm) divided among the three members of the squad

(additional 28 – 40 lb per person). 
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(FOUO) The all-male squads, regardless of PI or PIMG, were significantly faster than 

the integrated squads. The impact of additional carried weight was not as pronounced 

in PIMG over this initial movement like it was in the 0331 squads. The disparity grows 

with distance in the approach march. 

9.2.1.2.2 Negotiate Obstacles

(FOUO) Upon arrival at the assault position, the PI squad was required to negotiate an 

8-ft wall by getting all Marines and equipment over as quickly as possible. The squad 

was allowed to negotiate the obstacle any way possible so long as they maintained the 

appropriate tactical posture. 

(FOUO) When comparing low-density integrated PI squads to all-male PI squads, we 

saw no significant differences in time. The high-density integrated squads were 

significantly slower than both the low-density integrated and all-male PI squads. 

(FOUO) On this particular task, the results of PI squads should not be compared with 

0311 squads. The PI squads were faster, but their speed was a function of technique, 

not strength. The PI squads sent all three fireteams over the obstacle simultaneously, 

as opposed to the 0311 squads, which went one at a time. In short, the PI squad’s 

technique made them faster than the 0311s, but in the process, the PI squads sacrificed 

security. This made any comparisons of time problematic. 

9.2.1.2.3 Fire and Movement

(FOUO) While the PI squad was negotiating the wall obstacle, the PIMG squad was 

occupying a support-by-fire position to suppress enemy targets and prepare the 

battlefield for the PI squad. 

9.2.1.2.3.1 Suppressive Fire – Provisional Machine Gun Squad

(FOUO) Following close in timing to the PI squad on the left flank was the PIMG

machine gun squad. The machine gun section occupied a position of overwatch and 

provided support-by-fire for the rifle squad. From the support-by-fire position, the 

machine gun squad had to rapidly get their gun into action, acquire targets, and 

accurately engage the enemy. 

(FOUO) The movement and emplacement of the machine gun took significantly longer 

with both low- and high-integrated groups when compared to all-male groups. When 

the two tasks were broken out separately, the difference in time can be traced to the 

100-meter hasty movement from the assault position to the support-by-fire position. 

Once at the support-by-fire position, there was no significant difference in the time to 

emplace the machine gun or effects on target (i.e., hits) when comparing integrated to 

all-male PIMG squads. 
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9.2.1.2.3.2 Provisional Infantry Rifle Squad Attack and Counterattack

(FOUO) The mission of the rifle squad is “to locate, close-with, and destroy the enemy 

by fire and maneuver, and repel the enemy’s assault by fire and close combat.” Having 

negotiated the 8-ft wall obstacle, the PI rifle squad deployed into an on-line formation to 

maximize firepower in the direction of the enemy and then moved with weapons at the 

ready, expecting imminent contact. 

(FOUO) Upon contact with the enemy (targets being presented), the Marines 

established a heavy volume of fire to gain fire superiority. They then began buddy 

rushes to close with the enemy objective. Each squad conducted approximately 300 

meters of buddy rushes, engaging a total of 12 targets with direct-fire weapons and 

three machine gun bunkers with the M16A4 with M203 grenade launcher attachment. 

(FOUO) After all targets were destroyed (no targets remaining), the squad moved 

another 125 meters to a limit of advance and prepared for an enemy counterattack. 

(FOUO) At the conclusion of every assault, the attacking unit must be prepared for the 

enemy to regroup and organize a counterattack. Upon consolidation at the limit of 

advance, the squad oriented its weapons in the direction of the enemy’s retreat. Upon

target presentation, the counterattack commenced for 90 seconds. 

(FOUO) The principle measurement of the squad’s ability to destroy the enemy by fire 

during the attack and counterattack is hits on target. When comparing integrated PI

squads to all-male squads, the integrated PI squads had similar results for probability of 

hit. 

(FOUO) The squad attack involved all 12 Marines engaging targets. Each Marine can, 

and often does, engage some of the same targets because of overlapping sectors of 

fire. To uncover whether or not a gender effect exists in accuracy at the individual level, 

individual shots recorded by targets were correlated back to shooters. This enabled an 

investigation of gender differences by weapon system (i.e., M4, M27, and 

M16A4/M203). 

(FOUO) The shot accuracy by gender and by weapon reveals that there is a significant 

difference between genders for the M4 and M16A4/M203 weapon systems within the PI

squads for the probability of hit and the probability of hit/near miss10. Figure 16 and 

Figure 17 depict accuracy results for males versus females by weapon type. The 

overall accuracy declined and the percent difference increased as the weight of the 

weapon system increased. The M4 was the lightest weapon and yielded the most 

 

10 Hits are shots that impact the E-silhouette target. Near misses are shots that are detected within 1-

meter of the outside edge of the E-silhouette target, which may have some suppressive effect on the 

enemy.
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accurate results, while the M16A4/M203 was the heaviest weapon and yielded the least 

accurate results. 

Figure 16. Accuracy Comparison by Gender and Weapon Type for Hits

Figure 17. Accuracy Comparison by Gender and 

Weapon Type for Hits and Near Misses
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9.2.1.2.4 Movement to Limit of Advance

(FOUO) The ability to close with the objective after conducting a live-fire attack is crucial 

to maintaining momentum during offensive operations. At the conclusion of the live-fire 

attack, the PI squad moved 125 meters to a limit of advance. The PIMG squads also 

conducted a displacement to a limit of advance, but the distance was 300 meters. The 

low-density integrated PI and all-male PI squads’ performance was similar in the 

movement to the limit of advance. The high-density integrated PI and integrated PIMG

squads took significantly longer to complete their movement to the limit of advance than 

their all-male counterparts. The late arrival reduced the time to prepare for, or respond 

to, the counterattack launched by an enemy force.

9.2.1.2.5 Casualty Evacuation

(FOUO) Casualties are an inevitable part of conducting combat operations. Units train 

to become proficient in the triage, handling, and transport of a casualty. After a Marine 

is injured, it is essential to move the casualty to the appropriate level of care as quickly 

as possible. Each PIMG squad was assigned one casualty to evacuate upon 

conclusion of the live-fire attack and counterattack. PI rifle squads had 12 Marines in a 

squad as compared to 3 for the PIMG squads. Because the rifle squads had 4 times 

the number of Marines, each PI rifle squad had 3 casualties to evacuate (i.e., one 

casualty for every 3 to 4 Marines).

(FOUO) The casualty was a dummy11 wearing combat equipment that had to be moved 

a distance of 100 meters to a casualty collection point along with the weapons and gear 

of the Marines performing the transport. The Marines could use a variety of techniques 

for transport, but had to carry the dummy off the ground (not drag any part) and could 

not drop the casualty. 

(FOUO) The all-male PI fireteams and PIMG squads were significantly faster than their 

comparable integrated fireteams and squads. Figure 18 shows the differences 

observed in casualty evacuations.

 

11 The dummy was a full-scale anthropomorphic test device that simulates the dimensions, weight 

proportions and articulations of the human body. The dummy’s weight was equivalent to an average 

Marine (174 lb). When combat equipment (Marine Corps Combat Utility Uniform, boots, Kevlar helmet, 

plate carrier vest with small arms protective insert plates, and M16A4) was added to the dummy the total 

weight increased to 220 lb. 
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Figure 18. Differences in Integrated Casualty Evacuation 

Times Compared to All-male Times

9.2.1.2.6 PI and PIMG Day One Fatigue and Workload

9.2.1.2.6.1 Comparing Male Responses to Female Responses

(FOUO) Two self-report surveys (fatigue and workload) were administered to all 

volunteers at the end of trial activities on day one. The surveys were intended to 

provide insights into Marines’ perceptions of their own level of fatigue and workload 

during the course of offensive trials. 

(FOUO) Overall, males tended to report lower levels of fatigue and workload when 

compared with females in the PI and PIMG squads. 

9.2.1.2.6.2 Comparing Male Responses in Integrated Squads to All-male Squads

(FOUO) In addition to looking at how fatigue and workload self-reports compared 

between males and females, we also examined whether males responses remained 

consistent at different integration levels. This comparison was omitted for PIMG squads 

because of insufficient data for valid comparisons. 

(FOUO) The reported fatigue and workload levels of males do not appear to change 

depending on integration of the squad. 

9.2.1.3 Trial Cycle Day Two

(FOUO) The second day of the provisional infantry and provisional machine gun 

assessment was focused on an approach march for all squads, defensive actions of the 

rifle squad, and heavy weapons employment of the machine gun squads, as shown in 

Figure 19. At the conclusion of the defense and weapons employment, the Marines 

operated under the guidance of their Company leadership, performing tasks that 

required minimal physical demand and then bivouacking in the field, sleeping in 2-man 

tents. 
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Figure 19. Provisional Infantry and Provisional Machine Guns Day-Two Scheme of Maneuver

9.2.1.3.1 Approach March

(FOUO) The beginning of day two started with a march carrying the approach load

(55 lb)12. Moving under a load is one of the most fundamental tasks of an infantry unit; 

it is both physically and mentally demanding. Units train by conducting tactical marches 

with an approach load at increasing distances. The Infantry Training &Readiness

Manual states: “the approach march load will be such that the average infantry Marine 

will be able to conduct a 20 mile hike in 8 hours with the reasonable expectation of 

maintaining 90% combat effectiveness.” Each squad moved a distance of 7.20 km

while carrying the approach load and personal weapons. In addition to the approach 

load, the following additional equipment was carried by PIMG squads:

• (FOUO) PIMGs: The M240B machine gun, tripod, spare barrel, and ammunition 

(4 cans of 7.62 mm) divided among the three members of the squad (additional 

28 – 40 lb per person). 

 

12 The approach load is in addition to the fighting load (35 lb) and personal weapon (6.4 lb, 7.9 lb, or 10.5 lb 

depending upon weapon type assigned).
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(FOUO) The all-male PI and PIMG squads were significantly faster than the integrated 

squads. The differences observed between all-male and integrated squads are more 

pronounced in non-0311 squads, which corresponds to an increase in carried weight of 

crew-served weapons and ammunition carried in addition to the approach load. Figure 

20 shows the percent increase in average times when comparing integrated groups to 

the all-male groups.

Figure 20. Percent Increase in Approach March Times

for Integrated Squads Compared to All-male Squads. 

(FOUO) The differences illustrated in Figure 20 follow the same pattern observed in the 

approach march for 03XX squads. The march with approach load has an applicable 

standard that can be used to provide a second frame of reference. Similar to the 03XX 

squads, the movement over 20 miles in 8 hours equates to a pace of 4 kilometers per 

hour (km/h). This standard is applicable to PI and PIMG squads because Marines from 

non-03XX MOSs assigned to Infantry units are required to keep pace with the 03XX 

Marines. 

(FOUO) Figure 21 shows a conversion of the average squad times over the 7.2-km 

distance to pace. This conversion enables a comparison to the 4-km/h required to meet 

the standard. As shown in the figure, the integrated PI squads and both all-male 

squads achieved the standard; the integrated PIMG squads were not able to meet the 

standard. Figure 21 also illustrates the same corresponding decrease in pace as weight 

of the carried load increases that was seen in the 03XX Marines. 

10%

10%

25%

PI

PMG

Percent Increase in Time

MOS

High-density compared to All-male

Low-density compared to All-male

All results are statistically

significant
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Figure 21. Conversion from Average Elapsed Time for the 7.2 km 

March to Pace for the Provisional’s Approach March 

9.2.1.3.2 Heavy Weapons Employment

(FOUO) Upon completion of the approach march and after a brief rest period, the 

infantry moved into the defense. The PI Marines moved into the preparation of 

defensive fighting positions while the PIMG Marines moved into heavy weapons 

employment.

9.2.1.3.2.1 PI Fireteams Preparing Defensive Fighting Positions

(FOUO) Protection is vital to infantry units, especially in a defensive posture. Infantry 

units commonly construct fighting positions to conceal positions and minimize exposure 

to enemy fire. There are many characteristics to constructing a doctrinal fighting 

position, but the most physically demanding aspect is digging out the fighting hole. The 

terrain where the fighting holes were dug consisted of hard, compact sand and rocks.

Each PI fireteam dug two 2-man fighting holes in a time limit of 2 hours, maintaining 

50% security, meaning two Marines dug while two provided security in the prone 

position. The Marines swapped positions every 15 minutes. During the course of this 

task, the earth was scooped into buckets and weighed. 

(FOUO) The integrated PI fireteams average weight of earth moved was not 

significantly different than all-male groups. 

9.2.1.3.2.2 PIMG Squad Employment of M2 Machine Gun 

(FOUO) Providing defensive fires with the M2 heavy machine gun entails moving the

system to a position of advantage, engaging the enemy, and conducting a rapid 

displacement. After completing the approach march, the PIMG squads dismounted the 
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M2 heavy machine gun from a vehicle platform, moved and emplaced the weapon, 

engaged targets, displaced, and mounted the weapon onto a vehicle platform. 

(FOUO) To dismount the weapon system, the squad worked to manually disassemble 

and lower each component to the ground from a HMMWV. To mount the weapon 

system on the HMMWV, the process was reversed. This task determined the time for a 

squad of three Marines to fully dismount and mount the M2 from a tactical vehicle and 

required the strength to lift, manipulate, and lower heavy components. 

(FOUO) The integrated PIMG squads’ average time was significantly faster than allmale squads’ times for the aggregate mounting and dismounting of the M2 heavy 

machine gun. When broken down into individual tasks, the all-male group took 

significantly longer to mount the M2. The time to dismount for both types of squads was 

the same.

(FOUO) During the assessment, each machine gun squad emplaced the M2 on a tripod 

at a specified firing location. The squad engaged targets as they began to be exposed 

while hits on, and around, the target were recorded by sensors. The assessment began 

with targets exposed and engaged by the squad. 

(FOUO) The integrated PIMG squads had significantly more hits on target than the allmale squads. Figure 10 (see page 25) shows the percentage of hits and near misses13

on the machine gun targets. The finding that integrated groups have a higher 

percentage of hits on target is somewhat unusual given the findings from PI and 0311

hit percentages. To see if there is a consistent finding, the results of provisional 

machine gunners were compared to the 0331 squads. As shown in Figure 10, the trend 

of integrated groups outperforming all-male groups is repeated and consistent. 

(FOUO) After an engagement, a machine gun squad must be able to breakdown their 

weapon system and move to a position of cover as rapidly as possible. Immediately 

after completing target engagement, the PIMG squad took the gun out of action and 

displaced 100 meters from the firing line to a designated location, moved a heavy load a 

short distance, and manipulated a weapon while fatigued. 

(FOUO) The integrated PIMG squads took significantly longer to displace from the firing 

line compared with all-male squads.

 

13 For experimental purposes a hit or near miss for a machine gun target is defined as any detectable 

round within a 3-meter radius from the center of the target.
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9.2.1.3.3 PI and PIMG Day Two Fatigue and Workload

9.2.1.3.3.1 Comparing Male Responses to Female Responses

(FOUO) Two self-report surveys (fatigue and workload) were administered to all 

volunteers at the end of trial activities on day two. The surveys were intended to 

provide insights into Marines’ perceptions of their own level of fatigue and workload 

level during the course of defensive trials. 

(FOUO) Overall males tended to report lower levels of fatigue and workload when 

compared to females in the PI and PIMG squads. 

9.2.1.3.3.2 Comparing Male Responses in Integrated Squads to All-male Squads

(FOUO) In addition to looking at how fatigue and workload self-reports compared 

between males and females, we also examined whether male responses remained 

consistent at different integration levels. This comparison was omitted for PIMG squads 

because of insufficient data for valid comparisons. 

(FOUO) PI males report lower levels of fatigue and workload in high-density integrated 

groups when compared with all-male and low-density integrated groups. This finding is 

consistent with the 03XX results, where integrated squads, especially high-density 

squads, moved at a slower (easier) pace on the 7-km approach march, resulting in 

lower workloads on males in those squads. 

9.2.2 Engineers

(FOUO) The combat engineer assessment was a 2-day scheme of maneuver intended 

to replicate offensive and defensive tasks. All Marines, regardless of task, wore the 

fighting load (35 lb) and carried a personal weapon (6.4 lb, 7.9 lb, or 10.5 lb, depending 

upon weapon type).

9.2.2.1 Trial Cycle Day One

(FOUO) The first day of the combat engineer assessment was a breaching mission in 

support of an infantry squad attack followed immediately by a demolitions raid. The 

ability for an infantry unit to quickly overcome unexpected or lightly defended obstacles 

to maintain the momentum of the attack is critical to mission success. The reinforced 

infantry squad was supported by two engineer fireteams, each responsible for 

conducting a hasty breach using Bangalore torpedoes to overcome a concertina wire 

obstacle once the advancing infantry squad halted. 

(FOUO) At the conclusion of the squad attack and successful breach, the two combat 

engineer fireteams formed an engineer squad and moved to a likely avenue of enemy 

approach to conduct a demolitions raid and emplace a countermobility obstacle to 

further disrupt an enemy’s mobility and prevent the loss of recently acquired terrain. 
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(FOUO) Day one was a fluid scenario that allowed the Marines to flow from beginning to 

end without interruption or breaks. Figure 22 is an illustration of the combat engineer 

attack. At the conclusion of the demolitions raid, the Marines operated under the 

guidance of their platoon leadership, performing tasks that required minimal physical

demand and then bivouacking in the field, sleeping in 2-man tents. 

9.2.2.1.1 Initial Movement

(FOUO) The employment of forces on the battlefield requires maneuver in combination 

with fire, or fire potential, to achieve a position of advantage in respect to the enemy in 

Figure 22. Combat Engineers Day-One Scheme of Maneuver
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order to accomplish the mission. During the experiment, the first combat engineer task 

was a foot-movement following in trace of an infantry squad for a distance of 

approximately 1 km to an assault position. Each fireteam moved this distance as 

quickly as possible while carrying an assault load (20 lb). In addition to the assault load, 

every individual Marine carried either two or three Bangalore components, weighting 

15 lb each, depending on their individual billet. 

(FOUO) The all-male fireteams were significantly faster than the integrated fireteams.

9.2.2.1.2 Negotiate Obstacles

(FOUO) Upon arrival at the assault position, the combat engineer Marines were 

required to negotiate an 8-ft wall by getting all Marines and equipment over as quickly 

as possible. The fireteams were allowed to negotiate the obstacle any way they could, 

as long as they maintained the appropriate tactical posture. 

(FOUO) The all-male fireteams were significantly faster than the integrated fireteams.

9.2.2.1.3 Breaching

(FOUO) After negotiating the obstacle, the engineer fireteams conducted a 450-meter

movement in trace of the infantry squad to the Limit of Advance. Upon arrival at the 

Limit of Advance, the fireteams held in place until the infantry squad completed the 

attack. 

(FOUO) At the conclusion of the infantry squad’s live-fire attack and casualty 

evacuation, the combat engineer fireteams conducted a hasty breach using Bangalore

torpedoes to breach a concertina-wire obstacle out in front of the halted infantry squad. 

Once the fireteam had all 10 Bangalore sections connected, the explosives were dually 

primed and the engineers initiated the breach via Modern Demolition Initiators (MDI). 

Breaching operations enables forces to neutralize, reduce, or overcome 

obstacles/impediments as soon as possible to allow unrestricted movement and 

maintain the initiative. The all-male fireteams were significantly faster than the 

integrated fireteams.

9.2.2.1.4 Mobility Denial

(FOUO) The most obvious way to seize and maintain the initiative is to strike first and 

keep striking. Once ground is taken, it requires continuous action to hold and maintain. 

Engineers apply this fundamental tactic by denying the enemy’s ability to influence 

mobility. This is accomplished by being proactive and, often, by conducting 

countermobility missions to deny the enemy advancing momentum and by providing 

protection to friendly maneuvering forces. Upon conclusion of the attack, the combat 

engineers conducted a demolitions raid by moving a 2.4-km distance to a likely avenue 
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of approach with 40-lb shape and 40-lb crater charges to conduct mobility denial 

operations. 

(FOUO) There was no significant difference in the movement under load between the 

all-male squads and the low-integration groups; however, once the squad was formed 

as a higher-integration squad, the movement times were significantly slower.

9.2.2.1.5 Fatigue and Workload

9.2.2.1.5.1 Comparing Male Responses to Female Responses

(FOUO) Two self-report surveys (fatigue and workload) were administered to all 

volunteers at the end of trial activities on day one. The surveys were intended to 

provide insights into Marines’ perceptions of their own levels of fatigue and workload 

during the course of offensive trials. 

(FOUO) Overall, male engineers tended to report fatigue levels that were similar to 

fatigue levels reported by female engineers, but male engineers reported lower 

workload levels than female engineers. 

9.2.2.1.5.2 Comparing Male Responses in Integrated Squads to All-male Squads

(FOUO) In addition to looking at how fatigue and workload self-reports compared 

between males and females, we also examined whether male responses remained 

consistent at different integration levels. 

(FOUO) No differences were seen in the reported fatigue and workload levels of males 

depending on integration of the squad.

9.2.2.2 Trial Cycle Day Two

(FOUO) The second day of the combat engineer assessment focused on defensive 

actions of the engineer squad, and included a 7.2-km forced march, dismounted route 

clearance operations, and a cache reduction evolution, as shown in Figure 23. 

(FOUO) At the conclusion of the defensive day, the Marines operated under the 

guidance of their platoon leadership, performing tasks that required minimal physical

demand and then bivouacking in the field, sleeping in 2-man tents.
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Figure 23. Combat Engineers Day-Two Scheme of Maneuver

9.2.2.2.1 Approach March

(FOUO) The beginning of day two started with a march carrying the approach load (40 

lb)14. Combat Engineers serving in the closed Combat Engineer Battalions work in 

direct support of, or are often attached to, Infantry units at various levels. As such, the 

Combat Engineers must be able to move through all sorts of terrain by foot. Moving 

under a load is one of the most fundamental tasks of a combat engineer in support of an 

infantry unit; it is both physically and mentally demanding. Each squad moved a 

distance of 7.20 km while carrying the approach march load and personal weapons. 

(FOUO) While the all-male squads were significantly faster than the integrated squads, 

all squads met the training standard. Figure 24 shows a conversion of the average 

squad times over the 7.2-km distance to pace. This conversion enables a comparison 

to the 4-km/h required to meet the standard.

 

14 The approach load is in addition to the fighting load (35 lb) and personal weapon (6.4 lb, 7.9 lb, or 10.5 lb 

depending upon weapon type assigned).
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Figure 24. Conversion from Average Elapsed Time for the 7.2-km 

March to Pace for the Combat Engineers Approach March

(FOUO) Similar to the 03XX squads, the movement over 20 miles in 8 hours equates to 

a pace of 4 kilometers per hour (km/h). This standard is applicable to Engineer squads 

because they are frequently assigned to Infantry units and are required to keep pace 

with the 03XX Marines. 

9.2.2.2.2 Route Sweep

(FOUO) Advancing foot mobile forces may require units to conduct route clearance 

missions to ensure that the lines of communication enable safe passage of combat,

combat-support, and combat-service-support organizations. The combat engineers are 

required to perform these route clearance tasks in support of ground forces as a way to 

reduce casualties and equipment losses on the battlefield. Upon completion of the 

7.2-km forced march, the combat engineer squad was required to conduct deliberate 

route clearance using mine detectors and sweeping a 500-meter lane. Time was not a 

component of this task; the squads were assessed based on their detection rate. 

(FOUO) There was no significant difference in detection rates between all-male squads 

and integrated squads.

9.2.2.2.3 Destroy Captured Munitions

(FOUO) At the conclusion of the route clearance mission, the engineer squads 

unearthed a large ammunition cache consisting of (32) 155-mm artillery shells, each 

shell weighing 95 lb. To deny the enemy access to the munitions, as well as to ensure 

the safety of the surrounding population, the engineers were required to move artillery 

shells to a safe location and destroy them with demolitions. During this task, the squad 
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loaded the ammunition onto the bed of a 7-ton truck, transported it to a safe demolition 

site, and then unloaded, buried, and subsequently destroys all 32 artillery shells. 

(FOUO) There were no significant differences in times for loading, digging, unloading, or 

rigging for detonation between the all-male squads and the integrated squads. One 

reason for the lack of observed time difference was noted based on the division of labor. 

In the most demanding portion of the task, loading the ammunition onto the bed of the 

7-ton truck, the female Marines were positioned on the bed of the vehicle to aid in the 

loading and stowing of the ammunition for transport rather than at the base of the 

vehicle. This resulted in the male Marines lifting the 95-lb artillery shells up from the 

ground at least 62 inches or higher to the bed of the 7-ton truck. 

9.2.2.2.4 Fatigue and Workload

9.2.2.2.4.1 Comparing Male Responses to Female Responses

(FOUO) Two self-report surveys (fatigue and workload) were administered to all 

volunteers at the end of trial activities on day two. The surveys were intended to 

provide insights into Marines’ perceptions of their own levels of fatigue and workload 

during the course of defensive trials. 

(FOUO) Overall, male engineers tended to report fatigue levels that were similar to 

female engineers, but male engineers reported lower workload levels than female 

engineers. 

9.2.2.2.4.2 Comparing Male Responses in Integrated Squads to All-male Squads

(FOUO) In addition to looking at how fatigue and workload self-reports compared 

between males and females, we also examined whether male responses remained 

consistent at different integration levels. 

(FOUO) The reported fatigue level of engineer males does not appear to be different 

based on squad integration level. Workload level of male engineers does appear to 

depend upon integration level, but it does appear to depend on whether they are in 

high-density integrated squads. This finding is consistent with the 03XX and PI results 

where integrated squads, especially high-density squads, move at a slower (easier) 

pace on the 7-km approach march, which results in lower workloads on males in those 

squads. 

9.2.2.3 Mountain Warfare (Open MOSs) 

(FOUO) Similar to the infantry, the mountaineering assessment replicated a logistical 

resupply of a forward-staged squad while moving in a mountainous environment. Each 

12-Marine squad departed an assembly area located at a lower base camp where they 

hiked 4.6 km with a 75-lb pack and personal weapon (M4) to an objective rally point. 
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(FOUO) The route for this movement was on an unimproved, hilly surface; the terrain 

was hard, rocky, and uphill, with an approximate gain in elevation of 175 meters, as 

shown in Figure 25. 

Figure 25. Elevation Change in Meters over 4.6-km Hike Distance

(FOUO) From the objective rally point, the squad crossed a 200-ft gorge via two singlerope bridges. Once across, the squad pulled their packs across and made a short 

movement to a location requiring a cliff ascent. Each Marine executed a 40-ft cliff 

ascent using two climbing lanes. The final action was to conduct a return foot-march to 

lower base camp. The return march was 5 km while wearing the 75-lb pack and 

personal weapon across terrain similar to the ascent, but downhill. The entire resupply 

mission took approximately 5 hours to complete.

(FOUO) The mountaineering tasks were non-MOS specific. Due to the non-MOSspecific nature of the tasks, all Marines from provisional infantry, provisional machine 

guns, and engineers were combined for the purposes of forming 12-Marine squads. 

Two types of squads were formed each day, all-male and high-density integration 

squads15. 

(FOUO) Every Marine received 1 day of recovery after each execution day over the 

course of 15 days. At the end of a day and during off-days, they lived in squad bays at 

lower base camp and operated under Company leadership, performing tasks that 

required minimal physical demand.

(FOUO) The all-male squads were faster than integrated squads on hikes, the gorge 

crossings, and cliff ascents. 

 

15 High-density integrated squads had six females per squad.
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(FOUO) Fatigue and workload self-report surveys were also administered at the end of 

mountain warfare activities, in particular after the ascent hike and upon return to lower 

base camp. When comparing males to females, males reported lower fatigue and 

workload results. Males also reported lower fatigue, but similar workload levels, when 

in integrated squads compared to when they were in all-male squads. 

9.2.3 Open MOS Summary

Figure 26 presents a summary of the differences observed when comparing all-male 

squads to integrated squads. The horizontal bars depict the percentage change 

observed when comparing the average all-male squad result to an average integrated 

squad result. The numerical percentage presented adjacent to the bar is indicative of 

statistical significance. Statistical significance is related to the size of the difference, 

variation, and the number of trials for that task. This explains why some larger bars 

show no significance. 

When a bar shifts to the right of the centerline the all-male group’s average is better 

than the integrated group’s. When a bar shifts to the left the integrated group’s average 

is better than the all-male’s. Most of the horizontal bars are shifted to the right for each 

MOS indicating that all-male groups typically outperform integrated groups.
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Figure 26. Open MOS Summary Comparison of Percentage Change of All Tasks

9.3 Objectives 1 and 2: Correlating Individual Physical Characteristics to 

Collective Mission Effects 

(FOUO) The previous sections within this objective discussed results only as they 

pertain to differences due to integration level and critical billets. The goal of statistical 

modeling, as applied here, is to estimate, simultaneously, the effect of genderintegration levels and other relevant individual variables on squad and team 

performance. 

(FOUO) For selected tasks described in the annexes and where possible, we examined 

the following individual, physical characteristics by Closed and Open MOSs:

• (FOUO) Age

• (FOUO) Height 

• (FOUO) Weight

• (FOUO) Armed Forces Qualification Test score 
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• (FOUO) General Technical score 

• (FOUO) Combat Fitness Test Movement to Contact time

• (FOUO) Combat Fitness Test Maneuver Under Fire time

• (FOUO) Physical Fitness Test crunches

• (FOUO) Physical Fitness Test 3-mile run time

• (FOUO) Rifle score

(FOUO) What we found is that there was no individual, physical characteristic that was

statistically significant and that had a practical impact on the model. Each time an 

individual, physical characteristic was statistically significant in a model, the effect was

practically negligible, conflicting, and/or incomplete for the squad or team. That is, there

were almost no tasks for which a variable is significant for all, or even most, members of 

a unit. 

(FOUO) Integration level, however, consistently appears as statistically significant for 

modeled tasks, and its effect is clear, causal, and practical. Therefore, integration level 

is the best variable to describe performance for each task.

9.4 Objectives 1 and 2: Task Cohesion 

(FOUO) Task cohesion in the experiment refers to an individual’s beliefs about team

closeness, similarity, and bonding around the group’s task. The task cohesion survey 

was an excerpt from a previously designed survey instrument, and was administered

upon conclusion of each MOS’s cycle. The task cohesion survey was intended to 

provide insights into Marines’ perceptions of how cohesive their unit was over the 

course of the run cycle. The cohesion survey was broken into five parts with an overall 

score given that sums the responses from each of the five questions. 

(FOUO) Overall, the Marines reported high levels of cohesion across all MOSs and 

genders. The MOS with the lowest cohesion result was the 0311s, but these results 

were still positive with respect to cohesion. We further examined the cohesion results in 

two different ways. The first comparison examined male responses vs. female 

responses, by MOS, to determine if there were any significant differences in responses. 

Figure 27 displays the results of the MOSs broken out into three rows. The MOSs in 

the top row are those where males report significantly higher cohesion scores than 

females. The MOSs in the middle row indicates no significant difference based on 

gender. The bottom row indicates where female cohesion results are reported as 

significantly higher than males. 
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Figure 27. Comparison of Male vs. Female Cohesion Survey Responses

(FOUO) During the first 2 months of the experiment in Twentynine Palms, just over half 

of the comparisons (6 of 11) showed no significant difference in cohesion based on 

gender comparisons. Females reported higher cohesion than males in 4 of 11 MOSs 

with only one MOS (0341) having males reporting higher cohesion results then females. 

The last month of the experiment at Mountain Warfare Training Center (MWTC) and 

Camp Pendleton (Amphib) showed a change in the cohesion results. 

(FOUO) At MWTC, all 03XX Marines were combined into one group, while PI, PIMG, 

and 1371 were combined into a second group. What we saw was a change in opinion, 

where males reported higher cohesion scores than females, although given all the 

factors that changed going from Twentynine Palms to Bridgeport, we cannot be certain 

what caused the change in results. The Amphib portion showed a similar change in 

cohesion results, where the results showed males leaning more favorably than females 

by the end of the experiment. Again, we cannot be certain of what caused the change.

(FOUO) The second method of examining cohesion results considered the results of 

only male participants, by MOS and integration level of the squad or crew. We 

performed this analysis to determine whether males’ cohesion responses remained 

consistent at different integration levels. 

(FOUO) What we found is shown in Figure 28 and indicates that almost universally 

males indicate higher levels of cohesion when working in all-male groups compared to 

integrated groups, regardless of MOS or location. The one exception was the Marines 

in the Open MOSs. In the Open MOSs at MWTC, we do see a small, but visible, 

increase in the percentage of males who rate all-male squads higher than integrated 

squads - though this is not enough to be statistically significantly. Provisional Machine 

Guns was omitted from the second analysis because there was insufficient data to draw 

any meaningful conclusions.
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Figure 28. Comparison of Male Results in All-male vs. Integrated Groups, by MOS

9.5 Objective 3 

9.5.1 Readiness

(FOUO) Readiness, at its most basic level, is a measure of the combat power available 

to respond to mission demands. Individual Readiness is a measure of a person’s 

availability to perform required military tasks on a given day. An individual can be 

unavailable for a variety of reasons, to include misconduct, and administrative or 

medical conditions, just to name a few. For the purposes of addressing readiness of the 

volunteers at the GCEITF, we restricted our analysis to medical readiness. 

(FOUO) The readiness dataset contains observations for each volunteer’s medical 

readiness at an individual level. The observed time began when the Marine joined the 

GCEITF and ended at the completion of the experiment. The completion of the 

experiment for an individual could either be the actual end of the experiment, when a 

Marine DORed, or when a Marine was dropped (due to medical reasons) from the 

experiment by GCEITF leadership. 

(FOUO) When comparing males to females, males were available 98.4% of the time 

while females were available 96.8% of the time. The cause of lower availability for 

females was their likelihood of injury. Females were more likely to be injured than 

males. However, once an injury occurs, the recovery time for males and females are 

similar. The breakout of injury sources reveals the greatest source of lost days for 

females was caused by occupational injuries, whereas males lost more days due to 

non-occupational causes. Table 3 displays a summary breakout, by cause and gender 

for unavailable days. 

Table 3. Percentage Breakout of Unavailable Days by Gender and Causality

Occupational Non-Occupational
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Male 40% 60%

Female 80% 20%

(FOUO) Our comparison of male and female injuries considers the fact that Marines are 

capable of incurring one or more injuries/illnesses during a time period. A descriptive 

comparison of the number of injuries and illnesses is displayed in Figure 29. 

Figure 29. Percentage of Volunteers, by Gender, with 

One or More Injuries or Illnesses

(FOUO) We analyzed the readiness data by gender, taking into consideration 

explanatory factors, and considered the fact that Marines often incur more than one 

injury or illness during a specified time period. 

(FOUO) We found that the only personnel variables that consistently stood out as 

predictors of readiness were gender and MOS type. In particular, with the exception of 

non-occupational injuries, outcomes were always worse for female volunteers. 

Additionally, Marines in vehicle MOSs tended to have lower injury rates than those in 

hiking or Artillery MOSs. Finally, the CFT MANUF time appears several times as a 

predictor of readiness, so we recommend further investigating the relationship of this 

measure with injury rates. 

9.5.2 Proficiency and Conduct

(FOUO) No valid results were available to report; see paragraph 5.2. 
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10. Conclusions

10.1 Objectives 1 & 2 

(FOUO) The female Marines integrated into the closed MOS units demonstrated that 

they are capable of performing the physically demanding tasks, but not necessarily at 

the same level as their male counterparts in terms of performance, fatigue, workload, or 

cohesion. 

(FOUO) Integrated units, compared with all-male units, showed degradations in the time 

to complete tasks, move under load, and achieve timely effects on target. The size of 

the differences observed between units and tasks varied widely. The more telling 

aspect of the comparisons is the cumulative impacts. The pace, timing, and accuracy of 

any singular task is not necessarily important, but taken together, and in the context of 

actual combat operations, the cumulative differences can lead to substantial effects on 

the unit, and the unit’s ability to accomplish the mission.

10.2 Objective 3 

(FOUO) Gender and MOS type are the best predictors of occupational injuries. In 

particular, we found that females are more likely to incur occupational injuries, resulting 

in reduced readiness compared to their male counterparts. Males, on the other hand, 

are more likely to incur non-occupational injuries. Additionally, Marines in vehicle MOSs 

tended to have lower injury rates than those in MOSs that march (i.e., foot mobile) or 

Artillery MOSs. 

(FOUO) No clear conclusions can be drawn from the Proficiency and Conduct ratings of 

the GCEITF volunteers.

11. References

a) MCOTEA. Ground Combat Element Integrated Task Force Experimental Event 

Plan. January 2015

b) MCOTEA. Ground Combat Element Integrated Task Force Experimental Data 

Report. May 2015 

c) MCOTEA. Ground Combat Element Integrated Task Force Experimental 

Assessment Plan. May 2014

Annex A. Infantry Rifleman (MOS: 0311) 

Annex B. LAV Crewman (MOS: 0313)
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Annex C. Infantry Machine Gunner (MOS: 0331)

Annex D. Infantry Mortarman (MOS: 0341)

Annex E. Infantry Assaultman (MOS: 0351) /

Infantry Antitank Missileman (MOS: 0352)

Annex F. Provisional Infantry (Open MOSs)

Annex G. Provisional Machine Gunner (Open MOSs)

Annex H. Field Artillery Cannoneer (MOS: 0811)

Annex I. Tank Crewman (MOS: 1812)

Annex J. AAV Crewman (MOS: 1833)

Annex K. Combat Engineer (MOS: 1371)

Annex L. Bridgeport Experiment (MOS: Closed)

Annex M. Bridgeport Experiment (MOS: Open)

Annex N. Fatigue, Workload, and Cohesion Surveys

Annex O. Readiness

Annex P. Proficiency and Conduct

Annex Q. GCEITF Population

Annex R. Methodology
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Annex A. 

Infantry Rifleman (MOS 0311)

This annex details the Infantry Rifleman (MOS 0311) portion of the Ground Combat 

Element Integrated Task Force (GCEITF) experiment executed 2 March–26 April 2015 

at Range 107 and Range 110 aboard the Marine Corps Air-Ground Combat Center

(MCAGCC), Twentynine Palms, CA. The sections outline the Infantry Rifleman Scheme 

of Maneuver (SOM), Limitations, Deviations, Data Set Description, Descriptive and 

Basic Inferential Statistics, and Modeling Results.

A.1 Scheme of Maneuver

A.1.1 Experimental Cycle Overview

The Infantry Rifleman (MOS 0311) assessment of the GCEITF took place in a field 

environment aboard MCAGCC, Twentynine Palms, CA. The assessment consisted of 

21 trial cycles, each of which was a 2-day test cycle, conducted over the course of 55 

days. After every 4 days of trials, the Marines received 1 recovery day spent at Camp 

Wilson. Each squad consisted of 12 volunteers and a direct assignment (nonvolunteer)

squad leader. Each member of the squad was trained to fill each billet within the 

fireteam: fireteam leader, grenadier, automatic rifleman, and rifleman. The rifle squad 

contained three fireteams. The assessment was executed under the supervision of 

MCOTEA functional test managers and a range officer-in-charge (OIC)/range safety 

officer (RSO) from the GCEITF. 

A.1.2 Experimental Details

The 2-day 0311 assessment was modeled to replicate offensive and defensive tasks. 

The 0311s began each cycle on the Day 1/Offensive task. Two 0311 squads executed 

each trial cycle: a control (C) nonintegrated squad, and a high-density (HD) integrated 

squad with 2 females.

Day 1 of the trial cycle was executed on Range 107 and consisted of a squad-reinforced 

attack. Each squad moved approximately 1 km to an assault position wearing an 

assault load and carrying personal weapons. As a squad, they moved all personnel and

gear over an 8-ft obstacle/wall. After negotiating the obstacle, the squad staged their 

assault packs, deployed on-line, and conducted a 425-m live-fire assault to a limit of 

advance (LOA) wearing the fighting load. They immediately repelled an enemy 

counterattack by fire for 90 seconds. Finally, each fireteam conducted a 100-m casualty 

evacuation (CASEVAC) of a 220-lb dummy. 

Day 2 of the experimental cycle was executed on Range 110 and consisted of 

defensive actions. The day started with the squads making a 7-km march from Range 
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107 to Range 110 wearing an approach load and carrying personal weapons. After a 

10-minute operational pause, each fireteam spent 2 hours digging 2-man fighting 

positions wearing a fighting load. Two Marines from each fireteam provided security 

while the other two dug, rotating every 15 minutes. At the conclusion of Day 2, the 

composition of the squad was dissolved and a new sample of males and females were 

randomly assigned for the following cycle. 

A.1.3 Additional Context

Throughout the duration of the assessment, Marines bivouacked at Range 107, 

sleeping in 2-man tents. Prior to the Day 1 trial, each Marine zeroed his or her weapon 

system to maximize accuracy. During trial execution, Marines wore/carried prescribed 

loads for each task. Packs were weighed each day prior to the 7-km march to ensure 

consistency. After each trial day, the Marines operated under the guidance of their 

company leadership, performing minimal physically demanding tasks. Not all Marines 

were selected for each trial cycle. Those Marines who were not part of an assessed 

squad conducted the same experimental subtasks to ensure equity in physical loading 

between individuals participating in a trial cycle and those not chosen via random 

selection for that particular cycle. (A detailed discussion of these loading tasks are in 

the loading section below.) 

Fatigue surveys were designed to capture the volunteers’ cumulative fatigue level at the 

beginning and end of each day’s trials. The data collected provide additional insight into 

apparent aberrations in the performance level of a given volunteer on a specific day. It 

allows for outside fatigue-related factors (minor illness, lack of sleep the night before, 

etc.) to be accounted for in the analysis of the performance data. Workload surveys 

collected the volunteers’ perceived average and maximal level of exertion during the 

specified performance tasks. Cohesion surveys provided a method of collecting 

subjective data relating to each squad’s ability to work as a team and its members’ 

overall perspective on the cohesiveness of the squad. 

A.1.4 Experimental Tasks

A.1.4.1 1-km Movement 

Assaulting an enemy position never starts from a static position: First, a movement must 

be conducted to the assault position (AP). The distance from the line of departure to 

the AP is dependent upon myriad factors. Based on time and space constraints during 

the GCEITF assessment, this distance was a little less than 1 km. Each rifle squad 

moved this distance as quickly as possible while carrying an assault load and individual 

weapon. The Infantry Training and Readiness (T&R) Manual states that “the assault 

load is the load that is needed during the actual conduct of the assault.” This task put 

the Marines under moderate fatigue prior to commencing the attack. 
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A.1.4.2 Negotiate an Obstacle

The conduct of an attack often involves reducing or negotiating an obstacle. It is 

common in an urban environment to make entry through a window or over a wall 

(obstacle). One of the more difficult tasks is climbing over a wall with a fighting load. 

Each squad negotiated an 8-ft wall by getting all Marines and equipment over as quickly 

as possible. Although the technique was not dictated, the 0311 squads used a single 

launch-point to lift all Marines up onto the wall. 

A.1.4.3 Squad Attack and Movement to LOA

The mission of the rifle squad is “to locate, close with, and destroy the enemy by fire 

and maneuver, and repel the enemy’s assault by fire and close combat.” Conducting a 

live fire-and-movement task is fundamental to the Infantry community and operationally 

relevant. Having moved to an AP, each rifle squad deployed into an on-line formation to 

maximize firepower in the direction of the enemy and then began movement-to-contact 

with weapons at the ready. Upon contact with the enemy (targets being presented), the 

Marines laid down a heavy volume of fire to gain fire superiority. They then began 

buddy rushes to close with the enemy objective. Each squad conducted approximately 

300 meters of buddy rushes, engaging a total of 12 GCEITF targeting systems (GTS) 

with direct-fire weapons and three machinegun bunkers with the M16A4 and M203 

grenade-launcher attachment. After all targets were destroyed (no targets remaining), 

the squad moved another 125 meters to an LOA and prepared for an enemy 

counterattack. This task is physically demanding and involves a combination of 

accuracy, tempo, and squad cohesion. 

A.1.4.4 Repel Counterattack

At the conclusion of every assault, the attacking unit must be prepared for the enemy to 

regroup and organize a counterattack. Upon consolidation at the LOA, the squad 

oriented its weapons in the direction of the enemy’s retreat. Upon target presentation, 

the counterattack commenced for 90 seconds. Six GTSs were used during the course 

of the counterattack. The primary purpose of this task was to determine the squad’s 

accuracy engaging targets approximately 300 meters away after conducting a squad 

attack. 

A.1.4.5 CASEVAC

Casualties are an inevitable part of conducting combat operations. Units train to 

become proficient in triaging, handling, and transporting a casualty. After a Marine is 

injured, it is essential to move the casualty to the appropriate level of care as quickly as 

possible. During the GCEITF assessment, each fireteam was assigned a casualty at 

the conclusion of the live-fire attack and counterattack. Each fireteam had to move a 

220-lb casualty (dummy and equipment) a distance of 100 meters to a casualty 
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collection point (CCP). They could use a variety of techniques for transport, but had to 

carry the dummy off the ground (not drag any part). The primary purpose of this task 

was to determine the fireteam’s proficiency in moving a simulated casualty to a CCP. 

After the CASEVAC, each Marine took a fatigue and workload survey to assess overall 

fatigue and workload of the entire offensive task (see GCEITF Experimental 

Assessment Plan, Annex D). 

A.1.4.6 7-km Hike

Moving under a load is one of the most fundamental tasks of an Infantry unit; it is both 

physically and mentally demanding. Units train by conducting tactical marches with an 

approach load at increasing distances. The Infantry T&R Manual states that “the 

approach march load will be such that the average Infantry Marine will be able to 

conduct a 20 mile hike in 8-hours with the reasonable expectation of maintaining 90% 

combat effectiveness.” During the GCEITF assessment, each rifle squad moved a 

distance of 7.20 km from Range 107 to Range 110. This route was flat (minimal 

elevation change) and conducted on an unimproved surface with varying degrees of 

conditions (compact dirt and loose sand). The squads moved as fast as the slowest 

person, carrying an approach load and an individual weapon. The individual weapons 

included the M-4, M-16A4 with M203 attachment, and the M27, resulting in a cumulative 

load of 96–101lbs per Marine. The primary purpose of this task was to determine the 

squad’s pace over a 7.20-km route while carrying the approach load. Each Marine took 

a fatigue and workload survey after completion of the 7.20 km hike (see GCEITF EAP, 

Annex D).

A.1.4.7 Digging Fighting Holes

Protection is vital to Infantry units, especially in a defensive posture. Infantry units 

commonly construct fighting positions to conceal positions and minimize exposure to 

enemy fire. There are many characteristics to constructing a doctrinal fighting position, 

but the most physically demanding aspect is digging out the fighting hole. The terrain at 

Twentynine Palms consists of hard, compact sand and rocks. Each fireteam dug 2 2-

man fighting holes in a time limit of 2 hours, maintaining 50% security, meaning 2 

Marines dug while 2 provided security in the prone position. The Marines swapped 

positions every 15 minutes. The purpose of this task was to determine the fireteam’s 

rate of work while digging fighting positions. After 2 hours, each Marine took a fatigue 

and workload survey (see GCEITF EAP, Annex D). 

At the completion of the 2-day cycle, Marines also took a cohesion survey to record 

cohesion during the execution of the 2-day trial cycle (see GCEITF EAP, Annex M). 
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A.1.5 Loading Plan

Due to the number of volunteers, a handful of Marines were not part of an assessed 

squad for each 2-day cycle. The primary purpose of the loading plan was to ensure, to 

the greatest extent possible, equity of physical activity among all volunteers throughout 

the duration of the experimental assessment. Collaboration with the company 

leadership determined that the best method of loading nonassessed Marines was to 

have them perform the same tasks as an assessed squad to experience the same 

conditions and physical strain. Every trial and task was conducted in the same manner 

and sequence to ensure consistency. 

A.1.5.1 Variations

Several factors, including safety and the number of loading Marines, introduced 

variations to the loading plan. 

• In some instances, the loading Marines formed a quasi-squad and conducted the 

trial after all assessed squads were done for the day. At other times, the quasisquad was too small, so the loading Marines were attached to an assessed 

squad, in which case they operated on the flanks and were not given 

ammunition. At no point in time did a loading Marine aid or interfere with an 

assessed Marine/squad. 

• The loading Marines did not always dig for 2 hours. To gain efficiencies, the 

loading Marines would rotate between digging, assisting in weighing buckets of 

sand, and refilling the holes of the assessed squads. Any such variation was 

carefully calculated to ensure loading Marines were doing an equivalent amount 

of work as the assessed Marines. 

A.1.6 Scheme of Maneuver Summary

The 0311 experiment consisted of a 2-day trial cycle comprising an offensive and 

defensive day. The offensive day involved five subtasks based around a squad live-fire 

attack: 1-km movement, negotiating an obstacle, fire and movement, counterattack, 

and CASEVAC. The defense day involved two subtasks: a 7-km march and digging a 

fighting position. During the course of the experiment, the 0311/Provisional Infantry (PI) 

squad executed 2 pilot trial cycles and 21 record trial cycles. During trial execution, 

Marines rotated through every billet within the rifle squad, carrying the respective 

weapon system. 

A.2 Limitations 

A.2.1 Limitations Overview

The GCEITF experiment was designed to allow operationally relevant tasks to occur as 

naturally as possible, while gathering unbiased measurements. Most tasks were 
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performed in a similar manner to those in an operational environment. However, under 

certain situations, artificial limitations or interruptions were introduced that changed or 

altered the way a task would normally be performed. While these limitations represent 

a degree of artificiality, they do not detract significantly from our ability to generalize the 

conclusions of this experiment to the performance of Marines in a field environment. 

The following limitations were observed for the 0311 assessment. 

A.2.2 Relative Difficulty of Record Test

The Infantry GCEITF assessment was designed to gather data associated with some of 

the most physically demanding tasks within the 0311 MOS. However, these tasks in 

isolation did not fully replicate life experienced by a Marine during a typical field exercise 

(FEX) or a combat environment and did not obtain the maximum cumulative load that 

could be placed on an Infantry Marine. With limited time available, only selected 0311 

tasks were assessed. Other tasks/duties outside of the assessment were minimized

due to specific experimental constraints and human factors. During a typical FEX, it is 

common for Marines to conduct 24-hour operations that include day and nighttime 

operations/patrols, standing firewatch or a security post, and conducting continuing 

tactical actions. It took 0311 squads approximately 1 hour to complete the offensive 

day and approximately 4 hours to complete the defensive day. Outside the assessed 

trials, there were minimal tasks required of the volunteers that demanded any degree of 

physical strain. 

Another concern in designing the 0311 assessment was to ensure that it was 

achievable and sustainable for a 60-day period. The 7-km march distance was selected 

based on the training time available prior to the assessment. However, many of the 

loads carried were decreased prior to the commencement of the 21 cycles used to form 

the dataset. Once over the wall obstacle, the 0311s staged their assault packs without 

security rather than wearing them during the fire-and-movement. The 0311s also did 

not carry additional ammunition, radios, batteries, or other equipment often required 

when operating in a tactical environment. The Marines were authorized 1 day off after 

every 4 days of training; this artificial recovery period is not achievable when conducting 

training or combat operations. 

A final factor affecting the relative difficulty of the record test pertains to the intangible 

physiological impact of the volunteers’ ability to drop on request (DOR) at any point

during a trial. Any time a volunteer dropped during a trial cycle, that squad/team 

performed the following subtasks with fewer personnel. This factor affected the 

cohesion of each squad and influenced its performance. 

A.2.3 Digging a Fighting Position

Several artificialities were present as the volunteers dug their fighting holes. Preparing 

a defensive fighting position involves many continuing actions by those not actually 
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digging the hole, such as clearing fields of fire, creating sectors of fire, etc. However, no 

continuing defensive actions were conducted other than lying in the prone position and 

providing notional security. The Marines digging would not normally fill up a 5-gallon 

bucket for measurement; under normal conditions they would either fill sandbags or 

build up a parapet. These artificialities may have influenced their performance and 

morale.

A.2.4 Number of Volunteer Participants

For the 0311 experiment, 36 male and 9 female volunteers began the experiment, but 

by the end 28 males and 6 females completed the assessment. The results presented 

in this annex are based on the performance of 34–45 Marines. 

A.2.5 Limitations Summary

The 0311 assessment was designed to replicate realistic training in a field environment. 

The end-state was to create an experiment in which the volunteers felt they were 

conducting realistic and operationally relevant tasks, but unavoidable limitations to the 

assessed tasks and non-assessed operating environment introduced a level of 

artificiality not normally present in a field training or combat environment. 

A.3 Deviations 

A.3.1 Concentration for Rifle Squad

Marines participated in this experiment voluntarily and could leave the experiment at 

any time, for any reason, making the total number of subjects available highly volatile. 

Trials were not executed if there were not enough participants to carry out the assigned 

mission and if attrition affected the integration levels for the 0311 experiment. The EAP 

stated that the Rifle Squad would have three levels of integration: C group, low-density

(LD) group, and high-density (HD) group, with zero females, one female, and two 

females, respectively. Prior to the beginning of the first record trial cycle, the population 

could no longer support an LD group. The MCOTEA Research Team eliminated the LD

group and began the Record Trials on 7 March 2015 with the control and HD groups 

only.

A.4 Data Set Description 

A.4.1 Data Set Overview

The 0311 portion of the experiment consisted of 2 pilot trial cycles and 21 record trial 

cycles. The pilot trial cycles were conducted from 2 March to 6 March 2015. Pilot trial 

cycle data are not used in analysis due to variations in the conduct of the experiment. 

We based all analysis on the 21 record trial cycles executed from 7 March to 26 April 

2015.
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A.4.2 Record Test Volunteer Participants

At the beginning of the first record trial cycle, there were 36 male 0311 volunteers and 9 

female volunteers. There were several Marines who voluntarily withdrew, or were 

involuntarily withdrawn, during the execution of the experiment. The final number of 

volunteers was 28 males and 6 females. 

A.4.3 Planned, Executed, and Analyzed Trial Cycles

Table A-1 displays number of trial cycles planned, executed, and analyzed by task. The

planned number of trials for the 0311 MOS per section 7.5.3 of GCEITF EAP was 120 

trial cycles, or 40 trial cycles per planned integration level (C, LD, and HD). The original 

plan called for 6 squads per day (2 per integration level) over the 20 trial cycles. 

However, due to the number of Marines who voluntarily withdrew or were involuntarily 

withdrawn from the experiment prior to the execution of the first record trial cycle, only 

one squad of the C and HD integration levels remained. We chose to keep the HD 

integration level to employ more Marines in the experiment. The planned number of 

trial cycles in Table A-1 reflects 21 planned trial cycles for each integration level. 

There are several occurrences of missing data for the 7-km hike by individual kilometer. 

The individual kilometer times were derived from GPS data. Early in the experiment, 

the Garmin GPS’s were set to record a volunteer’s position every second. Due to the 

storage space on the GPS and length of the trial, when volunteers executed the 7-km 

hike and then 2 hours of preparing a fighting position, the GPS could not hold all the 

data. Therefore, it overwrote the hike data. Once the problem was found, the GPSs 

were corrected to record location every 2 seconds.
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Table A-1. 0311 Planned, Executed, and Analyzed Trial Cycles

Task and 

Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

trials 

conducted 

Number of 

trials used in 

analysis

Notes

7-km Hike C 21 21 20 Remove Mar 28 due to TIRa

HD 21 21 21

Movement to 

LOA

C 21 20 19 Did not execute Mar 19 due to targets 

catching on fire. Mar 17 outlier.

HD 21 21 20 Mar 17 outlier

Attack & C-Atk 

Percent Hits

C 21 20 20 Did not execute Mar 19 due to targets 

catching on fire

HD 21 21 21

CASEVAC by 

FT

C 84 82 82 Did not execute Mar 19 due to targets 

catching on fire

HD 42 41 41

Prepare 

Fighting 

Position by FT

C 84 84 84

HD 42 41 41 Mar 10 FT 3 attrited

1-km Hike C 21 20 20 Did not execute Mar 19 due to targets 

catching on fire

HD 21 21 20 Mar 17 outlier

Negotiate 

Obstacle

C 21 20 19 Did not execute Mar 19 due to targets 

catching on fire. Mar 7 outlier.

HD 21 21 21

7-km Hike; 

1km Time

C 21 21 17 No data: Mar 8, Mar 13, Mar 15, Mar 

18.

HD 21 21 18 No data: Mar 8, Mar 15, Mar 18.

7-km Hike; 

2km Time

C 21 21 16 No data: Mar 8, Mar 10, Mar 13, Mar 

15, Mar 18.

HD 21 21 18 No data: Mar 8, Mar 15, Mar 18.

7-km Hike; 

3km Time

C 21 21 16 No data: Mar 8, Mar 10, Mar 13, Mar 

15, Mar 18.

HD 21 21 19 No data: Mar 8, Mar 18

7-km Hike; 

4km Time

C 21 21 16 No data: Mar 8, Mar 10, Mar 13, Mar 

15, Mar 18.

HD 21 21 19 No data: Mar 8, Mar 18

7-km Hike; 

5km Time

C 21 21 16 No data: Mar 8, Mar 10, Mar 13, Mar 

15, Mar 18.

HD 21 21 19 No data: Mar 8, Mar 18

7-km Hike; 

6km Time

C 21 21 16 No data: Mar 8, Mar 10, Mar 13, Mar 

15, Mar 18.

HD 21 21 19 No data: Mar 8, Mar 18

7-km Hike; 

7km Time

C 21 21 16 No data: Mar 8, Mar 10, Mar 13, Mar 

15, Mar 18.

HD 21 21 19 No data: Mar 8, Mar 18 a. A TIR in this table refers to a Test Incident Report, which is a report the test team or direct assignment 

leaders completed when an incident occurred that affected the natural execution of a trial. If a data point 

is removed due to a TIR, it is because the TIR affected the data in such a way that it is not comparable to 

the rest of the dataset.

A.5 Descriptive and Basic Inferential Statistics 

A.5.1 Descriptive Statistics Overview

Performance metrics were measured during the conduct of common Infantry tasks and 

are indicative of unit-level proficiency during either field exercises or combat operations. 
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This section presents results for 7 out of 16 tasks. The 0311 Appendix contains the 

descriptive statistics for the remainder of the 0311 tasks. The words “metric” and “task” 

are used interchangeably throughout this Annex; both refer to the experimental task. 

Each fireteam consisted of four volunteer Marines: the fireteam leader, automatic 

rifleman, grenadier, and rifleman. Each squad consisted of 12 volunteer Marines (three 

fireteams) with a direct assignment (nonvolunteer) squad leader. There were two 

integration levels for all tasks. For squad-level tasks, a C group was non–gender 

integrated, and a HD group was gender integrated with two female Marines. For 

fireteam-level tasks, a C group was non-gender integrated and an HD group contained 

at least one, but not more than two, females. 

This section includes experimental results based on descriptive statistics, analysis of 

variance (ANOVA), and scatterplots. The subsequent sections will cover each task in 

detail. Finally, contextual comments, additional insights, and subjective comments (as 

applicable) tying back to each experimental task are incorporated. 

Use caution when comparing similar tasks executed by different MOSs within the 

GCEITF experiment. Comparative analysis may be misleading due to differing factors 

between MOS tasks such as distances, techniques, leadership, load carried, group size, 

and group composition.

A.5.2 0311 Selected Tasks Descriptive Statistics Results

The two tables below display the results for the 7 selected 0311 metrics. Table A-2

displays the metrics and integration levels with their respective sample sizes, means, 

and standard deviations. Table A-3 displays ANOVA results, including metrics and 

integration levels, p-values suggesting statistical significance, integration level elapsedtime differences, and percentage differences between integration levels. For each task, 

an ANOVA and t-test were conducted to compare the two groups. If p-values are less 

than the a priori–determined significance level of 0.10, we conclude that there is 

statistical evidence that the response for the HD group is different from that in the C 

group. 

Table A-2. 0311 Selected Task Results (Descriptive Statistics)

Metric Description Integration 

Level

Sample 

Size Mean SD 

7-km Hike (minutes)a C 20 79.76 3.12

HD 21 82.40 3.90

Movement to LOA 

(minutes)a

C 19 2.65 0.21

HD 20 2.89 0.25

Attack & C-Atk Percent 

Hits (%)a

C 20 0.40 0.05

HD 21 0.36 0.07

CASEVAC by FT C 82 1.46 0.25
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Metric Description Integration 

Level

Sample 

Size Mean SD 

(minutes)a

HD 41 1.57 0.47

Prepare Fighting Positions 

by FT (lbs.) 

C 84 4284.86 1005.43

HD 40 4041.81 1017.44

1-km Hike (minutes)a C 20 8.07 0.53

HD 20 8.49 0.39

Negotiate Obstacle 

(minutes)

C 19 2.77 0.34

HD 21 2.92 0.48 a.Indicates that there is a statistically significant difference, in either a 

one-sided or two-sided hypothesis test, between integration levels 

according to ANOVA.

Table A-3. 0311 Selected Task ANOVA and Welch’s T-test Results

Metric

F 

statistic 

(df)

F 

Test

Pvalue

Compariso

n 

Differenc

e 

% 

Differenc

e 

2-sided 

PValue

1-sided 

P-Value

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

7-km Hike 

(minutes)*

5.73

(1, 39) 0.02a HD-C 2.64 3.32% 0.02a 0.01a 1.21 4.08 0.79 4.50

Movement 

to LOA 

(minutes)*

10.76

(1, 37)

< 

0.01a HD-C 0.24 9.06% < 0.01a < 0.01a 0.15 0.34 0.12 0.36

Attack & 

C-Atk (% 

hit)*

4.76

(1, 39) 0.04a HD-C -0.04 -10.40% 0.03a 0.02a -0.07 -0.02 -0.07 -0.01

CASEVA

C 

(minutes)*

2.96

(1, 121) 0.09a HD-C 0.11 7.63% 0.16 0.08a 0.01 0.21 -0.02 0.24

Prepare 

Fighting 

Positions

(lbs)

1.57

(1, 122) 0.21 HD-C -243.05 -5.67% 0.21 0.11 -

494.78 8.67 -

567.28 81.18

1-km Hike

(minutes)*

8.04

(1, 38) 0.01a HD-C 0.42 5.18% 0.01a < 0.01a 0.23 0.61 0.17 0.67

Negotiate 

Obstacle

(minutes)

1.24

(1, 38) 0.27 HD-C 0.15 5.33% 0.27 0.14 -0.02 0.32 -0.07 0.37

a.Indicates that there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA.

A.5.2.1 7-km Hike Results

A.5.2.1.1 7-km Hike Overview

This experimental task assessed a squad of 12 Marines moving 7.20 km while each 

carried an approach load and an individual weapon. The individual weapons included 

the M-4, M-16A4 with M203 attachment, and the M27, resulting in a cumulative load of 

96–101 lbs per Marine The recorded time for this task started when the squad departed 

the Range 107 start point and stopped when the squad arrived at the Range 110 stop 

point. Each squad moved as fast as the slowest person and could take as many breaks 

as necessary. 
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Figure A-1 displays all 0311 Infantry 7-km hike time data. On trial cycle 9, the C data 

point was removed from the analysis due to a TIR; this data point is circled in black in 

the figure. With the exception of this data point, all data on the scatterplot are valid for 

analysis.

Figure A-1. 7-km Hike

The data are normally distributed, as evidenced by the Shapiro-Wilk test that resulted in 

a p-value of 0.17 for the C group and 0.81 for the HD group. 

The C group had a mean time of 79.76 minutes. This time is statistically significantly

faster than the HD mean time of 82.40 minutes. This difference results in a 3.32%, or 

2.64-minute, degradation in hike time between the groups. The HD group has greater 

variability, as shown by the 0.78-minute increase in standard deviation (SD) (3.12 

minutes for the C group and 3.90 minutes for the HD group). (See Tables A-2 and A-3 

for detailed analytical results.) 

A.5.2.1.2 7-km Hike Contextual Comments

A.5.2.1.2.1 USMC Hike Standards

The 7-km hike is a task that the following MOSs completed during the experiment: 

0311, 0331, 0341, 0351 and 0352, Provisional Infantry (PI), Provisional Machine 

Gunners, and Combat Engineers. There are varying standards to which we can 
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compare this result. The following sections define those standards, as well as the one 

we chose as a comparison.

The Infantry T&R Manual (30 Aug 2013) identifies minimum standards that Marines 

must be able to perform in combat, including standards for tactical marches. In Chapter 

8 of the Infantry T&R Manual in the MOS 0300 Individual Events section, task 0300-

COND-1001 (March under an approach load) is applicable to all 03XX MOSs, ranks 

PVT–LtCol. The condition and standard established by this task is: “Given an 

assignment as a member of a squad, individual weapon, and an approach load, 

complete a 20-kilometer march in under 5 hours.” The march pace required by this 

standard is 4 kilometers per hour (km/h). In Chapter 9 of the Infantry T&R Manual in the 

MOS 0302/0369 Individual Events section, tasks 0302-OPS-2001 (Lead an approach 

march) and 0369-OPS-2501 (Lead an approach march) are applicable to MOS 0302 

and 0369, ranks SSgt–MGySgt and 2ndLt–LtCol. The condition and standard 

established by these tasks is: “Given a mission, time constraints, an approach march 

load, organic weapons, and a route, move 24.8 miles (40 km) in a time limit of 8 hours.” 

The march pace required by this standard is 5 km/h. Appendix E of the Infantry T&R 

Manual (Load Terms and Definitions) states: “The approach march load will be such 

that the average Infantry Marine will be able to conduct a 20 mile hike in 8-hours with 

the reasonable expectation of maintaining 90% combat effectiveness.” The march pace 

required by this definition is 4.02 km/h.

Chapter 3 of Fleet Marine Force Reference Publication (FMFRP) 3-02A: Marine 

Physical Readiness Training for Combat (16 Jun 2004) states: “The normal pace is 30 

inches. A pace of 30 inches and a cadence of 106 steps per minute result in a speed of 

4.8 km/h or 3 mi/h and a rate of 4 km/h or 2.5 mi/h if a 10-minute rest halt per hour is 

taken.” Common Infantry practice today is to hike for 50 minutes and take a 10-minute

break, while maintaining an overall pace of 4 km/h (resulting in a hiking pace of 4.8 

km/h). 

Driven by the need to pick an evaluative reference standard, this report follows the T&R 

Manual’s intent to establish minimum standards and uses the 4 km/h march pace for a 

20 km march established by task 0300-COND-1001 and supported by the definition of 

an approach load. Further, while an established reference standard is required to 

anchor observed performance to the T&R program, more important information is 

provided by performance differences observed between gender-integrated and non–

gender integrated units.

A.5.2.1.2.2 0311 7-km Hike Pace

The difference in 7-km hike times is relevant to both the training and combat 

environment as it will take integrated squads more time to conduct foot marches. Per 

the tactical march standards noted above, the Marine Corps standard of hiking is 4.0 

km/h. Both the C and HD groups surpassed this standard. The average C group’s 
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7.20-km pace was 5.42 km/h and the average HD group’s pace was 5.24 km/h, 

meaning the HD group was 0.17 km/h slower. To extrapolate this pace over a 20-km 

movement (an optimistic assumption that does not account for any further degradation 

of performance), the HD group would finish 7.33 minutes behind the C group. 

The 0311 Appendix contains the descriptive statistics for each individual km of the 7-km 

hike, and these data show that the C and HD groups had an increasing trend in 1-km 

split-times over the course of the 7.20-km march. Both groups’ march pace decreased 

over the distance marched. The C group’s speed decreased at a trend rate of 0.20 

km/h per km, while the HD group’s speed decreased at 0.24 km/h per km. Assuming 

this speed decrement continued for every kilometer in a 20-km march (a pessimistic 

assumption that ignores attainment of a sustainable pace), then the HD group would 

have been 57 minutes behind the C group at the finish of a 20-km march. More 

realistically—and allowing for the attainment of a sustainable pace—if we assumed 

each group followed its speed decrement trend down to the first kilometer, where its 

speed was just under the 4 km/h standard and then finished the march at that predicted 

pace, then the HD group would have been 14.4 minutes behind the C group at the finish 

of a 20-km march. On any given day (under the same environmental conditions), the C 

group was faster than the HD group 76.2% of the time (16 of 21 trial cycles).

A.5.2.1.3 7-km Hike Additional Insights

While the difference in the 7-km hike time and speed is statistically significant, the size 

of the difference is small. A purely objective evaluation of 0.17 km/h slower hike speed 

is elusive, but Marine Corps Doctrinal Publications (MCDP) consistently emphasize the 

importance of speed. MCDP 1-3: Tactics devotes an entire chapter to “Being Faster,” 

stating: “Physical speed, moving more miles per hour, is a powerful weapon in itself.” 

MCDP-6: Command and Control also speaks to speed relative to the enemy, stating:

“The speed differential does not necessarily have to be a large one: a small advantage 

exploited repeatedly can quickly lead to decisive results.” Nonetheless, the difference 

observed between the C and HD groups in the 0311 Infantry 7-km hike task was a 

nominal 2.64 minutes. For an indication of performance when the load is increased, 

see the 0331, 0341, and 035X 7-km hike data and contextual comments. 

A.5.2.1.4 7-km Hike Subjective Comments

For subjective comments relating to this task, see the 0311 Appendix. The subjective 

comments reveal a fairly equal spread of males and females who were falling behind 

and slowing the overall movement. 
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A.5.2.2 Movement to LOA

A.5.2.2.1 Movement to LOA Overview

This experimental task assessed a squad moving approximately 125 meters to an LOA 

immediately after conducting a fire-and-movement assault. The recorded time started 

when the last target went down after the assault and stopped when the last member of 

the squad was prone at the LOA. 

Figure A-2 is a scatterplot showing all 0311 Movement to LOA time data. On Trial 

Cycle 5, the C and HD group data points were removed from the analysis due to data 

collection errors; data omitted from the analysis are circled in black. With the exception 

of the Trial Cycle 5 data points, all data on the scatterplot is valid for analysis.

Figure A-2. Movement to LOA

The data are normally distributed, as evidenced by the Shapiro-Wilk test that resulted in 

a p-value of 0.22 for the C group and 0.31 for the HD group. 

The C group has a mean of 2.65 minutes. This time is statistically significantly faster 

than the HD mean time of 2.89 minutes. This difference results in a 9.06%, or 0.24-

minute, degradation in movement time between the groups. The HD group has greater 

variability, as shown by the 0.04-minute increase in SD (0.21 minutes for the C group 

and 0.25 minutes for the HD group). See Table A-2 and Table A-3 for detailed 

analytical results.
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A.5.2.2.2 Movement to LOA Contextual Comments

The ability to close with the objective after conducting a live-fire attack is a crucial 

aspect to maintaining momentum during offensive operations. In this case, the 

integrated squads were exposed to the enemy 14.4 seconds (9.06%) longer and had 

that much less time to prepare for a counterattack or conduct follow-on actions. On any 

given day (under the same environmental conditions), the C group was faster than the 

HD group 80% of the time (16 of 20 trial cycles). 

A.5.2.2.3 Movement to LOA Additional Insights

A purely objective evaluation of 14.4 seconds is elusive, but it may possess some 

practical significance on the battlefield that would reduce the survivability of an 

integrated squad. Considering the 12–15 rounds-per-minute sustained rate of fire for 

the M4 and AK-47 rifles, a single enemy fighter would have the opportunity to take two 

to three more well-aimed shots on Marines in an integrated squad than they would on a 

non-integrated squad moving to the LOA. Similarly, the delay degrades Marines' pursuit 

of the enemy by fire, denying the slowest Marines 2 to 3 well-aimed engagements on 

the enemy from a fixed position at the LOA. The resulting trade in casualty exchange 

could be significant.

A.5.2.2.4 Movement to LOA Subjective Comments 

For subjective comments relating to this task, see the 0311 Appendix.

A.5.2.3 Attack and Counterattack (C-Atk) Percent Hits Results

A.5.2.3.1 Attack and C-Atk Percent Hits Overview

This experimental task assessed the accuracy of a rifle squad engaging 12 GTSs during 

a 300-meter fire-and-movement assault. Each GTS captured the precise location of a 

round that impacted a target silhouette using a location-of-hit-and-miss (LOMAH) 

sensor. The GTSs were equally spread over the downrange area at varying distances 

and were exposed according to predetermined parameters consistent for every squad 

attack. The accuracy was determined by dividing the number of hits on each target by 

the total ammunition expended by each squad. 

Figure A-3 displays all Attack & C-Atk Percent Hit data. All data on the scatterplot are 

valid for analysis.
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Figure A-3. Attack and C-Atk Percent Hits

The data are normally distributed, as evidenced by the Shapiro-Wilk test that resulted in 

a p-value of 0.47 for the C group and 0.73 for the HD group.

The C group had an average percent hit of 40%. This proportion is statistically 

significantly higher than the HD average of 36%. This difference results in a 10.40%, or 

4-percentage point, degradation in accuracy. In addition, the HD group has greater 

variability, as shown by the 2-percentage point increase in SD (5% for the C group and 

7% for the HD group). See Table A-2 and Table A-3 for detailed analytical results. 

A.5.2.3.2 Attack and C-Atk Percent Hits Contextual Comments

A.5.2.3.2.1 Attack and C-Atk Percent Hits Contextual Comments Overview

In combat operations, accuracy is highly desirable when destroying or effectively 

suppressing an enemy position. In the execution of this task, the HD group sustained 

an average 10.4% decrement in the percentage of hits for the number of shots taken. 

Operationally, this decrease equates to a degradation of lethality and an increase in 

ammunition expenditure. On any given day (under the same environmental conditions), 

the C group was more accurate than the HD group 85% of the time (17 of 20 trial

cycles).

A.5.2.3.2.2 Analysis by Gender and Weapon System

The use of a Weapons Player Pack (WPP) on each weapon system allowed data to be 

captured on each shot taken by a Marine during the conduct of the attack and C-atk. 

When synchronized with the data obtained from the GTS, a shooter-to-shot correlation 

was possible. For the analysis of shot accuracy, accuracy percentages by gender and 

weapon were analyzed that measured percent hits and percent hits and near misses, 
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where a hit indicates that a round hit the target silhouette and a near miss indicates that 

the LOMAH sensor detected a round within a 1.5 meter detection arc.

Since the accuracy results by gender were collected, a t-test was used for this analysis. 

Table A-4 displays the shot accuracy results by gender and weapon system.

Table A-4. Shot Accuracy by Gender and Weapon System

Probability of Hit Probability of Hit & Near Miss

Weapon F M % 

Difference

2-sided 

p-value F M % Difference

2-sided 

p-value

M4 0311b .28 .42 33% <0.01 .73 .75 3% 0.32

M27 0311c .25 .43 42% <0.01 .58 .69 16% .0144

M16A4/M203 0311c .15 .28 46% <0.01 .50 .67 25% <0.01

M4 PIc .37 .44 16% .0189 .73 .79 8% 0.0341

M27 PI .37 .38 3% .7571 .66 .69 4% .3663

M16A4/M203 PIc .15 .26 42% <0.01 .59 .70 16% 0.0453 a. The M16A4/M203 shot accuracy data is only for 5.56mm ammunition shot from the weapon and does not include 

the 40mm practice round accuracy.

b. Indicates that there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between the percent hits values for the gender. c. Indicates that there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between the percent hits and percent hits and near miss values for the gender.

The shot accuracy by gender and by weapon reveals that there is a statistically 

significant difference between genders for every weapon system within the 0311 

squads, except for the probability of hit/near miss with the M4. The overall accuracy 

declined and the percent difference increased as the weight of the weapon system 

increased. The M4 was the lightest weapon and yielded the most accurate results, 

while the M16A4/M203 was the heaviest weapon and yielded the least accurate results. 

One might think that the experience level of the Marines (male vs. female) influenced 

the results. However, the PI results disprove this conjecture, as the male and female PI 

Marines came to the unit with the same experience level and their performance mirrors 

the results of the 0311 Marines. With the exception of the M27 accuracy, which was not 

statistically significant, the PI accuracy and percent difference declined as the weapon 

got heavier. Furthermore, a close look at the unit-training plan, methodology, 

leadership, and ammunition expended shows that the Marines in the GCEITF were very 

well prepared for this assessment, minimizing the impact of past experience. One could 

conclude that given the same type and amount of training, female Marines will be less 

lethal on the battlefield than male Marines. 

A.5.2.3.3 Attack and C-Atk Percent Hits Additional Insights

To explore the operational effect of a 4-percentage point difference in percentage of 

hits, a Monte Carlo simulation was conducted using the Lanchester Square Law as a 

model of tactical-level engagement. We chose the Lanchester Square Law for 
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rudimentary analysis using a well-known combat model to explore the potential effects 

of the differences discovered between integration levels. (For more information on the 

Lanchester Square Law, see the Methodology Annex, Annex R.) 

There are several important assumptions we make for this Lanchester model in terms of 

parameter selection. We chose parameters that model a worst-case scenario for a 

squad engagement in which the squad faces an equivalent adversary in terms of 

capability. The first assumption is that the force sizes are equal, which is a 12-on-12 

fight. The second assumption is the relative rate of fire between forces; we assume this 

ratio of friendly-to-enemy rate of fire to be equal to 1. Finally, with respect to accuracy, 

the enemy was assumed to be as good as the best experimental group, which was the 

C group. Thus the enemy probability of hit was set at 0.40.

Two hundred thousand simulated engagements were run for the C and HD groups. A 

force won an engagement when its opposition was eliminated. By construct, the C 

group (with a probability of hit equal to the enemy’s, at 0.40) won 50% of the 

engagements, with an average of three Marines remaining. This even-fight case is 

useful only to assess the effect of the HD group’s decrement in probability of hit. In 

another two hundred thousand simulated engagements, the HD group (with a 

probability of hit equal to 0.36) won 46.9% of the engagements, with three Marines 

remaining. The difference in these results represents a 6.2%, or 3.1 percentage point, 

degradation in tactical-level engagement wins.

A.5.2.3.4 Attack and C-Atk Percent Hits Subjective Comments

For subjective comments relating to this task, see the 0311 Appendix.

A.5.2.4 CASEVAC by FT Results

A.5.2.4.1 CASEVAC by FT Overview

This experimental task assessed a fireteam’s ability to move a 220-lb dummy a distance 

of 100 meters to a CCP while wearing a fighting load and individual weapon. Marines 

conducted this task at the conclusion of the squad attack/counterattack. At the 

discretion of each fireteam, Marines used a 2-Marine, 3-Marine, or 4-Marine carry to 

move the casualty. The recorded time started when a member of the fireteam touched 

the dummy, and it stopped when the dummy and all members of the fireteam arrived at 

the CCP.

Figure A-4 displays all CASEVAC by FT data. All data on the scatterplot are valid for 

analysis.
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Figure A-4. CASEVAC by FT

For this task, sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA.

The C group had a mean of 1.46 minutes. This time is statistically significantly faster 

than the HD mean time of 1.57 minutes. This difference results in a 7.63%, or 6.6-

second, degradation in evacuation times between the groups. In addition, the HD group 

has greater variability, as shown by the 0.22 increase in SD (0.25 minutes for the C 

group and 0.47 minutes for the HD group). See Table A-2 and Table A-3 for detailed 

analytical results.

A.5.2.4.2 CASEVAC by FT Contextual Comments

The implications of this task contain relevance to the training and combat environments, 

as survival is dependent upon expeditious movement of the casualty to higher levels of 

care. Based on the standard deviations, the variation in performance of the HD group is 

nearly twice as much as the variation in performance of the C group. This inconsistency 

in the performance of the HD group leads to greater uncertainty and less confidence in 

its future performance from the mean. 

A.5.2.4.3 CASEVAC by FT Additional Insights

While the “Golden Hour” is a common medical battlefield care construct for C2 and 

logistical support, medical literature supports a “Platinum Ten” construct of first 

response. Noting that the majority of casualties die within ten minutes of the trauma, 

the “Platinum Hour” construct holds that a patient needs to be correctly triaged and

moved to medical care as fast as possible; any time degradation will reduce the 

probability of survival. 
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A.5.2.4.4 CASEVAC by FT Subjective Comments

For subjective comments relating to this task, see the 0311 Appendix.

A.5.2.5 Prepare Fighting Positions by FT Results

A.5.2.5.1 Prepare Fighting Positions by FT Overview

This experimental task assessed the amount of earth moved by a fireteam in a 2-hr 

period. Each fireteam was required to dig 2 2-man fighting holes while wearing a 

fighting load and maintaining 50% security (only two Marines were digging at any given 

time). All the earth was scooped into buckets and weighed by a nonassessed Marine. 

The recorded time began 10 minutes after finishing the 7-km hike, and time stopped 2 

hours after beginning to dig. 

Figure A-5 displays all 0311 Prepare Fighting Positions data. All data on the scatterplot 

are valid for analysis.

Figure A-5. Prepare Fighting Positions by FT

For this task, sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA.

The C group moved a mean of 4,284.86 lb. of earth. This amount is greater (but not 

statistically significantly) than the HD group mean of 4,041.81 lb. There is a 5.67%, or 

243.05 lb, degradation between groups. In addition, the HD group has slightly greater

variability, as shown by the 12.01-lb increase in SD (1005.43 lb. for the C group and 

1017.44 lb. for the HD group). See Table A-2 and Table A-3 for detailed analytical 

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A.5.2.5.2 Prepare Fighting Positions by FT Contextual Comments

Marine Corps Warfighting Publication (MCWP) 3-11.2: Marine Rifle Squad specifies the 

dimensions of a 2-person fighting hole: 6-ft long x 2-ft wide x 5-ft deep (assuming 

occupants of height 5 ft. 6 in.–6 ft). The volume of this fighting hole is 60 cu ft. Two 

such holes are required for a fireteam, with a combined volume of 120 cu ft. In 

Engineering Manual 1110-1-1905: Engineering and Design: Bearing Capacity of Soils, 

the Army Corps of Engineers estimates that collapsible soil (of the type found at 

MCAGCC 29 Palms) has an average density of 85 lb/cu ft. Thus a total of 10,200 lbs of 

dirt would have to be moved to construct two fighting positions.

The C group moved earth at a rate of 2,142.43 lb./h. At this rate, the C group would 

have completed digging their fighting holes in 4 hr, 46 min. The HD group moved earth 

at a rate of 2,020.91 lb/h. At this rate, the HD group would have completed digging their 

fighting holes in 5 hr, 3 min. Thus, the HD group would have completed digging their 

fighting holes 17 min later than the C group. 

A.5.2.5.3 Prepare Fighting Positions by FT Additional Insights

Motivation and perspective provided by the platoon leadership was a contributing factor 

to the overall morale and work ethic of each Marine. Leadership and inspiration were 

not explicitly measured in this tactical task, but are thought to have had a larger impact 

than anticipated. The 0311 Platoon leadership was regularly observed sitting as a 

group approximately 50 meters away from their Marines with little interaction during the 

assessment. While the platoon leadership fulfilled their duties during the assessment, 

they did not attempt to maximize the output of their Marines. 

A.5.2.5.4 Prepare Fighting Positions by FT Subjective Comments

For subjective comments relating to this task, see the 0311 Appendix.

A.5.2.6 1-km Hike Results

A.5.2.6.1 1-km Hike Overview

This experimental task assessed a squad of 12 Marines moving approximately 1 km 

while each Marine carried an assault load and individual weapon. Each squad moved 

as quickly as possible to reinforce a notional friendly squad pinned down by enemy fire. 

The recorded time started when the squad departed the assembly area on Range 107, 

and ended upon reaching a designated attack position just prior to the wall obstacle. 

Figure A-6 displays all 0311 1-km hike data. On Trial Cycle 5, the HD group data point 

was removed from analysis as it represents a data outlier. With the exception of this 

point, all data on the scatterplot are valid for analysis.
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Figure A-6. 1-km Hike

The data are normally distributed, as evidenced by the Shapiro-Wilk test that resulted in 

a p-value of 0.49 for the C group and 0.04 for the HD group. 

The C group had a mean of 8.07 minutes. This time is statistically significantly faster in 

a one-sided t-test than the HD mean time of 8.49 minutes. This difference results in a 

5.18%, or 25-second, degradation in hike time. The C group has greater variability, as 

shown by the 0.14-minute increase in SD (0.53 minutes for the C group and 0.39 

minutes for the HD group). See Table A-2 and Table A-3 for detailed analytical results.

A.5.2.6.2 1-km Hike Contextual Comments

The Infantry T&R Manual states that “the maximum assault load weight will be such that 

an average Infantry Marine will be able to conduct combat operations indefinitely with 

minimal degradation in combat effectiveness.” While moving 1 km with the assault load, 

the HD group moved 5.18% slower, making them 25 seconds less responsive to 

reinforcing a unit in contact with the enemy. On any given day (under the same 

environmental conditions), the C group was faster than the HD group 80% of the time 

(16 of 20 trial cycles). 

A.5.2.6.3 1-km Hike Additional Insights

A purely objective evaluation of 25 seconds is elusive but may possess some practical 

significance on the battlefield that would reduce the survivability of a unit waiting on an

integrated squad. Considering the 12–15 rounds-per-minute sustained rate of fire for 

the M4 and AK-47 rifles, a single enemy fighter would have the opportunity to take 3 to 
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4 more well-aimed shots on Marines while waiting for reinforcements from an integrated 

squad. A fireteam of enemy fighters would have the time to call in indirect 82-mm 

mortar fire or maneuver during this time delay. The resulting trade in casualty exchange 

could be significant.

A.5.2.6.4 1-km Hike Subjective Comments

For subjective comments relating to this task, see the 0311 Appendix.

A.5.2.7 Negotiate Obstacle Results

A.5.2.7.1 Negotiate Obstacle Overview

This experimental task assessed the time it took to get a squad of 12 Marines and all 

equipment over an 8-ft ISO Container (wall obstacle). The squad began this task as 

soon as they finished the 1-km movement. The recorded time started when the first 

Marine touched the wall, and time stopped when the last Marine touched both feet down 

on the other side. 

Figure A-7 displays all 0311 Negotiate Obstacle data. On Trial Cycle 1, the C group 

data point was removed from analysis, as it represents a data outlier due to trial 

execution. With the exception of this point, all data on the scatterplot is valid for 

analysis.

Figure A-7. Negotiate Obstacle

The data are normally distributed, as evidenced by the Shapiro-Wilk test that resulted in 

a p-value of 0.75 for the C group and 0.17 for the HD group. 
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The C group had a mean of 2.77 minutes. This time is faster (but not statistically 

significantly) than the HD mean time of 2.92 minutes. There is a 5.33%, or 9-second, 

degradation in time. In addition, the HD group had a greater variability, as shown by the 

0.14-minute increase in SD (0.34 minutes for the C group and 0.48 minutes for the HD 

group). See Table A-2 and Table A-3 for detailed analytical results.

A.5.2.7.2 Negotiate Obstacle Contextual Comments

According to Sun Tzu: “Speed is the essence of war. Take advantage of the enemy’s 

unpreparedness; travel by unexpected routes and strike him where he has taken no 

precautions” (MCDP-1, p. 69). Speed and surprise are crucial to success. The enemy 

is reliably expected to cover obstacles with fires. When possible, obstacles are to be 

avoided. When this is not possible, the obstacles must be negotiated quickly. While no 

purely objective standard can be set for the negotiation of the obstacle presented in this 

task, any decrement in speed translates into increased exposure to enemy fires and 

greater risk for friendly casualties. On any given day (under the same environmental 

conditions), the C group was faster than the HD group 63.2% of the time (12 of 19 trial 

cycles).

A.5.2.7.3 Negotiate Obstacle Additional Insights

Of note, a large discrepancy may be observed when comparing the 0311 obstacle time 

with the Provisional Infantry (PI) obstacle time. This difference can be explained by the 

different techniques used by each group. The 0311 squads provided their own security 

and only used one launch-point up the wall, while the PI squads did not establish 

security and used three launch-points to get over the wall. Each group (0311 and PI) 

was consistent within itself, but the two groups should not be compared with each other. 

A.5.2.7.4 Negotiate Obstacle Subjective Comments

One subtask involved in negotiating the wall included each Marine throwing his or her 

30-lb assault pack up onto the wall. According to leadership observations, females 

were observed needing help throwing packs onto the wall during the majority of trials. 

The record of subjective comments reveals 8 occasions in which females required 

assistance getting their packs onto the wall, compared with zero documented instances 

of males requiring assistance. For additional subjective comments relating to this task, 

see the 0311 Appendix.

A.6 Statistical Modeling Results 

A.6.1 Statistical Modeling Results Overview

The previous section discussed results only as they pertain to differences due to 

integration level alone. The goal of statistical modeling, as applied here, is to estimate 

simultaneously the effect of gender integration levels and other relevant variables on 
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squad performance. (Refer to the Methodology Annex for a broad overview of the 

analysis plan and the variables used in the models.) 

For the same seven selected tasks described in the previous section, this section 

presents an overview of the analysis and results, and then presents the modeling 

results for each of the tasks.

For each task, we describe the significant variables in the model and whether these 

variables are either positively or negatively correlated with the result. A negative 

correlation indicates that an increase in that variable will result in a decrease in the 

response variable, which is a desired outcome for elapsed time but not a desired 

outcome for the percent hits or pounds of earth moved outcome. The results indicate 

where certain patch numbers are significant for a given variable. The experiment 

tracked Marines within the rifle squad by a patch number that associated their random 

position within the squad to a specific billet. Table A-5 displays the patch numbers and 

associated billet titles for the rifle squad.

Table A-5. Patch Numbers and Billet Titles for the Rifle Squad

Patch Number Billet Title

1 FT 1 Fireteam Leader

2 FT 1 Automatic Rifleman

3 FT 1 Grenadier

4 FT 1 Rifleman

5 FT 2 Fireteam Leader

6 FT 2 Automatic Rifleman

7 FT 2 Grenadier

8 FT 2 Rifleman

9 FT 3 Fireteam Leader

10 FT 3 Automatic Rifleman

11 FT 3 Grenadier

12 FT 3 Rifleman

A.6.2 Mean Value Imputation

Because the personnel data were not available for one volunteer, we impute this 

Marine’s information from all other male volunteers who completed the experiment. A 

mean value imputation method was used for each measurement using only male 

volunteers who completed the entire Twentynine Palms portion of the experiment.
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A.6.3 0311 Selected Tasks Method of Analysis

Because there are more volunteers than trials for any given 0311 task, a mixed-effects 

model does not work for the 0311 dataset. Therefore, we model the 0311 selected 

tasks using ordinary least squares regression. 

For the majority of each of the primary metrics for the rifle squad, there are only 41 

observations for each result. Because there are 12 Marines in a rifle squad and so few 

results, the regression model does not have a sufficient number of degrees of freedom 

to create a model using all types of personnel data for each squad member for each 

result. Thus each variable combined with integration level is modeled separately. For 

example, age for each member of the rifle squad (12 variables) and integration level are 

modeled with the result (response time, percentage hits, or pounds of earth moved) as 

the response variable. Where possible, a backward stepwise regression using AIC

determined which variables are optimal in the model. If there were missing values, 

backward stepwise could not run, and significant variables are reported based on pvalues from the overall model.

A.6.4 0311 Selected Tasks Overall Modeling Results

There are no personnel data variables that are both statistically significant and have a 

practical impact to the model. Each time personnel data variables are statistically 

significant in a model, their effects are practically negligible, conflicting, and/or 

incomplete for the squad (i.e., there are no tasks for which a variable is significant for 

all, or even most members of the rifle squad). 

Integration level, however, consistently appears as statistically significant in each task, 

and its effect is clear, causal, and practical. Therefore, integration level is the best 

variable to describe performance for each task. Refer to the section A.5 for the ANOVA 

summary for each 0311 task mentioned below. 

A.6.4.1 7-km Hike 

We model elapsed time for the 7-km hike as a function of each personnel variable and 

integration level in a separate model. The covariates in each model are the values of 

each personnel variable for each patch number. For each model, we report statistically 

significant positive and negative correlations, and whether we observe any patterns.

The models for the following variables do not run due to missing values: 

• GT score

• PFT crunches

• PFT 3-mile run. 

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 
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• Age

• Height

• Weight 

• AFQT score

• Rifle score. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the 7-km hike time: 

• CFT MTC of patches 2, 4, and 9

• CFT MANUF of patches 9 and 12

• Rifle score of patch 11. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the 7-km hike time: 

• Age of patches 1 and 6

• Height of patches 10 and 11

• AFQT score of patch 7

• CFT MTC of patches 5 and 10

• Rifle score of patch 5. 

The following personnel variables have no significant variables in their respective 

models:

• None. 

There are no patterns for any personnel variables for the 7-km hike. See section 

A.5.2.1 for the ANOVA summary of this task.

A.6.4.2 Movement to LOA 

We model elapsed time for the movement to LOA as a function of each personnel 

variable and integration level in a separate model. The covariates in each model are 

the values of each personnel variable for each patch number. For each model, we 

report statistically significant positive and negative correlations and whether we observe 

any patterns.
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The models for the following variables do not run due to missing values: 

• GT score

• PFT 3-mile run. 

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Age

• Height

• Weight

• AFQT score 

• CFT MANUF

• PFT crunches

• Rifle score. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the movement to LOA time: 

• Age of patch 2

• Height of patch 5

• Weight of patches 4, 5, and 10

• CFT MTC of patch 8

• CFT MANUF of patches 1 and 8. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the movement to LOA time: 

• Age of patches 7, 9, and 11

• Height of patches 9 and 12

• Weight of patches 3, 11, and 12

• AFQT score of patch 9

• CFT MTC of patches 4, 9, and 12

• CFT MANUF of patches 3 and 10.
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The following personnel variables have no significant variables in their respective 

models:

• None. 

There are no patterns for any personnel variables for the movement to LOA time. See 

section A.5.2.2 A.5.2.1for the ANOVA summary of this task.

A.6.4.3 Attack & C-Atk Percent Hits

We model the attack & c-atk percent hits as a function of each personnel variable and 

integration level in a separate model. The covariates in each model are the values of 

each personnel variable for each patch number. For each model, we report statistically 

significant positive and negative correlations and whether we observe any patterns.

The models for the following variables do not run due to missing values: 

• GT score

• PFT 3-mile run. 

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Age

• Height

• Weight

• AFQT score

• CFT MTC

• CFT MANUF

• Rifle Score. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the attack and c-atk percent hits: 

• Age of patches 6 and 12

• Height of patch 10 

• AFQT score of patches 3, 7, and 10

• CFT MTC of patches 2 and 6
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• CFT MANUF of patches 1 and 2

• Rifle score of patches 4 and 10. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the attack and c-atk percent hits: 

• Age of patches 4 and 5 

• Height of patch 8 

• Weight of patches 4, 8 and 12 

• AFQT score of patches 4 and 6

• CFT MTC of patch 9

• CFT MANUF of patch 9. 

The following personnel variables have no significant variables in their respective 

models:

• PFT crunches. 

There are no patterns for any personnel variables for the attack and c-atk percent hits. 

See section A.5.2.3 for the ANOVA summary of this task.

A.6.4.4 CASEVAC by FT

We model elapsed time for the CASEVAC as a function of each personnel variable and 

integration level in a separate model. The covariates in each model are the values of 

each personnel variable for each patch number. For each model, we report statistically 

significant positive and negative correlations and whether we observe any patterns.

The models for the following variables do not run due to missing values: 

• None. 

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Age

• Height

• Weight

• AFQT score 

• PFT crunches 

• PFT three-mile run 

• Rifle score. 
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The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the CASEVAC time: 

• Age of patch 2 

• GT score of patch 1 

• CFT MANUF of patches 3 and 4 

• PFT crunches of patch 2. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the CASEVAC time: 

• Age of patch 4 

• PFT crunches of patch 1

• Rifle score of patch 3. 

The following personnel variables have no significant variables in their respective 

models:

• CFT MTC. 

There are no patterns for any personnel variables for the CASEVAC time. See section 

A.5.2.4 for the ANOVA summary of this task.

A.6.4.5 Prepare Fighting Positions by FT

We model the amount of earth moved to prepare a fighting position as a function of 

each personnel variable and integration level in a separate model. The covariates in 

each model are the values of each personnel variable for each patch number. For each 

model, we report any statistically significant positive and negative correlations and 

whether we observe any patterns. 

The models for the following variables do not run due to missing values: 

• None. 

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• None. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 
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• Weight 

• PFT crunches 

• PFT 3-mile run. 

The following personnel variables are significant in their respective models and are 

positively correlated with the amount of earth moved for the defensive position: 

• Age of patch 4 

• AFQT score of patch 4 

• GT score of patches 1 and 3

• Rifle score of patch 1. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the amount of earth moved for the defensive position: 

• CFT MTC of patches 2 and 4 

• CFT MANUF of patches 3 and 4. 

The following personnel variables have no significant variables in their respective 

models:

• Height. 

There are no patterns for any personnel variables for the amount of earth moved to 

prepare a fighting position. See section A.5.2.5 for the ANOVA summary of this task.

A.6.4.6 1-km Hike

We model elapsed time for 1-km hike a function of each personnel variable and 

integration level in a separate model. The covariates in each model are the values of 

each personnel variable for each patch number. For each model, we report any

statistically significant positive and negative correlations and whether we observe any 

patterns.

The models for the following variables do not run due to missing values: 

• GT score

• PFT three-mile run. 

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Age

• Height 
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• Weight 

• AFQT score

• Rifle score. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the 1-km hike time: 

• Age of patch 2 

• Height of patches 5, 8, 9, and 10 

• Weight of patch 7 

• AFQT score of patches 1, 5, and 11 

• CFT MTC of patch 6 

• Rifle score of patch 12. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the 1-km hike time: 

• Age of patches 6, 8, and 9 

• Height of patches 3 and 6 

• AFQT score of patches 3, 7, and 10 

• Rifle score of patches 3, 8, and 10. 

The following personnel variables have no significant variables in their respective 

models:

• CFT MANUF

• PFT crunches. 

There are no patterns for any personnel variables for the 1-km hike time. See section 

A.5.2.6 for the ANOVA summary of this task.

A.6.4.7 Negotiate Obstacle

We model elapsed time for the negotiate obstacle of each personnel variable and 

integration level in a separate model. The covariates in each model are the values of 

each personnel variable for each patch number. For each model, we report statistically 

significant positive and negative correlations and whether we observe any patterns.
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The models for the following variables do not run due to missing values: 

• GT score

• PFT 3-mile run. 

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Age 

• Height 

• Weight 

• Rifle score. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the negotiate obstacle time: 

• Age of patch 6 

• Height of patches 4 and 11, 

• Weight of patches 2, 4, and 5 

• AFQT score of patch 5 

• CFT MTC of patches 3, 4, 8, and 11 

• CFT MANUF of patches 6 and 11 

• Rifle score of patches 1, 5, 10, and 12. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the negotiate obstacle time: 

• Height of patches 7 and 9 

• Weight of patch 9 

• CFT MTC of patches 5, 9, 10, and 12 

• CFT MANUF of patch 2

• Rifle score of patches 2 and 11. 

The following personnel variables have no significant variables in their respective 

models:
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• PFT crunches. 

There are no patterns for any personnel variables for the negotiate obstacle time. See 

section A.5.2.7 for the ANOVA summary of this task.
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Appendix to Annex A

0311 Supplemental Information

This appendix provides supplemental information for the 0311 portion of the GCEITF

experiment. It provides information regarding the GCEITF leadership subjective 

comments and additional descriptive and basic inferential statistics not described in 

Annex A.

Section 1. GCEITF Leadership Subjective Comments

The GCEITF leadership provided comments on their observations of the experiment 

throughout it execution. Table A A displays a summary of these comments broken 

down by task, integration level, gender, and type of comment.

Table A A – Summary of GCEITF Leadership Comments

Section 2. Additional Task Basic and Inferential Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. The experiment included a number of tasks and associated metrics 

conducted to enhance operational realism and maintain consistent application of the 

experimental process. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

This section presents results for nine additional 0311 tasks. Annex A contains the 

descriptive statistics for the remainder of the 0311 tasks. The words “metric” and “task” 

are used interchangeably throughout this Appendix. They both refer to the experimental 

task. 

Task and Metric 

Description Gender Total

C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total

M 9 7 16 5 2 7 1 0 1 6 0 6 2 0 2 0 0 0 1 1 2 1 0 1 35

F 0 10 10 0 2 2 0 2 2 0 1 1 0 0 0 0 1 1 0 0 0 0 0 0 16

M 16 5 21 0 0 0 3 5 8 4 1 5 0 0 0 0 0 0 0 1 1 0 0 0 35

F 0 8 8 0 0 0 0 11 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19

M 0 0 0 0 0 0 0 1 1 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 4

F 0 1 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 2

M 1 1 2 0 0 0 0 0 0 4 0 4 0 0 0 0 0 0 0 0 0 0 0 0 6

F 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

M 1 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2

F 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

M 0 0 0 0 0 0 0 0 0 11 1 12 0 2 2 0 0 0 0 1 1 0 0 0 15

F 0 0 0 0 0 0 0 5 5 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 6

Prepare Fighting Positions

1-km Hike

Negotiate Obstacle

CASEVAC to CCP

7-km Hike

Movement to LOA

Other No category

Falling 

behind/slowing 

movement

Requesting extra 

breaks

Requires extra 

assistance

Needs no 

assistance

Compensating 

for another 

Marine

Gear pass off
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The two tables below display the results for nine additional 0311 metrics. Table A B

displays the metrics and integration levels with their respective sample sizes, means, 

standard deviations, and percent difference between integration levels. 

Table A C displays ANOVA results, including metrics and integration levels, and pvalues suggesting statistical significance. For each task, an ANOVA and t-test were 

conducted to compare the two groups. If p-values are less than the a-priori determined 

significance level of 0.10, we conclude that there is statistical evidence that the 

response for the HD group is different from that in the C group. We present basic 

inferential statistics for two tasks.

Table A B. 0311 Test Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference 

(HD-C)

7-km Hike; first km C 17 10.08 0.41 0.43% HD 18 10.13 0.59

7-km Hike; second km

C 16 10.21 0.43 0.21% HD 18 10.24 0.40

7-km Hike; third km

C 16 9.74 0.35

1.51% HD 19 9.89 0.64

7-km Hike; fourth km C 16 10.26 0.45 1.85% HD 19 10.45 0.63

7-km Hike; fifth km C 16 11.14 0.52 3.84% HD 19 11.57 0.51

7-km Hike; sixth km

C 16 12.38 1.70

8.00% HD 19 13.37 2.05

7-km Hike; seventh km

C 16 11.90 0.63 3.37% HD 19 12.30 0.65

Attack (Hits on Target) C 20 546.40 79.3 -8.95% HD 21 497.48 101.40

C-Atk (Hits on Target)

C 20 74.15 31.06 -18.25% HD 21 60.62 25.07

Table A C. 0311 ANOVA Results and Welch’s T-Test Results

Metric

F 

statistic 

(df)

F Test

PvalueComparison 2-sided 

P-Value

1-sided 

P-Value

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Attack (hits on 

target)*

2.94

(1, 39) 0.09* HD-C 0.09* 0.05* -85.91 -11.94 -96.74 -1.11

C-Atk (Hits on 

Target)*

2.37

(1, 39) 0.13 HD-C 0.13 0.07* -25.07 -1.99 -28.45 1.39

*Indicates there is a statistically significant difference, in either a one-sided or two-sided 

hypothesis test, between integration levels according to ANOVA.
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Additional Task Results: 

7-km Hike by km. The general trend for the 7-km hike was that the difference between 

the HD and C groups increased over the course of the hike.

Attack (hits on target). The data are normally distributed, as evidenced by the 

Shapiro-Wilk Test that resulted in a p-value of 0.47 for the C group and 0.84 for the HD 

group.

The C group had a mean of 546.40 hits on targets. This number is statistically 

significantly higher than the HD group mean of 497.48 hits. The HD group produced 

8.95% fewer hits. 

• Contextual Comments. The ability to effectively engage enemy targets on the 

battlefield is the hallmark of the Marine rifleman. The number of hits scored by 

the C group squads was consistently greater than those scored by the HD 

groups. The operational effect of this is obvious: more hits equates to greater

enemy casualties, which means less chance of being hit by the enemy. On any 

day, under the same conditions, the C group scored more hits than the HD group 

80% (16 of 20 trial cycles) of the time. 

Counterattack (hits on target). The data are normally distributed, as evidenced by the 

Shapiro-Wilk Test that resulted in a p-value of 0.99 for the C group and 0.21 for the HD 

group.

The C group had a mean of 74.15 hits on targets. This number is statistically 

significantly higher than the HD group mean of 60.62 hits. The HD group produced 

18.25% fewer hits. 

• Contextual Comments. This event produced extremely variable results for both 

squad types. The C groups produced a high of approximately 135 hits and a low 

of about 15. The HD group results ranged between about 25 and 100. This was 

at least in part a function of the number of rounds each squad had remaining 

after the “attack” event. Since the number of rounds remaining after the attack 

was a random variable, not controlled for in any way, the results of this event 

cannot be used to meaningfully differentiate the performance of the squad types. 

On any day, under the same conditions, the C group scored more hits than the 

HD group 55% (11 of 20 trial cycles) of the time.
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Annex B. 

Light Armored Reconnaissance (MOS 0313) 

This annex details the Light Armored Reconnaissance Vehicle Crewman (MOS 0313) 

portion of the Ground Combat Element Integrated Task Force (GCEITF) experiment 

executed from 3 March – 4 May 2015 at Range 500, aboard the Marine Corps Air 

Ground Combat Center (MCAGCC), Twentynine Palms, CA. The sections outline the 

Light Armored Vehicle (LAV) Crewman Scheme of Maneuver, Limitations, Deviations,

Dataset Description, Descriptive and Basic Inferential Statistics, and Modeling Results.

B.1 Scheme of Maneuver

B.1.1 Experimental Cycle Overview

The LAV Crewmen (MOS 0313) were assessed in a field environment aboard 

MCAGCC, Twentynine Palms, CA. This timeline included 2 pilot trial cycles, 16 record 

test cycles, and 3 makeup test cycles. One cycle was equivalent to a 3-day period 

which included a live-fire day, non-live-fire day and a maintenance day. The record test 

was conducted as planned from 9 March through 1 May 2015. One makeup test cycle 

was required. A range maintenance day was conducted every four cycles (12 days) to 

allow contractor support to conduct range and targetry upkeep, and allowed the Marine 

volunteers to receive 1 recovery day spent at Camp Wilson. The evaluated subtasks 

within the cycle were considered the most physically demanding and operationally 

relevant tasks that a junior 0313 LAV crewman would perform on a recurring basis. An 

LAV-25 crew is made up of three Marines: a Vehicle Commander (VC), Gunner, and 

Driver. For each trial, male and female volunteers rotated through the role of gunner 

and driver on the vehicle; due to required experience, the five VCs remained in their 

billet throughout the duration of the experiment. The assessment was executed under 

the supervision of MCOTEA Light Armored Reconnaissance (LAR) Functional Test 

Manager and a range OIC/RSO from the GCEITF. 

B.1.2 Experimental Details

The members of the LAR experiment executed a variety of subtasks over the course of 

a 3-day trial cycle. The first day consisted of non-live-fire, maintenance-evaluated 

subtasks divided into three categories: casualty evacuation (CASEVAC) actions, vehicle 

recovery operations, and maintenance actions. The second day consisted of live-fire 

evaluated subtasks divided into two categories: prepare for combat actions and main 

gun target engagements. The third day of the trial cycle consisted of non-evaluated 

maintenance tasks meant to keep the vehicles and equipment combat ready to continue 

to execute subsequent trial cycles. Initial Fatigue surveys were given to each volunteer 
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at the beginning of each experimental day, followed by a final Fatigue survey at the 

completion of that particular day’s tasks. Workload surveys were administered 

immediately following certain specified tasks. Lastly, volunteers completed cohesion 

surveys at the end of each trial cycle. For survey instruments, see the GCEITF EAP 

Annexes D and M.

B.1.3 Additional Context

Prior to any trial day with observed subtasks, the Marines bivouacked at a platoon 

position on their LAVs. On maintenance days, Marines bivouacked in a permanent 

structure at Range 500. Most subtasks had a maximum time allowed for completion. If 

a crew exceeded the maximum time allowed, they completed the trial and the time was 

recorded, but the subtask was flagged as a unit failure. This ensured that all data from 

the trial and subtask was collected and recorded. All volunteers not randomly selected 

to participate on a particular day’s trials conducted additional tasks outside the 

assessed events to provide realistic loading. The additional tasks were equivalency 

tasks to ensure equity between individuals participating in a trial cycle and those not 

chosen via random selection. These tasks are discussed in detail in the loading section 

below.

Fatigue surveys were designed to capture the volunteers’ cumulative fatigue level at the 

beginning and end of each day’s trials. The data collected provide additional insight into 

apparent aberrations in the performance level of a given volunteer on a specific day. It 

allows for outside fatigue-related factors (minor illness, lack of sleep the night before, 

etc.) to be accounted for in the analysis of the performance data. Workload surveys 

collected the volunteers’ perceived average and maximal level of exertion during the 

performance specified tasks. Cohesion surveys provided a method of collecting 

subjective data relating to each Tank crew’s ability to work as a team and their overall 

perspective on the cohesiveness of the crew.

B.1.4 Scheme of Maneuver Experimental Tasks

B.1.4.1 Conduct Crew / CASEVAC

The CASEVAC portion of the non-live-fire trial day consisted of two separate subtasks: 

conduct crew evacuation and conduct CASEVAC. Prior to start of the subtasks, each 

vehicle crewman completed a baseline fatigue survey. Subtasks were conducted as a 

crew event, and evaluated on the overall time required to evacuate the vehicle and 

move to a rally point 25 meters away. LAV-25 crews had 9 minutes to complete each 

task. An initial Fatigue survey was given to each volunteer prior to the beginning of this 

task. 
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B.1.4.1.1 Conduct Crew Evacuation

All crewmen (VC, Gunner, and Driver) were required to exit the vehicle safely and move 

as a crew to the rally point 25 meters away. Marines wore fighting loads and carried 

individual weapons, as would be expected when evacuating a vehicle in a tactical 

environment. Although the crew evacuation subtask was not as physically demanding 

as extracting a casualty from an LAV-25 turret, the ability to evacuate a vehicle quickly 

is important in the event of a vehicle fire or other life-threatening issue. 

B.1.4.1.2 Conduct Casualty Evacuation

This event required the LAV-25 Gunner and Driver to extract a combat-loaded test 

dummy and its associated protective equipment, weighing 204 lb, from the vehicle and 

move it to a rally point 25 meters away. This weight was derived from the average 

weight of a male Marine wearing a standard, vehicle fighting load. The casualty 

simulated an incapacitated VC, leaving the two remaining crewmen to conduct the 

evacuation. The crewmen evacuated the dummy from the VC’s station by extracting it 

from the turret and placing it on the front of the vehicle, then moving the simulated 

casualty to the rally point. The subtask also simulated the arrival and aid of another 

LAV-25 crew or scouts from a supplementary position to assist in the CASEVAC. This 

was accomplished by the VC assisting in the evacuation after 6 minutes. Evacuating 

the dummy from the turret is the most difficult form of evacuation a crew faces in a 

tactical environment should the vehicle suffer damage that prevents normal turret 

operations. 

B.1.4.2 Vehicle Recovery and Tow Operations

The vehicle recovery portion of the non-live-fire trial day consisted of two separate 

subtasks: rig for recovery and rig for tow. All tasks were conducted as a crew event. 

Crews had varying times to finish each subtask and wore personal protective 

equipment. 

B.1.4.2.1 Rig for Recovery

This subtask required the LAV-25 crew to use the winch mounted on the vehicle’s front 

and the side-mounted snatch blocks of the LAV-25 and the LAV Logistics Variant 

(LAV-L). With the vehicles spaced 10 m apart, the crewmen paid out the winch cable 

and used the two snatch blocks, each weighing 75 lb, to create a three-point recovery 

system with the shackles and tow-points of the vehicles. An LAV mechanic inspected 

the equipment to ensure it was properly constructed and that the crew followed all 

necessary safety requirements. Upon verification, the crew then detached and stowed

all materials. The subtask was complete when all tools and equipment were returned to 

their proper locations. The crew had 25 minutes to accomplish this task. The ability to 

quickly recover a mired vehicle is an important skill that all crewmen must possess. A 
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three-point recovery system is used often, as it only requires two vehicles to establish 

and can be accomplished fairly quickly. A workload survey was administered 

immediately following this task to measure the average and maximum workload 

experienced by each volunteer.

B.1.4.2.2 Rig for Tow

This subtask required the LAV-25 crew to use the tow bar, weighing approximately 

175 lb., located on the side of the LAV-L. With the two vehicles spaced 10 meters

apart, the crewmen detached the tow bar from the LAV-L and connected it to the tow 

points on the LAV-25. They then ground guided the LAV-L and, with one crewman 

holding the tow bar, attached the eye of the tow bar to the tow pintle of the LAV-L. An 

LAV mechanic inspected the equipment to ensure it was properly constructed and that 

the crew followed all necessary safety requirements. Upon verification, the crew then 

detached and stowed all materials. The subtask was complete when all tools and 

equipment were returned to their proper locations. The crew had 35 minutes to 

accomplish this task. Marines completed workload surveys at completion. Vehicles will 

often break down, either due to mechanical issues or enemy action, and the ability to rig 

a vehicle for towing, quickly, directly affects combat effectiveness. A workload survey 

was administered immediately following this task to measure the average and maximum 

workload experienced by each volunteer.

B.1.4.3 Conduct Maintenance Actions

The maintenance actions portion of the non-live-fire trial day consisted of three separate 

subtasks: remove scout hatch armor, remove side panel armor, and change a tire. All 

tasks were conducted as a crew event. Prior to the start of each maintenance subtask, 

Marines completed a mid-trial fatigue survey. Crews had varying times to finish each 

subtask, and wore personal protective equipment throughout. Each task was evaluated 

on the time to reach the mid-point of the task and the overall time to completion. 

B.1.4.3.1 Mount/Remove Scout Hatch Armor

The vehicle crew used the tools and equipment (SL-3) associated with the LAV-25 to 

remove each armor panel mounted on the back hatches. Each panel is a solid piece of 

composite armor weighing approximately 125 lb. The crew dropped and remounted

one hatch panel, followed by the second. The crew had 30 minutes to accomplish this 

task. Marines completed workload surveys at completion. Removing armor panels, 

while not conducted as regularly as other maintenance actions, is required when the 

panels are damaged or during wash-downs and cleaning after extended operations. A 

workload survey was administered immediately following this task to measure the 

average and maximum workload experienced by each volunteer.
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B.1.4.3.2 Mount/Remove Side-Panel Armor

The vehicle crew used the SL-3 associated with the LAV-25 to remove the front-most 

armor panels, mounted on the left and right sides. Each panel is a solid piece of 

composite armor weighing approximately 60 lb. The crew dropped and remounted one 

panel, followed by the second. The crew had 20 minutes to accomplish this task. 

Marines completed workload surveys at completion. Removing armor panels, while not 

conducted as regularly as other maintenance actions, is required when the panels are

damaged or during wash-downs and cleaning after extended operations. A workload 

survey was administered immediately following this task to measure the average and 

maximum workload experienced by each volunteer.

B.1.4.3.3 Mount/Remove Spare Tire

The vehicle crew used the SL-3 associated with the LAV-25 to remove a tire, weighing 

approximately 200 lb, and mount the spare. For the first half of the subtask, the crew 

jacked up the vehicle, removed a vehicle tire, mounted the vehicle’s spare tire, and 

tightened the lug nuts. The crew then removed the spare tire, mounted the original tire, 

tightened the lug nuts, and returned the spare tire and all additional equipment to the 

proper location. The crew manually lifted the spare tire from the ground to its mounting 

bracket on the side of the LAV-25. The crew had 40 minutes to accomplish this task. 

After completion, Marines completed a post-trial fatigue and a post-trial workload 

survey. The ability to rapidly change a tire has critical implications to ensuring mission 

accomplishment. Depending on the terrain, it would not be unusual for a vehicle crew 

to change multiple tires throughout the course of an operation. A workload survey was 

administered immediately following this task to measure the average and maximum 

workload experienced by each volunteer. Additionally, a final Fatigue survey was 

administered at the end of this task. 

B.1.4.4 Prepare LAV for Combat

The preparation for combat actions portion of the live-fire trial day consisted of six 

separate subtasks, as discussed below. Prior to the start of the subtasks, each vehicle 

crewman completed a baseline fatigue survey. After completion of each subtask, 

Marines completed a mid-trial workload survey. Many of the tasks were conducted as 

an individual Gunner event that afforded assistance, if required, while some were crew 

events. Crews had varying times to finish each subtask, and wore personal protective 

equipment throughout. With the exception of load and stow ammunition, each task was 

evaluated on the time to reach the mid-point of the task and the overall time to 

completion. 
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B.1.4.4.1 Prepare the M240 Coax

This subtask required the LAV-25 Gunner, without assistance, to remove, disassemble, 

reassemble, and install the M240 coaxially mounted machine gun. Disassembly was 

achieved when the Gunner removed the bolt assembly from the weapon system. The 

Gunner had 15 minutes to accomplish this task. The ability to rapidly troubleshoot and 

correct issues within the turret is a critical skill for LAV Gunners. As the very basis of 

their role on a vehicle crew, a Gunner must rapidly accomplish any task involving the 

LAV-25’s weapons systems. An initial Fatigue survey was given to each volunteer at 

the beginning of this task since it was the first task of an experimental day. Additionally, 

a workload survey was administered to measure the average and maximum workload 

experienced by each volunteer.

B.1.4.4.2 Manually Traverse and Elevate the LAV-25 Turret

This subtask required the LAV-25 Gunner, without assistance, to manually traverse, 

elevate, and depress the vehicle turret. The Gunner used the manual traverse and 

elevation controls within the turret to accomplish the subtask. The Gunner manually 

traversed the turret 180 degrees from vehicle centerline. The Marine then elevated the 

barrel until the M240 Coax barrel was even with the barrel of the VC’s M240B. The 

Gunner then depressed the barrel until it touched the rear of the vehicle and returned it 

to center. Finally, the Gunner traversed the turret 180 degrees back to its original 

starting location. The Gunner had 5 minutes to accomplish this task. In the event of 

power loss within the turret, a Gunner must rapidly manipulate the turret to acquire and 

engage targets. This skill is regularly assessed with manual engagements during table 

qualification gunnery. A workload survey was administered immediately following this 

task to measure the average and maximum workload experienced by each volunteer.

B.1.4.4.3 Prepare the M242 Main Gun

This subtask required the LAV-25 Gunner, without assistance, to remove, disassemble, 

reassemble, and install the M242 Bushmaster Cannon, weighing approximately 263 lb. 

The Driver was permitted to assist the Gunner after 30 minutes had elapsed. 

Disassembly was achieved when the Gunner disassembled the bolt and track assembly 

and removed the barrel from the weapon system. The Gunner and Driver had 45 

minutes to accomplish this task. In many situations, other crewmembers will be 

unavailable to assist the Gunner in manipulation and troubleshooting of the main gun. 

The Gunner must rapidly troubleshoot the primary weapon system of the platform. A 

workload survey was administered immediately following this task to measure the 

average and maximum workload experienced by each volunteer.
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B.1.4.4.4 Load and Stow Additional Ammunition

This subtask required the LAV-25 crew to load and stow a full complement of 25-mm 

ammunition into the vehicle. An LAV-25 can hold 150 rounds of High Explosive (HE) 

and 60 rounds of Armor Piercing (AP) ammunition, linked and prepared in the vehicle’s 

HE and AP ready-boxes. Two more uploads of each ammo type is stored within the 

vehicle in their original cans, for a total of 180 AP and 450 HE rounds. Dummy rounds 

weighing just over a pound each were used to simulate the linked rounds. These 

dummy rounds were broken out of their containers and linked prior to the start of the 

subtask. Ten cans of HE training rounds, each weighing 50 lb, and four cans of AP 

training rounds each weighing 55 lb were used. The crew had 20 minutes to 

accomplish this task. Without assistance, a crew must load and stow their ready rounds 

and additional uploads on their vehicle as part of normal combat preparation. A 

workload survey was administered immediately following this task to measure the 

average and maximum workload experienced by each volunteer. 

B.1.4.4.5 Upload the M242 Main Gun

This subtask required the LAV-25 crew to upload the HE and AP rounds from their 

respective ready-boxes into the M242 main gun. This was accomplished by ratcheting 

the rounds from the ready box, through the gun’s feed chutes, and into the feeder 

assembly on the gun. The AP ready-box is located near the Driver, while the HE readybox is located next to the Gunner. The crew had 20 minutes to accomplish this task. 

Without assistance, a crew must upload their weapons systems as part of normal 

combat preparation. A workload survey was administered immediately following this 

task to measure the average and maximum workload experienced by each volunteer.

B.1.4.4.6 Upload the M240 Coax

This subtask required the LAV-25 Gunner, without assistance, to upload a belt of 200 

7.62-mm rounds from coax ready box into the M240 coaxially mounted machine gun. 

This was accomplished by feeding the rounds through the feed chute that extends 

across the turret and onto the feed tray of the M240 coax. The Gunner had 10 minutes 

to accomplish this task. Without assistance, a crew must upload their weapons systems 

as part of normal combat preparation. A workload survey was administered 

immediately following this task to measure the average and maximum workload 

experienced by each volunteer.

B.1.4.5 Engage Main Gun Targets

The main gun engagement portion of the live-fire trial day consisted of five separate 

subtasks, as discussed below. All tasks were conducted as crew events. Crews had 

varying times to finish each subtask, and wore their vehicle fighting load throughout. 
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Live-fire engagements were adapted from table VI gunnery qualification engagements, 

which all vehicle crews are required to fire to achieve qualified status. 

B.1.4.5.1 Gunner’s Defensive Engagement 1

The first live-fire engagement was conducted from a defensive battle position. The 

crews engaged two vehicle targets, one with AP and one with HE ammunition. The 

time to engage each target and number of bursts required to kill each target was 

recorded. An LAV Crew Evaluator (LCE) observed and completed an LCE form, which 

is a standard LAV gunnery template that evaluates a crew’s performance based on 

exposure times, fire commands, correct engagement procedures, and other metrics. 

Live-fire engagements were adapted from table VI gunnery qualification engagements.

B.1.4.5.2 Gunner’s Offensive Engagement 1

The first live-fire offensive engagement was conducted on the move through a 

maneuver box. The crews engaged one vehicle target with the LAV-25 main gun and a 

bank of troop targets with the coaxially mounted machine gun. The time to engage 

each target and number of bursts required to kill the main gun target was recorded. An 

LCE observed and completed an LCE form. Live-fire engagements were adapted from 

table VI gunnery qualification engagements.

B.1.4.5.3 Main Gun Remedial Action

This subtask required the LAV-25 Gunner, with assistance from the VC and Driver, to 

conduct remedial action on the main gun. The crew downloaded the ammunition from 

the main gun, removed the feeder assembly and ensured it was correctly timed, and 

then reinstalled and uploaded ammunition. A data collector recorded the time required 

to disassemble and reassemble the weapon system, and the overall time required to 

complete the subtask, as well as the nature of the assistance provided by the Driver and 

VC. Disassembly was achieved when the Gunner removed the feeder assembly from 

the weapon system. The vehicle crew had 40 minutes to accomplish this task. This 

task simulates a misfire on the main gun, and the actions that the crew would take to 

get their vehicle back in the fight.

B.1.4.5.4 Gunner’s Defensive Manual Engagement 2

The second live-fire defensive engagement was conducted from a defensive battle 

position. This engagement required the gunner to use AP ammunition to engage a 

vehicle target without turret power. The Gunner used the manual traverse and elevation 

controls within the turret to acquire and destroy the target. The time to engage the 

target and number of bursts required to kill the target was recorded. An LCE observed 

and completed an LCE form. Live-fire engagements were adapted from table VI 

gunnery qualification engagements.
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B.1.4.5.5 Gunner’s Offensive Engagement 2

The second live-fire offensive engagement was conducted on the move through a 

maneuver box as a retrograde engagement. With the turret oriented over the rear end 

of the vehicle, the crews engaged one vehicle target with the LAV-25 main gun and a 

bank of troop targets with the coaxially mounted machine gun. The time to engage 

each target and number of bursts required to kill the main gun target was recorded. An 

LCE observed and completed an LCE form. Live-fire engagements were adapted from 

table VI gunnery qualification engagements. After completion of this task, Marines 

completed a post-trial fatigue, a post-trial workload survey, and a crew cohesion survey. 

B.1.5 Loading Events

The loading events ensured, to the greatest extent possible, equity of physical activity 

among all volunteers, and attempted to simulate the intense physical and mental 

workload present in combat or in a combat-focused training environment. Loading 

activities included nightly security and observation posts, maintenance actions, and 

execution of all subtasks to ensure equitable effort. The first enduring task was turret 

watch, held by all Marines scheduled to participate in the following days’ trials and 

consisted of 2 hours of watch. This watch only occurred on nights prior to evaluated 

assessed events. On the platoon's maintenance day, for preventative maintenance 

checks and services (PMCS), Marines conducted maintenance on winch cables and 

reset any gear stowed incorrectly during evaluations, as well as any major maintenance 

actions required from vehicle issues. At the end of the established 12-day cycle, each 

crew conducted lubrication orders on their vehicle prior to movement back to Camp 

Wilson. The day spent at Camp Wilson was a range maintenance day where 

contractors performed any repairs or maintenance on all targets used during the 12-day 

cycle. Weekly maintenance checks and services were conducted every other PMCS 

day.

B.1.5.1 Loading Challenges

There were multiple challenges enacting a loading plan that simulated the physical and 

mental difficulties of combat or a combat-training environment. The foremost problem 

was the mindset of the volunteers. When executing subtasks during loading trials, 

Marines moved slower or exerted less effort knowing the trial was not part of formal 

data collection efforts. Concerns for troop welfare and morale support led to decisions 

that allowed Marines to bivouac in a covered administrative position every maintenance 

day during a trial rather than maintain a tactical posture on their vehicles over the 

course of multiple trials. This administrative posture alleviated the cumulative effect that 

fatigue has on Marines in a tactical environment. 
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B.1.6 Scheme of Maneuver Summary

The LAR Experiment consisted of a 3-day trial cycle consisting of non-live-fire, live-fire, 

and maintenance days. The non-live-fire trials had seven subtasks in three categories: 

CASEVAC, recovery operations, and maintenance actions. The live-fire trials had 11 

subtasks in two categories: prepare for combat and live-fire engagements. During the 

course of the experiment, the LAR platoon executed 2 pilot trial cycles, 16 record trial

cycles, and 1 makeup trial cycle. During trial execution, Marines wore a standard, 

vehicle fighting load while conducting all subtasks, which weighed approximately 35 lb. 

When not participating in a trial, Marines executed all subtasks to ensure equivalency 

loading amongst volunteers and wore the standard vehicle fighting load. Knowing their 

efforts were not being directly observed and recorded did not ensure equivalency of 

effort. Additional physical loading included watch rotations, vehicle maintenance, and a 

vehicle bivouac site. A rotation into an administrative posture every maintenance day 

alleviated the cumulative effect fatigue has on Marines in a tactical environment. 

B.2 Limitations

B.2.1 Limitations Overview

The members of the LAR assessment executed a variety of subtasks over the course of 

a 3-day trial cycle meant to encompass, as accurately as possible, the demands of the 

LAV Crewman MOS. The evaluated subtasks within the cycle were considered the 

most physically demanding and operationally relevant tasks that a junior LAV crewman 

would be expected to perform on a recurring basic. These subtasks were executed as 

they would normally be performed; however, due to time constraints, data collection 

requirements, and other factors, limitations and artificialities existed in the assessment. 

These limitations had little to no effect on data collection, but impacted the cumulative 

loading effects and fatigue of the volunteers. 

B.2.1.1 Number of Volunteer Participants

For the LAV experiment, 14 male and 7 female volunteers began the experiment, but by 

the end 13 males and 7 females were able to complete the assessment. The results 

presented in this annex are based on the performance of 21 Marines. 

B.2.2 Additional Duties as Dismounted Infantry

During normal LAR operations, vehicle crewmen may be required to operate as 0311 

dismounted infantry (known as scouts within the LAR community) at any time. The 

continuing actions of combat operations, such as vehicle maintenance, turret watch, 

and patrolling, are shared between the scouts and the crewmen. During defensive 

operations, the four-man scout team may augment the three-man vehicle crew and 

share in the collective burden of turret watch and observation throughout the course of a 
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night, if not otherwise engaged. Crewmen will be expected to conduct dismounted 

operations, such as patrolling or defensive position improvement, to aid the scouts. 

The limited scope, duration, and resources available meant crewmen did not participate 

in any dismounted operations nor were any scouts used during the execution of the 

assessment. The Infantry Functional Test comprehensively captured most of the basic 

dismounted actions of scouts during their execution on the 100 series ranges. 

Crewmen would normally participate in a number of dismounted actions that contribute 

to the overall loading and fatigue inherent in combat operations and training exercises. 

B.2.3 Cycle of Operations Constraints

The LAR assessment attempted to observe and capture the most physically demanding 

tasks at the core of the LAV crewman billet description, but it could not fully replicate the 

demands of continuous 24-hour field operations, either in training or combat 

environment. A vehicle crew typically finished their assessed non-live-fire maintenance 

tasks within 2 hours on their first trial day and their assessed live-fire tasks within 

4 hours on their second trial day. Under normal operating conditions, Marines would 

not complete their day and responsibilities in such a short time. Limited maintenance 

and data collection resources, as well as time constraints, limited additional observed 

loading. 

Although many of the tasks required an intense amount of effort for a short time, 

Marines were exempt from auxiliary tasks and duties that come with sustained field 

operations. To ensure sustainability over a test that could have spanned 75 days, 

Marines spent two nights on their vehicles and one night in an improved structure during 

the 3-day cycle of operations. During normal operations, a platoon would spend nearly 

all of their time on their vehicles, executing a robust watch and patrolling rotation 

throughout the course of the night. Human factors and morale concerns prevented a 

fully tactical environment in which the Marines executed these continuing actions for 

extended periods. Observation and time constraints made many such actions 

impractical, as the data collection team would be unable to gather information as the 

Marines executed such duties. Marines returned from the field every 12 days, an 

artificiality that may not be present during extended operations. 

B.2.4 Missing Trials that Affect Analysis 

The Toughbook programming used to record time hack data for Prep M242 Main Gun 

and Conduct Main Gun Remedial Action incorrectly captured start and stop times for the 

tasks, leading to lost data. The program captured the disassembly time for the task, but 

did not record the completion time, leading to lost reassembly time data for 29 trials. 

Therefore, only 56 trials were available for certain metrics associated with those tasks. 
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B.2.5 0313 Limitations Summary

The LAR assessment sought to replicate the realities of field conditions and loading 

Marines experience during field training and combat operations. The assessment team 

balanced these demands with the necessity of collecting equitable and uniform data 

throughout the assessment’s duration and across many participants. This led to certain 

artificialities that departed from normal operations but did not affect the validity of data 

collection or the assessment as a whole. 

B.3 Deviations

Deviations to the execution of the LAV Crewman scheme of maneuver were made and 

annotated in the Experimental Data Report; however, there were no deviations that 

occurred that affected the analysis methodology outlined in the Experimental 

Assessment Plan.

B.4 Data Set Description

B.4.1 Data Set Overview 

The LAV experiment timeline included 2 pilot trial cycles, 16 record trial cycles, and 3 

makeup trial cycles. Pilot data were not analyzed. The record trial cycles were

conducted as planned from 9 March through 1 May 2015. One makeup trial cycle was 

required and conducted from 2-4 May 2015.

B.4.2 Record Test Volunteer Participants

Twenty-one Marine volunteers participated in the Light Armored Vehicle (LAV)

Crewman experiment, including 14 males and 7 females. One male volunteer was 

dropped from the experiment after 2 cycles, leaving a total of 20 volunteers, 13 males 

and 7 females.

B.4.3 Planned, Executed, and Analyzed Trial Cycles

Sixteen record cycles equates to 80 planned trials for each task. With the inclusion of 

one makeup trial cycle, volunteers executed 85 trials. Of note, there are several 

occurrences of missing data. As discussed above, the Toughbook programming used 

to record time data for Prep M242 Main Gun and Conduct Main Gun Remedial Action 

did not record the completion time, leading to lost reassembly time data for 29 trials. 

The data management team identified the problem on 26 March and fixed the program

for the subsequent trial cycles. Live-fire Engagement Data is missing on several 

occasions due to wind delays on the range. Sustained winds above 35 mph have the 

potential to damage targetry at Range 500, and gunnery went into a check fire status 

any time these conditions were observed. Wind delays caused the loss of 2 trials on 13 

March and 5 trials on 21 April. One trial was not executed on 17 March due to the loss 
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of a vehicle commander mid cycle. Any other lost trial data is due to data collector or 

Toughbook program error, or equipment malfunction that led to an invalid data point. 

Table B-1. 0313 Planned, Executed and Analyzed Trial Cycles1

Task and 

Metric 

Description

Integratio

n Level

Numbe

r of 

Planne

d Trials

Number 

of Trials 

Conducte

d 

Numbe

r of 

Trials 

Used 

in 

Analysi

s

Notes

Crew 

Evacuation 

from Turret

C 27 29 29

LD 27 28 28

HD 26 28 28

CASEVAC; 

Overall Time

C 27 29 29

LD 27 28 28

HD 26 28 28

CASEVAC; 

Time to 

Extract

C 27 29 29

LD 27 28 28

HD 26 28 28

CASEVAC; 

Time to Rally 

Point

C 27 29 29

LD 27 28 28

HD 26 28 28

Rig for 

Recovery; 

Overall Time

C 27 29 29

LD 27 28 27

Data Collector/Toughbook (DC/TB) Error; 9 

Mar

HD 26 28 28

Rig for 

Recovery; 

Time to Rig

C 27 29 28 DC/TB Error; 11 Apr

LD 27 28 28

HD 26 28 28

Rig for 

Recovery; 

Time to Stow

C 27 29 27 DC/TB Error; 1 Apr, 2 May

LD 27 28 27 DC/TB Error; 7 Apr

HD 26 28 28

Rig for Tow; 

Overall Time

C 27 29 29

LD 27 28 28

HD 26 28 28

Rig for Tow; 

Time to Rig

C 27 29 29

LD 27 28 28

HD 26 28 28

Rig for Tow; 

Time to Stow

C 27 29 29

LD 27 28 28

HD 26 28 28

Remove Scout C 27 29 29
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Task and 

Metric 

Description

Integratio

n Level

Numbe

r of 

Planne

d Trials

Number 

of Trials 

Conducte

d 

Numbe

r of 

Trials 

Used 

in 

Analysi

s

Notes

Hatches; 

Overall Time

LD 27 28 27 DC/TB Error; 19 Mar

HD 26 28 28

Remove Scout 

Hatches; 1st 

Hatch

C 27 29 29

LD 27 28 27 DC/TB Error; 19 Mar

HD 26 28 28

Remove Scout 

Hatches; 2nd 

Hatch

C 27 29 29

LD 27 28 27 DC/TB Error; 19 Mar

HD 26 28 28

Remove Side 

Panels; 

Overall Time

C 27 29 29

LD 27 28 28

HD 26 28 28

Remove Side 

Panels; 1st 

Panel

C 27 29 29

LD 27 28 28

HD 26 28 28

Remove Side 

Panels; 2nd 

Panel

C 27 29 29

LD 27 28 28

HD 26 28 28

Mount/Remo

ve Spare Tire; 

Overall Time

C 27 29 26 DC/TB Error; 9 Mar, 1 Apr, 11 Apr

LD 27 28 27 DC/TB Error; 23 Apr

HD 26 28 28

Mount/Remo

ve Spare Tire; 

Mount Spare

C 27 29 27 DC/TB Error; 9 Mar, 11 Apr

LD 27 28 27 DC/TB Error; 23 Apr

HD 26 28 28

Mount/Remo

ve Spare Tire; 

Remount 

Original 

C 27 29 27 DC/TB Error; 9 Mar, 1 Apr

LD 27 28 28

HD 26 28 28 

Prep M240 

Coax; Overall 

Time

C 27 29 29

LD 27 27 27

HD 26 28 27 Equip Failure; 15 Apr

Prep M240 

Coax; 

Disassembly 

C 27 29 29

LD 27 27 27

HD 26 28 27 Equip Failure; 15 Apr

Prep M240 

Coax; 

Reassembly

C 27 29 29

LD 27 27 27

HD 26 28 27 Equip Failure; 15 Apr

Manually C 27 29 29
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Task and 

Metric 

Description

Integratio

n Level

Numbe

r of 

Planne

d Trials

Number 

of Trials 

Conducte

d 

Numbe

r of 

Trials 

Used 

in 

Analysi

s

Notes

Manipulate 

Turret; 

Overall Time

LD 27 27 27

HD 26 28 28 

Manually 

Manipulate 

Turret; 

Traverse Time

C 27 29 28 DC/TB Error; 23 Mar

LD 27 27 27

HD 26 28 26 DC/TB Error; 13 Mar, 17 Mar

Manually 

Manipulate 

Turret; 

Elevation 

Time

C 27 29 28 DC/TB Error; 23 Mar

LD 27 27 27

HD

26 28

26

DC/TB Error; 13 Mar, 17 Mar

Prep M242 

Main Gun; 

Overall Time

C 27 29 18 TB Error; 3-26 Mar

LD 27 27 18 TB Error; 3-26 Mar

HD 26 28 18 TB Error; 3-26 Mar

Prep M242 

Main Gun; 

Disassembly 

C 27 29 27 DC/TB Error; 12 Apr, Equip Failure; 15 Apr

LD 27 27 27

HD 26 28 28

Prep M242 

Main Gun; 

Reassembly

C 27 29 17 TB Error; 3-26 Mar, DC/TB Error; 12 Apr

LD 27 27 18 TB Error; 3-26 Mar

HD 26 28 18 TB Error; 3-26 Mar

Load and 

Stow 

Additional 

Ammunition

C 27 29 29

LD 27 27 27

HD 26 28 28 

Upload M240 

Coax

C 27 29 29

LD 27 27 27

HD 26 28 28

Upload M242 

Main Gun

C 27 29 29

LD 27 27 25 DC/TB Error; 26 Mar, 30 Apr

HD 26 28 27 DC/TB Error; 17 Mar

Defensive 

Engagement 

#1

C 27 27 27 Wind Delays; 13 Mar, 21 Apr 

LD 27 25 25

Wind Delays; 13 Mar, 21 Apr, VC Drop; 17 

Mar 

HD 26 25 25 Wind Delays; 13 Mar, 21 Apr 

Offensive 

Engagement 

#1

C 27 27 27 Wind Delays; 13 Mar, 21 Apr 

LD 27 25 25

Wind Delays; 13 Mar, 21 Apr, VC Drop; 17 

Mar 
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Task and 

Metric 

Description

Integratio

n Level

Numbe

r of 

Planne

d Trials

Number 

of Trials 

Conducte

d 

Numbe

r of 

Trials 

Used 

in 

Analysi

s

Notes

HD 26 25 25 Wind Delays; 13 Mar, 21 Apr 

Conduct 

Remedial 

Actions; 

Overall Time

C 27 27 18 TB Error; 3-26 Mar

LD 27 27 18 TB Error; 3-26 Mar

HD 26 27 18 TB Error; 3-26 Mar

Conduct 

Remedial 

Actions; 

Disassembly

C 27 27 27 Wind Delay 13 Mar

LD 27 27 27 Wind Delay 13 Mar

HD 26 27 27 Wind Delay 13 Mar

Conduct 

Remedial 

Actions; 

Reassembly

C 27 27 18 TB Error; 3-26 Mar

LD 27 27 18 TB Error; 3-26 Mar

HD 26 27 18 TB Error; 3-26 Mar

Defensive 

Manual 

Engagement 

#2

C 27 27 22 Failed Engagements Excluded

LD 27 25 22 Failed Engagements Excluded

HD 26 25 21 Failed Engagements Excluded

Offensive 

Engagement 

#2

C 27 27 27 Wind Delays; 13 Mar, 21 Apr 

LD 27 25 25

Wind Delays; 13 Mar, 21 Apr, VC Drop; 17 

Mar 

HD 26 25 25 Wind Delays; 13 Mar, 21 Apr 

1. Data was not captured or captured incorrectly due to human (Data Collector - DC) error or data processing equipment 

(Toughbook - TB) error. Wind delays also caused a loss of data on some occasions. Some data points were classified as 

outliers or potential influential points and were excluded from the analysis as described in the methodology section. 

B.5 Descriptive and Basic Inferential Statistics

B.5.1 Descriptive Statistics Overview

The evaluated subtasks within the cycle were considered the most physically 

demanding and operationally relevant tasks that a junior 0313 LAV crewman would

perform on a recurring basis. Twelve out of 18 tasks are presented in this section. 

Appendix B contains the descriptive statistics for the remaining 0313 tasks. 

As described in the Scheme of maneuver (see Section B.1), an LAV-25 crew is made 

up of three Marines: a VC, Gunner, and Driver. For each trial, male and female 

volunteers rotated through the role of gunner and driver. Due to required experience for 

the VC billet, Marines selected to serve as VCs were rotated among the five billets for 

the duration of the experiment. There were three integration levels assessed for this 

task: a control (C) group of all male Marines, a low-density (LD) group of one female 
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and two male Marines, and a high density (HD) group of two females and one male 

Marine. 

In addition to integration level comparisons, there are certain tasks also analyzed by 

critical billet. Although most tasks are completed as an LAV Crew where Marines can 

assist other Marines, certain tasks (such as turret manipulation) require individuals 

holding the critical billet (such as vehicle gunner) to perform his or her specific duties 

with little or no assistance. A critical billet was identified for tasks where a physically 

demanding duty was primarily performed by that billet. 

This section includes experimental results based on descriptive statistics, analysis of 

variance (ANOVA), Tukey Tests (or non-parametric equivalent as necessary), and 

scatter plots. The first table titled Descriptive Statistics displays the metric, integration 

levels, sample sizes, means and standard deviations. The second table shows ANOVA 

and Tukey test results including, but not limited to, metrics, p-values suggesting 

statistical significance, integration level elapsed time differences and percentage 

differences between integration levels. If non-parametric tests were needed, the 

second table displays these results instead of ANOVA and Tukey test results. 

Subsequent subsections will cover each task in detail along with scatter plots of the 

data. If p-values are less than the a-priori significance level of 0.10, we conclude that 

there is statistical evidence that the mean elapsed time for the experimental groups, LD 

and HD, are different from the C group. 

Contextual comments and additional insights tying back to each experimental task are 

incorporated. Two separate subsections for each task are presented in order to report 

analytical results with and without potential influential points. These potential influential 

points form part of the valid data. 

Lastly, special caution should be taken when comparing similar tasks executed by 

different MOSs across the GCEITF experiment. Comparative analysis may be 

misleading due to differing factors between MOS tasks such as distances, techniques, 

leadership, load carried, group size, and group composition. The words “metric” and 

“task” are used interchangeably throughout this Annex. They both refer to the 

experimental task.

B.5.2 Conduct Casualty Evacuation Overview

The ability to perform a fast and efficient casualty or crew evacuation is a vital skill, 

especially while confined to a vehicle. This event required the LAV-25 Gunner and 

Driver to extract a combat loaded test dummy weighing 205 lbs. from the vehicle and 

move it to a rally point 25 meters away. The casualty simulated an incapacitated 

Vehicle Commander, thus leaving the two remaining crewmen to conduct the 

evacuation. The extraction required crewmen to physically lift the dummy straight up 

from the turret and move it to the front of the vehicle; this task also required either a 
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fireman carry or two-man carry technique to move the casualty to the rally point. The 

subtask also simulated the arrival and aid of another LAV-25 crew or scouts from a 

supplementary position in order to assist in the CASEVAC. This was accomplished by 

the VC assisting in the evacuation after 6 minutes. The start time for this task began 

when all crewman were in their stations. Times were recorded once the casualty was 

extracted from the turret and placed on the front slope of the vehicle. Time was stopped

when the crew reached the rally point 25 meters away. Additionally, another time hack 

was recorded once a crew reached six minutes and the simulation allowed for another 

crewman to assist in the CASEVAC. Evacuating the dummy from the turret simulated 

the most difficult form of evacuation a crew may face in a tactical environment after 

vehicle damage prevents normal turret operations.

B.5.2.1 Conduct Casualty Evacuation Scatterplots

The full data set is displayed in the scatter plots below. This data set did not contain 

outliers or potential influential data points. All data points shown in the scatter plots 

were determined to be valid and used in the analysis and modeling. The first plot 

shows the total elapsed time to evacuate the casualty from the turret and movement to 

the rally point. The second plot only displays the elapsed time for the extraction of the 

casualty from the turret. The third plot shows the times recorded for the movement of 

the casualty to the rally point after it was placed on the hood of the vehicle. 

Figure B-1. Evacuate Casualty from Vehicle by Integration Level
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Figure B-2. Evacuate Casualty from Vehicle; Extraction from Turret

Figure B-3. Evacuate Casualty from Vehicle; Movement to Rally Point

B.5.2.2 Conduct Casualty Evacuation Data Tables and Analysis

The tables below summarize the results of the task, Conduct Casualty Evacuation. The 

first table compares means across metrics and integration levels. The second table 
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AUGUST 2015 B-20

presents ANOVA and Tukey test results bringing to focus those metrics that resulted in 

statistical significance along with their percentage differences.

Table B-2. Evacuate Casualty from Vehicle Results

Metric Integration 

Level 

Sample 

Size Mean SD

Evac Casualty from Vehicle 

(minutes) *

C 29 2.24 0.78

LD 28 2.44 0.79

HD 28 3.73 1.73

Evac Casualty from Vehicle; 

Extraction (minutes) *

C 29 1.26 0.58

LD 28 1.42 0.68

HD 28 2.21 1.44

Evac Casualty from Vehicle; 

Movement to Rally Point (minutes) *

C 29 0.98 0.38

LD 28 1.02 0.21

HD 28 1.51 0.51

*Indicates there is a statistically significant difference in a two-sided hypothesis test, between integration levels 

according to ANOVA or a non-parametric equivalent test.

Table B-3. Evacuate Casualty from Vehicle ANOVA and Tukey Test

Metric

F 

Statisti

c (df)

F Test 

P-Value 

Comp

arison Diff % Diff 2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Evac Casualty 

from Vehicle 

(minutes)

8.52

(2, 51) < 0.01††

LD-C 0.20 8.88% 0.34 -0.07 0.47 -0.15 0.55

HD-C 1.48 66.20% < 0.01†† 1.02 1.95 0.88 2.09

HD-LD 1.29 52.65% < 0.01†† 0.82 1.75 0.68 1.89

Evac Casualty 

from Vehicle; 

Extraction 

(minutes)

5.19

(2, 50) 0.01††

LD-C 0.16 12.48% 0.35 -0.06 0.38 -0.12 0.44

HD-C 0.95 75.05% < 0.01†† 0.57 1.33 0.45 1.44

HD-LD 0.79 55.64% 0.01†† 0.40 1.18 0.28 1.30

Evac Casualty 

from Vehicle; 

Movement to Rally 

Point (minutes)

12.29

(2, 49) < 0.01††

LD-C 0.04 4.24% 0.61 -0.06 0.15 -0.09 0.18

HD-C 0.54 54.78% < 0.01†† 0.38 0.69 0.34 0.73

HD-LD 0.49 48.48% < 0.01†† 0.36 0.63 0.32 0.67

*Indicates there is a statistically significant difference in a two-sided hypothesis test, between integration levels 

according to ANOVA or a non-parametric equivalent test.

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances). For comparisons 

utilizing robust ANOVA, Tukey confidence intervals have been replaced by individual Welch’s T-tests with p-values 

compared to a Bonferroni corrected threshold. 

For the overall time to evacuate the casualty, the C group data are normally distributed 

with Shapiro-Wilk Test p-value of 0.05, while the LD and HD groups are not normally 

distributed as evidenced by p-values of 0.001 and 0.004, respectively. Additionally, 

since the standard deviation of the HD group is more than twice that of the C and LD 

groups, we recommend using the robust ANOVA results presented above. We proceed 

with presenting robust ANOVA results since they are confirmed by a Kruskal-Wallis Test 

(p-value = 0.01).
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B-21 AUGUST 2015

For the extraction portion of the time, the C group data are normally distributed with 

Shapiro-Wilk Test p-value of 0.36, while the LD and HD groups are not normally 

distributed as evidenced by p-values less than 0.01. Additionally, since the standard 

deviation of the HD group is more than twice that of the C and LD groups, we 

recommend using the robust ANOVA results presented above. We proceed with 

presenting robust ANOVA results since they are confirmed by a Kruskal-Wallis Test 

(p-value = 0.01).

For the movement to rally point portion of the time, the C and LD group data are 

normally distributed with Shapiro-Wilk Test p-values of 0.70 and 0.90, respectively, 

while the HD group is not normally distributed as evidenced by a p-value of 0.01. 

Additionally, since the SD of the HD group is more than twice that of the LD group, we 

recommend using the robust ANOVA results presented above. We proceed with 

presenting robust ANOVA results, since they are confirmed by a Kruskal-Wallis Test (pvalue < 0.01).

For the overall time to evacuate the casualty the C group had a mean time of 2.24 

minutes, which was statistically significantly faster than the LD and HD groups who 

recorded mean times of 2.44 minutes and 3.73 minutes, respectively. The C group’s 

66.20% faster mean time when compared to the HD group was statistically significant. 

The other two metrics shown in Table B-2, Evacuation Casualty from Vehicle Extraction 

and Movement to Rally Point, also show statistical significance when comparing the C 

group and HD group. The percentage differences equate to degradation in evacuation 

times for LD and HD groups when compared to the C group. Additionally, all HD groups 

for the three metrics above show greater variability as shown by the SD column. See 

Table B-1 and Table B-2 for detailed analytical results. 

B.5.2.3 Conduct Casualty Evacuation Contextual Comments

Rapidly removing a wounded crewman from the vehicle is the first step to providing 

lifesaving care. Longer times to extract a casualty could lead to greater exposure to 

various threats, such as vehicle on fire, both for the casualty and the Marines 

conducting the evacuation. Casualty extract should proceed as quickly as possible to 

minimize this exposure. Additionally, moving a casualty to a place of cover and 

concealment or to a CCP increases survivability. 

B.5.2.4 Conduct Casualty Evacuation Additional Insights

Slower movements lead to greater exposure time. A greater reliance on two-man 

carrying methods removes another Marine from providing local security during the 

movement. Integrated crews performed noticeably slower during the execution of this 

subtask. 
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AUGUST 2015 B-22

B.5.3 Prepare Light Armored Vehicle for Combat Overview

MCWP 3-14.1, Light Armored Vehicle-25 Gunnery and Employment, states the 

following: 

On future battlefields, the tempo will be such that an LAV-25 crew must be 

prepared to move and to rapidly acquire and engage multiple 

targets...The LAV-25’s speed and mobility, coupled with battle drills, 

increase the likelihood of opposing and allied forces becoming 

intermingled during combat operations. Survival in these situations 

depends on the crew’s ability to effectively search for, detect, locate, 

identify, classify, confirm, and rapidly engage enemy targets. The LAV-25 

crews must take advantage of the tactical situation and engage first. 

Speed and accuracy of an engagement depend on the degree of crew 

proficiency in target acquisition techniques and gunnery procedures. 

This passage effectively illustrates the importance of speed and tempo not only in the 

conduct of gunnery, but also in the basic skills and preparatory tasks that lend 

themselves to effective gunnery procedures and correct target acquisition techniques. 

The same publication also details the conduct of the LAV Gunnery Skills Test (LGST), a 

basic skills test that drove the inclusion of many of the prep for combat subtasks. By 

the end of the experiment, most if not all volunteers were able to meet LGST 

requirements. Important to note, however, is that the LGST is a tool that ensures 

Gunners “meet minimum standards for training and safety before advancing into live 

fire.” The times stipulated in the LGST should be viewed as safety minimums for training 

environments, not the expectation for gunnery standards in combat. 

Prep for combat tasks were conducted as individual Gunner’s events despite being 

crew level events. In an LAV crew, the Gunner’s primary responsibility is the 

preparation, upkeep, and employment of the vehicle’s turret and weapons systems, 

especially the M240 coaxially mounted machine gun and the M242 Main Gun. 

Therefore, the Gunner holds the critical billet in most prep for combat and live-fire tasks. 

The Gunner expends the most effort with little or no physical assistance from the other 

crewman. 

The data collected for this task was analyzed in two ways. The first comparison looked 

at performance differences between the crews grouped by the gender of the Marine 

serving as Gunner and actively participating in the task. The second comparison looked 

for performance differences between the control group, low-density group, and highdensity group. 

B.5.4 Prepare the M240 Coax Overview 

This subtask required the LAV-25 Gunner, without assistance, to remove, disassemble, 

reassemble and install the M240 coaxially mounted machine gun. Per MCWP 3-14.1, 
GCEITF EAR ANNEX B

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crewman have 15 minutes to complete this task during the LAV Gunnery Skills Test. 

Disassembly was achieved when the Gunner removed the bolt assembly from the 

weapon system. The ability to rapidly troubleshoot and correct issues within the turret is 

an absolutely critical skill for LAV Gunners. As the very basis of their role on a vehicle 

crew, a Gunner must be able to rapidly accomplish any task involving the LAV-25’s 

weapons systems. When the Vehicle Commander and Driver are engaged in their 

primary duties, they often will not be able to lend assistance to the Gunner. Gunners 

were evaluated on the time required to disassemble and to reassemble the weapon 

system. 

The data collected for this task was analyzed by critical billet and by integration level. 

B.5.4.1 Prepare the M240 Coax by Critical Billet

See B.5.4 for task description.

B.5.4.1.1 Prepare the M240 Coax by Critical Billet Scatterplots

All data points shown in the scatter plots below were determined to be valid and used in 

the analysis and modeling. There were no outliers or potential influential points for this 

data set. The first plot shows the total elapsed time to execute the task of Prep M240 

Coax. The second plot displays the elapsed time for disassembly of the M240, while 

the third plot displays the reassembly of the M240. 

Figure B-4. Prep M240 Coax by Critical Billet

Critical Billet Gender
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AUGUST 2015 B-24

Figure B-5. Prep M240 Coax; Disassembly by Critical Billet

Figure B-6. Prep M240 Coax; Reassembly by Critical Billet

B.5.4.1.2 Prepare the M240 Coax by Critical Billet Data Tables and Analysis

The tables below summarize the results of the task, Prepare the M240 Coax. The data 

was analyzed by critical billet. The first table compares means across metrics and 

integration levels. The second table presents ANOVA and Tukey test results bringing to 

Critical Billet Gender

Critical Billet Gender
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B-25 AUGUST 2015

focus those metrics that resulted in statistical significance along with their percentage 

differences. 

Table B-4. Prep M240 Coax by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD 

Prep M240 Coaxial Machine Gun (Gunner) 

(minutes) * 

M 41 2.79 0.96

F 42 3.74 2.05

Prep M240 Coaxial Machine Gun; 

Disassembly (Gunner) (minutes) * 

M 41 1.29 0.51

F 42 1.62 0.63

Prep M240 Coaxial Machine Gun; 

Re-assembly (Gunner) (minutes) * 

M 41 1.51 0.57

F 42 2.12 1.85

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

Table B-5. Prep M240 Coax by Critical Billet ANOVA and Welch’s T-Test

Metric

F 

Statist

ic (df)

F Test 

PValue 

Comp

arison Diff % Diff

TTest 

Stati

stic 

(df)

1-Sided 

P-Value 

2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Prep M240 Coaxial 

Machine Gun 

(Gunner) (minutes)

7.33

(1, 59) 0.01†† F-M 0.95 33.92% 2.71 (59) < 0.01* < 0.01* 0.49 1.40 0.36 1.53

Prep M240 Coaxial 

Machine Gun; 

Disassembly 

(Gunner) (minutes)

7.12 

(1, 81) < 0.01* F-M 0.34 26.14% 2.68 

(78) < 0.01* < 0.01* 0.17 0.50 0.13 0.55

Prep M240 Coaxial 

Machine Gun; Reassembly (Gunner) 

(minutes)

4.17

(1, 49) 0.05†† F-M 0.61 40.56% 2.04 (49) 0.02* 0.05* 0.22 1.00 0.11 1.11

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances). 

For all tasks above, the normality assumption of ANOVA is satisfied since all samples 

are sufficiently large (n > 30). For total time to prep the M240, the standard deviation of 

the F group is more than twice that of the M group, thus we recommend using the 

robust ANOVA results presented above. For the disassembly portion of time, the equal 

variance assumption is satisfied and we proceed with presenting ANOVA results. For 

the assembly portion of time, the standard deviation of the F group is more than twice 

that of the M group, thus we recommend using the robust ANOVA results presented 

above.

For all tasks above, we proceed with presenting ANOVA results since all samples are 

sufficiently large (n > 30). For the overall coax preparation time, the Male group had a 

mean time of 2.79 minutes, which was statistically significantly faster than the Female 

group that recorded a mean time of 3.74 minutes. The Male group’s 33.92% faster 
GCEITF EAR ANNEX B

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AUGUST 2015 B-26

mean time when compared to the Female group was statistically significant. The other 

two metrics shown in Table B-4 above, M240 Disassembly Time and M240 Reassembly 

Time also show statistical significance when comparing the Male group and Female 

group. The percentage differences equate to degradation in disassembly and 

reassembly times for the Female group when compared to the Male group. 

Additionally, the Female group for the three metrics above shows a greater variability as 

shown by the SD column. See Tables B-4 and B-5 above for detailed analytical results. 

B.5.4.1.3 Prepare the M240 Coax by Critical Billet Contextual Comments

Disassembly and Assembly of the M240 Coax is an individual task solely executed by 

the Gunner. A LD integration crew could have either a male or a female serving as the 

Gunner. This has the potential to mask an individual Gunner’s performance using 

integration level analysis alone. Therefore, it was necessary to explore the results of 

this subtask based on the gender of the Gunner. 

B.5.4.1.4 Prepare the M240 Coax by Critical Billet Additional Insights

Integrated crews performed noticeably slower during the execution of this subtask. Per 

the actuarial tables in MCWP 3-14.1, engagements against dismounted or troop targets 

most often engaged with the M240 are measured in seconds. Should the coax jam or 

require remedial action, rapidly troubleshooting and restoring functionality must occur as 

rapidly as possible to ensure crew and vehicle survivability.

B.5.4.2 Prepare the M240 Coax by Critical Billet (Excluding Potential Influential Results) 

See B.5.4 for description of task.

B.5.4.2.1 Prepare the M240 Coax by Critical Billet (Excluding Potential Influential Results) 

Scatterplots

Influential points are identified by a lightly colored solid black circle in the scatter plots 

below. These points were excluded for analysis. The first plot shows the total elapsed 

time to execute the task. The second plot displays the elapsed time only for the 

disassembly of the M240. The third plot shows the times recorded for the reassembly 

portion of the task.
GCEITF EAR ANNEX B

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B-27 AUGUST 2015

Figure B-7. Prep M240 Coax by Critical Billet (Excluding)

Figure B-8. Prep M240 Coax by Critical Billet; Disassembly (Excluding)

Critical Billet Gender

Critical Billet Gender
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AUGUST 2015 B-28

Figure B-9. Prep M240 Coax by Critical Billet; Reassembly (Excluding)

B.5.4.2.2 Prepare the M240 Coax by Critical Billet (Excluding Potential Influential Points) 

Tables and Analysis

The tables below summarize the results of the task, Prepare the M240 Coax. The 

results are presented by critical billet and exclude potential influential points. The first 

table compares means across metrics and integration levels that display critical billet by 

gender. The second table presents ANOVA and Tukey test results bringing to focus 

those metrics that resulted in statistical significance along with their percentage 

differences.

Table B-6. Prep M240 Coax by Critical Billet (Excluding) 

Metric Integration 

Level 

Sample 

Size Mean SD

Prep M240 Coaxial Machine Gun 

(Gunner) [excluding potential 

influential points] (minutes) *

M 41 2.79 0.96

F 41 3.48 1.22

Prep M240 Coaxial Machine Gun; 

Disassembly (Gunner) [excluding 

potential influential points]

(minutes) *

M 40 1.25 0.45

F 41 1.60 0.62

Prep M240 Coaxial Machine Gun; 

Reassembly (Gunner) [excluding 

potential influential points]

(minutes)

M 40 1.51 0.57

F 37 1.67 0.60

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between integration levels according to ANOVA or a non-parametric equivalent test.

Critical Billet Gender
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B-29 AUGUST 2015

Table B-7. Prep M240 Coax by Critical Billet (Excluding) ANOVA and Welch’s T-Test

Metric

F 

Statist

ic (df)

F Test 

PValue 

Comp

arison Diff % Diff

T-Test 

Statisti

c (df)

1-Sided 

P-Value 

2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Prep M240 Coaxial 

Machine Gun 

(Gunner) 

[excluding 

potential 

influential points]

(minutes)

8.14 

(1, 80) < 0.01* F-M 0.69 24.76% 2.85 

(76) < 0.01* < 0.01* 0.38 1.00 0.29 1.09

Prep M240 Coaxial 

Machine Gun; 

Disassembly 

(Gunner)

[excluding 

potential 

influential points] 

(minutes)

8.66 

(1, 79) < 0.01* F-M 0.36 28.50% 2.95 

(73) < 0.01* < 0.01* 0.20 0.51 0.15 0.56

Prep M240 Coaxial 

Machine Gun; Reassembly

[excluding 

potential 

influential points]

(Gunner) (minutes)

1.52 

(1, 77) 0.222 F-M 0.16 10.78% 1.23 

(76) 0.11 0.22 -0.01 0.33 -0.06 0.38

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between integration levels according to ANOVA or a non-parametric equivalent test.

For all tasks above, we proceed with presenting ANOVA results since all samples are 

sufficiently large (n > 30). Additionally, for all tasks, group standard deviations are 

sufficiently similar to satisfy the equal variance assumption for ANOVA. 

For all tasks above, we proceed with presenting ANOVA results since all samples are 

sufficiently large (n > 30). For the overall coax preparation time, the Male group had a 

mean time of 2.79 minutes, which was statistically significantly faster than the Female 

group that recorded a mean time of 3.48 minutes. The Male group’s 24.76% faster 

mean time when compared to the Female group was statistically significant. M240 

Disassembly Time shown in Table B-7 above also shows statistical significance when 

comparing the Male group and Female group. The percentage differences equate to 

degradation in disassembly time for the Female Group when compared to the Male 

group. Additionally, the Female group for the three metrics above shows a greater 

variability as shown by the SD column. See Table B-6 and Table B-7 for detailed 

analytical results. 

B.5.4.2.3 Prepare the M240 Coax by Critical Billet (Excluding Potential Influential Points) 

Additional Insights

Observations after excluding potential influential results remain largely the same.
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B.5.4.3 Prepare the M240 Coax by Integration Level

See B.5.4 for description of task.

B.5.4.3.1 Prepare the M240 Coax by Integration Level Scatterplots

The three scatter plots below display Prep M240 coax results by integration level for the 

total elapsed time of the task, followed by hack time means for disassembly and 

reassembly. 

Figure B-10. Prep M240 Coax by Integration Level

Figure B-11. Prep M240 Coax; Disassembly by Integration Level
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B-31 AUGUST 2015

Figure B-12. Prep M240 Coax; Reassembly by Integration Level

B.5.4.3.2 Prepare the M240 Coax by Integration Level Tables and Analysis

The results in the tables below are presented by integration level and include potential 

influential points. The first table compares means across metrics and integration levels. 

The second table presents ANOVA and Tukey test results bringing to focus those 

metrics that resulted in statistical significance, indicated by p-values less than 0.01, 

along with their percentage differences.

Table B-8. Prep M240 Coax by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Prep M240 Coaxial Machine Gun 

(minutes) * 

C 29 2.73 0.89

LD 27 3.18 1.23

HD 27 3.95 2.36

Prep M240 Coaxial Machine Gun; 

Disassembly (minutes) * 

C 29 1.24 0.46

LD 27 1.39 0.50

HD 27 1.76 0.70

Prep M240 Coaxial Machine Gun; 

Re-assembly (minutes)

C 29 1.49 0.52

LD 27 1.79 0.88

HD 27 2.19 2.21

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between integration levels according to ANOVA or a non-parametric equivalent test.
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AUGUST 2015 B-32

Table B-9. Prep M240 Coax by Integration Level ANOVA and Tukey Test

Metric

F 

Statistic 

(df)

F Test 

PValue

Comp

arison

Differ

ence

% 

Differen

ce

P-Value 80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Prep M240 

Coaxial Machine 

Gun (minutes)

3.70

(2, 47) 0.03††

LD-C 0.45 16.43% 0.13 0.07 0.82 -0.04 0.93

HD-C 1.22 44.63% 0.02†† 0.59 1.85 0.40 2.04

HD-LD 0.77 24.22% 0.14 0.10 1.44 -0.09 1.63

Prep M240 

Coaxial Machine 

Gun; 

Disassembly 

(minutes)

6.42 (2, 

80) < 0.01*

LD-C 0.14 11.69% 0.60 -0.11 0.40 -0.17 0.46

HD-C 0.52 42.10% < 0.01* 0.26 0.78 0.21 0.83

HD-LD 0.38 27.23% 0.04* 0.11 0.64 0.06 0.69

Prep M240 

Coaxial Machine 

Gun; Reassembly 

(minutes)

2.21

(2, 44) 0.12

LD-C 0.30 20.38% 0.13 0.05 0.56 -0.02 0.63

HD-C 0.70 46.75% 0.12 0.12 1.27 -0.04 1.44

HD-LD 0.39 21.90% 0.40 -0.21 0.99 -0.38 1.17

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances). For comparisons 

utilizing robust ANOVA, Tukey confidence intervals have been replaced by individual Welch’s T-tests with p-values 

compared to a Bonferroni corrected threshold. 

Statistical analysis included analysis of variance (ANOVA) and multiple comparisons 

using Tukey tests. For the overall time to prep the M240, the C, LD, and HD group data 

are all not normally distributed with Shapiro-Wilk Test p-values of less than 0.01. 

Additionally, since the standard deviation of the HD group is more than twice that of the 

C group, we recommend using the robust ANOVA results presented above. We 

proceed with presenting robust ANOVA results, since they are confirmed by a KruskalWallis Test (p-value < 0.01). 

For the disassembly portion of the time, the C, LD, and HD group data are all not 

normally distributed with Shapiro-Wilk Test p-values of less than 0.01. Group standard 

deviations are sufficiently similar to satisfy the equal variance assumption of ANOVA. 

Thus, we proceed with presenting ANOVA results, since they are confirmed by a 

Kruskal-Wallis Test (p-value < 0.01). 

For the assembly portion of the time, the C, LD, and HD group data are all not normally 

distributed with Shapiro-Wilk Test p-values of less than 0.01. Additionally, since the 

standard deviation of the HD group is more than twice that of the C and LD groups, we 

recommend using the robust ANOVA results presented above. We proceed with 

presenting robust ANOVA results since they are confirmed by a Kruskal-Wallis Test 

(p-value = 0.24)

For the overall time required to disassemble and assemble the M240 the C group had a 

mean time of 2.73 minutes, which was statistically significantly faster than the HD 

groups that recorded a mean time of 3.95 minutes. The C group’s 44.63% faster mean

time when compared to the HD group was statistically significant. The Disassembly 

Time metric in Table B-9 also shows a statistical significance when comparing the HD
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group to the C group and the LD group. All HD and LD groups for the three metrics 

above show greater variability, as shown by the SD column. See Table B-8 and Table 

B-9 for detailed analytical results. 

B.5.4.3.3 Prepare the M240 Coax by Integration Level Additional Insights

Observations when examined by integration level remain largely the same as by critical 

billet, although critical billet results in the low-density group are less apparent.

B.5.4.4 Prepare the M240 Coax by Integration Level (Excluding Potential Influential 

Points) 

See B.5.4 for description of task.

B.5.4.4.1 Prepare the M240 Coax by Integration Level (Excluding Potential Influential 

Points) Scatterplots

The scatter plots below display the results of the various integration levels elapsed 

times to complete the task, as well as disassembly and reassembly of the M240 coax. 

Influential points in the following plots are identified by a lightly colored solid black circle. 

Figure B-13. Prep M240 Coax by Integration Level (Excluding)
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AUGUST 2015 B-34

Figure B-14. Prep M240 Coax by Integration Level; Disassembly (Excluding)

Figure B-15. Prep M240 Coax by Integration Level; Reassembly (Excluding)

B.5.4.4.2 Prepare the M240 Coax by Integration Level (Excluding Potential Influential 

Points) Data Tables and Analysis

The tables below summarize the results of the task, Prepare the M240 Coax. The first

table compares means across metrics and integration levels. The second table 
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presents ANOVA and Tukey test results bringing to focus those metrics that resulted in 

statistical significance along with their percentage differences.

Table B-10. Prep M240 Coax by Integration Level (Excluding)

Metric Integration 

Level 

Sample 

Size Mean SD 

Prep M240 Coaxial Machine Gun

[excluding potential influential points] 

(minutes) * 

C 29 2.73 0.89

LD 27 3.18 1.23

HD 26 3.55 1.19

Prep M240 Coaxial Machine Gun; 

Disassembly [excluding potential 

influential points] (minutes) * 

C 29 1.24 0.46

LD 25 1.28 0.33

HD 27 1.76 0.70

Prep M240 Coaxial Machine Gun; Reassembly [excluding potential influential 

points] (minutes)

C 29 1.49 0.52

LD 25 1.61 0.62

HD 25 1.66 0.63

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

Table B-11. Prep M240 Coax by Integration Level ANOVA and Tukey Test (Excluding)

Metric

F 

Statist

ic (df)

F Test 

PValue

Comp

arison

Differ

ence

% 

Differen

ce

P-Value 80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Prep M240 Coaxial 

Machine Gun 

[excluding 

potential 

influential points] 

(minutes)

3.82 

(2, 79) 0.03*

LD-C 0.45 16.43% 0.29 -0.06 0.96 -0.17 1.06

HD-C 0.82 30.16% 0.02* 0.31 1.34 0.20 1.45

HD-LD 0.37 11.79% 0.44 -0.15 0.90 -0.26 1.01

Prep M240 Coaxial 

Machine Gun; 

Disassembly 

[excluding 

potential 

influential points] 

(minutes)

5.91

(2, 49)

< 

0.01††

LD-C 0.04 3.31% 0.71 -0.10 0.18 -0.14 0.22

HD-C 0.52 42.10% < 0.01†† 0.31 0.73 0.25 0.79

HD-LD 0.48 37.54% < 0.01†† 0.29 0.68 0.23 0.73

Prep M240 Coaxial 

Machine Gun; Reassembly

[excluding 

potential 

influential points] 

(minutes)

0.63 

(2, 76) 0.53

LD-C 0.12 8.30% 0.72 -0.16 0.40 -0.21 0.46

HD-C 0.17 11.70% 0.53 -0.10 0.45 -0.16 0.51

HD-LD 0.05 3.14% 0.95 -0.24 0.34 -0.30 0.40

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances). For comparisons 

utilizing robust ANOVA, Tukey confidence intervals have been replaced by individual Welch’s T-tests with p-values 

compared to a Bonferroni corrected threshold. 

Statistical analysis included analysis of variance (ANOVA) and multiple comparisons 

using Tukey tests. For the overall time to prep the M240, the C and LD groups are not 

normally distributed with Shapiro-Wilk Test p-values of less than 0.01, while the HD 
GCEITF EAR ANNEX B

FOR OFFICIAL USE ONLY 

AUGUST 2015 B-36

group is normally distributed with p-value of 0.01, respectively. Group standard 

deviations are sufficiently similar to satisfy the equal variance assumption of ANOVA. 

We proceed with presenting ANOVA results since they are confirmed by a KruskalWallis Test (p-value = 0.01). 

For the disassembly portion of the time, the C and HD group data are not normally 

distributed with Shapiro-Wilk Test p-values of less than 0.01, while the LD group is 

normally distributed with p-value of 0.09. Additionally, since the standard deviation of 

the HD group is more than twice that of the LD group, we recommend using the robust 

ANOVA results presented above. We proceed with presenting robust ANOVA results, 

since they are confirmed by a Kruskal-Wallis Test (p-value < 0.01). 

For the assembly portion of the time, the C group is not normally distributed with 

Shapiro-Wilk Test p-value of less than 0.01, while the LD and HD groups are normally 

distributed with p-values of 0.01 and 0.01, respectively. Group standard deviations are 

sufficiently similar to satisfy the equal variance assumption of ANOVA. We proceed 

with presenting ANOVA results since they are confirmed by a Kruskal-Wallis Test (pvalue = 0.46). 

When excluding potential influential results, the overall time required to disassemble 

and assemble the M240 the C group had a mean time of 2.73 minutes, which was 

statistically significantly faster than the HD groups that recorded a mean time of 3.55

minutes. The C group’s 30.16% faster mean time when compared to the HD group was 

statistically significant. The Disassembly Time metric shown in Table B-11 also shows 

a statistical significance when comparing the HD group to the C group and the LD 

group. Additionally, the LD group shows less variability than the C group for 

disassembly time as shown by the SD column; all other HD and LD groups for the three 

metrics above show greater variability. See Table B-10 and Table B-11 for detailed 

analytical results.

B.5.4.4.3 Prepare the M240 Coax by Integration Level (Excluding Potential Influential 

Points) Additional Insights

Observations after excluding potential influential results remain largely the same. 

B.5.5 Manually Traverse and Elevate the LAV-25 Turret Overview

This subtask required the LAV-25 Gunner, without assistance, to manually traverse, 

elevate, and depress the vehicle turret. The Gunner used the manual traverse and 

elevation controls within the turret to accomplish the subtask. In the event of power loss 

within the turret, a Gunner must be able to rapidly manipulate the turret to acquire and 

engage targets. This skill is regularly assessed with manual engagements during table 

qualification gunnery. Gunners were evaluated on the time required to traverse and to 

elevate the vehicle turret. 
GCEITF EAR ANNEX B

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B-37 AUGUST 2015

The data collected for this task was analyzed by critical billet and by integration level. 

B.5.5.1 Manually Traverse and Elevate the LAV-25 Turret by Critical Billet

See B.5.5 for task description.

B.5.5.1.1 Manually Traverse and Elevate the LAV-25 Turret by Critical Billet Scatterplots

The following scatter plots depict the full data set for this particular task. The data 

points contained inside dark black circles were determined to be data collector or 

Toughbook errors and were excluded from the analysis. The first plot shows the full 

elapsed time for the critical billet displayed by the gender of the Marine executing the 

task. The second and third scatter plots focus on the traversing and elevate/depress 

aspects of the task, respectively. 

Figure B-16. Manually Manipulate Turret/Main Gun by Critical Billet

Critical Billet Gender
GCEITF EAR ANNEX B

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Figure B-17. Manually Manipulate Turret/Main Gun; Traverse by Critical Billet

Figure B-18. Manually Manipulate Turret/Main Gun; Elevate/Depress by Critical Billet

Critical Billet Gender

Critical Billet Gender
GCEITF EAR ANNEX B

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B.5.5.1.2 Manually Traverse and Elevate the LAV-25 Turret by Critical Billet Data Tables 

and Analysis

The tables below summarize the results of the task, Manually Traverse and Elevate the 

LAV-25 Turret. The results are displayed by critical billet. The first table compares 

means across metrics and critical billet by gender. The second table presents ANOVA 

and Tukey test results bringing to focus those metrics that resulted in statistical 

significance, as depicted by p-values, along with their percentage differences.

Table B-12. Manually Manipulate Turret/Main Gun by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD 

Manually Manipulate Turret/Main Gun 

(Gunner) (minutes) * 

M 41 2.24 0.29

F 43 2.82 0.35

Manually Manipulate Turret/Main Gun; 

Traverse Elements (Gunner) (minutes) * 

M 40 0.68 0.11

F 41 0.89 0.17

Manually Manipulate Turret/Main Gun; 

Elevate/Depress Main Gun (Gunner) 

(minutes) *

M 40 1.56 0.22

F 41 1.90 0.22

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

Table B-13. Manually Manipulate Turret/Main Gun by Critical Billet ANOVA and Tukey Test

Metric

F 

Statist

ic (df)

F Test 

PValue 

Comp

arison Diff % Diff

T-Test 

Statisti

c (df)

1-Sided 

P-Value 

2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Manually 

Manipulate 

Turret/Main Gun 

(Gunner) (minutes)

69.35 

(1, 82) < 0.01* F-M 0.58 26.04

% 

8.37 

(80) < 0.01* < 0.01* 0.49 0.67 0.47 0.70

Manually 

Manipulate 

Turret/Main Gun; 

Traverse Elements 

(Gunner) (minutes)

44.94 

(1, 79) < 0.01* F-M 0.21 31.21% 

6.73 

(71) < 0.01* < 0.01* 0.17 0.25 0.16 0.26

Manually 

Manipulate 

Turret/Main Gun; 

Elevate/Depress 

Main Gun (Gunner) 

(minutes)

51.94 

(1, 79) < 0.01* F-M 0.35 22.34

% 

7.21 

(79) < 0.01* < 0.01* 0.29 0.41 0.27 0.43

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

For all tasks above, we proceed with presenting ANOVA results since all samples are 

sufficiently large (n > 30). Additionally, for all tasks, group standard deviations are 

sufficiently similar to satisfy the equal variance assumption for ANOVA. For all tasks 

above, we proceed with presenting ANOVA results since all samples are sufficiently 

large (n > 30). For the overall time required to traverse and elevate the turret, the Male 

group had a mean time of 2.24 minutes, which was statistically significantly faster than 
GCEITF EAR ANNEX B

FOR OFFICIAL USE ONLY 

AUGUST 2015 B-40

the Female group that recorded a mean time of 2.82 minutes. The Male group’s 

26.04% faster mean time when compared to the Female group was statistically 

significant. The other two metrics shown in Table B-13 above, both Traverse Time and 

Elevation Time also show statistical significance when comparing the Male group and 

Female group. The percentage differences equate to degradation in traverse and 

elevation times for Female Group when compared to the Male group. Additionally, the 

Female group for the overall time and traverse time metrics above shows a greater 

variability as shown by the SD column. See Table B-12 and Table B-13 for detailed 

analytical results. 

B.5.5.1.3 Manually Traverse and Elevate the LAV-25 Turret by Critical Billet Contextual 

Comments

This is an individual task solely executed by the Gunner. A LD integration crew could 

have either a male or a female serving as the Gunner. This has the potential to mask

an individual Gunner’s performance using integration level analysis alone. Therefore, it 

was necessary to explore the results of this subtask based on the gender of the Gunner. 

Per MCWP 3-14.1, a Gunner’s ability to conduct Manual Engagements is regularly 

assessed during pre-qualification and qualification tables of gunnery. The speed at 

which a Gunner is able to manipulate the turret to acquire and engage a target directly 

affects the effectiveness, survivability, and lethality of an LAV-25 crew. 

B.5.5.1.4 Manually Traverse and Elevate the LAV-25 Turret by Critical Billet Additional 

Insights

Integrated crews performed noticeably slower during the execution of this subtask. 

Should a vehicle lose power or should the requirement arise to operate without power 

(i.e., night operations on a screen line) a Gunner must be able to rapidly obtain a firing 

solution and quickly engage targets, and slower traverse and elevation times can 

degrade the survivability of the crew and vehicle.

B.5.5.2 Manually Traverse and Elevate the LAV-25 Turret by Critical Billet (Excluding 

Potential Influential Points) 

See B.5.5 for task description.

B.5.5.2.1 Manually Traverse and Elevate the LAV-25 Turret by Critical Billet (Excluding 

Potential Influential Points) Scatterplots

The following scatter plots depict the full data set for this particular task. The data 

points contained inside dark black circles were determined to be data errors and were

excluded from the analysis. The data points contained inside the lightly colored black 

circles were considered to be potential influential points and were excluded from the 

analysis. The first plot shows the full elapsed time to complete the task for the critical 
GCEITF EAR ANNEX B

FOR OFFICIAL USE ONLY 

B-41 AUGUST 2015

billet, displayed by the gender of the Marine executing the task. The second scatter plot 

displays the traverse aspect of the task. 

Figure B-19. Manually Manipulate Turret/Main Gun by Critical Billet (Excluding)

Figure B-20. Manually Manipulate Turret/Main Gun; Traverse by Critical Billet (Excluding)

Critical Billet Gender

Critical Billet Gender
GCEITF EAR ANNEX B

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B.5.5.2.2 Manually Traverse and Elevate the LAV-25 Turret by Critical Billet (Excluding 

Potential Influential Points) Data Tables and Analysis

The tables below summarize the results of the task, Manually Traverse and Elevate the 

LAV-25 Turret. The results are presented by critical billet and exclude potential 

influential points. The first table compares means across metrics and critical billets by 

gender. The second table presents ANOVA and Tukey test results bringing to focus 

those metrics that resulted in statistical significance along with their percentage 

differences.

Table B-14. Manually Manipulate Turret/Main Gun Results by Critical Billet (Excluding)

Metric Integration 

Level 

Sample 

Size Mean SD 

Manually Manipulate Turret/Main Gun 

(Gunner) [excluding potential influential 

points] (minutes) *

M 40 2.22 0.26

F 43 2.82 0.35

Manually Manipulate Turret/Main Gun; 

Traverse Elements (Gunner) [excluding 

potential influential points] (minutes) *

M 39 0.66 0.09

F 41 0.89 0.17

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

Table B-15. Manually Manipulate Turret/Main Gun by Critical Billet (Excluding) ANOVA and Tukey 

Test

Metric

F 

Statist

ic (df)

F Test 

PValue 

Comp

arison

Differ

ence

% 

Differen

ce

TTest 

Stati

stic 

(df)

1-Sided 

P-Value 

2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Manually 

Manipulate 

Turret/Main Gun 

(Gunner) 

[excluding 

potential 

influential points]

(minutes)

79.15 

(1, 81) < 0.01* F-M 0.60 27.22% 8.99 (77) < 0.01* < 0.01*) 0.52 0.69 0.49 0.72

Manually 

Manipulate 

Turret/Main Gun; 

Traverse Elements 

(Gunner) 

[excluding 

potential 

influential points]

(minutes)

54.1 

(1, 78) < 0.01* F-M 0.22 33.27% 7.45 

(63) < 0.01* < 0.01* 0.18 0.26 0.17 0.27

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.. 

For all tasks above, we proceed with presenting ANOVA results since all samples are 

sufficiently large (n > 30). Additionally, for all tasks, group SDs are sufficiently similar to 

satisfy the equal variance assumption for ANOVA. For all tasks above, we proceed with 
GCEITF EAR ANNEX B

FOR OFFICIAL USE ONLY 

B-43 AUGUST 2015

presenting ANOVA results since all samples are sufficiently large (n > 30). For the 

overall time excluding potential influential points required to traverse and elevate the 

turret, the Male group had a mean time of 2.22 minutes, which was statistically 

significantly faster than the Female group that recorded a mean time of 2.82 minutes. 

The Male group’s 27.22% faster mean time when compared to the Female group was 

statistically significant. The traverse time metric shown in Table B-15 also shows 

statistical significance when comparing the Male group and Female group. Elevation 

elapsed time results did not contain potential influential points and are excluded. 

Additionally, the Female group for the overall time and traverse time metrics above 

shows a greater variability as shown by the SD column. See Table B-14 and Table 

B-15 for detailed analytical results. 

B.5.5.2.3 Manually Traverse and Elevate the LAV-25 Turret by Critical Billet (Excluding 

Potential Influential Points) Additional Insights

Observations after excluding potential influential results remain largely the same.

B.5.5.3 Manually Traverse and Elevate the LAV-25 Turret by Integration Level

See B.5.5 for task description.

B.5.5.3.1 Manually Traverse and Elevate the LAV-25 Turret by Integration Level 

Scatterplots

The scatter plots below display the results of the various integration level elapsed times 

to complete the task. 
GCEITF EAR ANNEX B

FOR OFFICIAL USE ONLY 

AUGUST 2015 B-44

Figure B-21. Manually Manipulate Turret/Main Gun by Integration Level

Figure B-22. Manually Manipulate Turret/Main Gun; Traverse by Integration Level
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Figure B-23. Manually Manipulate Turret/Main Gun; Elevate/Depress by Integration Level

B.5.5.3.2 Manually Traverse and Elevate the LAV-25 Turret by Integration Level Data 

Tables and Analysis

The tables below summarize the results of the task, Manually Traverse and Elevate the 

LAV-25 Turret by integration level. The first table compares means across metrics and 

integration levels. The second table presents ANOVA and Tukey test results bringing to 

focus those metrics that resulted in statistical significance along with their percentage 

differences.

Table B-16. Manually Manipulate Turret/Main Gun by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Manually Manipulate Turret/Main Gun 

(minutes) * 

C 29 2.22 0.25

LD 27 2.51 0.43

HD 28 2.89 0.31

Manually Manipulate Turret/Main Gun; 

Traverse Elements (minutes) * 

C 28 0.68 0.11

LD 27 0.75 0.17

HD 26 0.92 0.15

Manually Manipulate Turret/Main Gun; 

Elevate/Depress Main Gun (minutes) * 

C 28 1.53 0.18

LD 27 1.76 0.28

HD 26 1.93 0.20

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test

Integration Level
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Table B-17. Manually Manipulate Turret/Main Gun by Integration Level ANOVA and Tukey Test

Metric

F 

Statist

ic (df)

F Test 

PValue 

Comp

arison

Differ

ence

% 

Differen

ce

P-Value 80 %

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Manually 

Manipulate 

Turret/Main Gun 

(minutes)

28.4 

(2, 81) < 0.01*

LD-C 0.29 13.25% < 0.01* 0.14 0.45 0.11 0.48

HD-C 0.67 30.19% < 0.01* 0.52 0.82 0.48 0.86

HD-LD 0.38 14.96% < 0.01* 0.22 0.53 0.19 0.56

Manually 

Manipulate 

Turret/Main Gun; 

Traverse Elements 

(minutes)

17.87 

(2, 78) < 0.01*

LD-C 0.07 10.67% 0.17 0.00 0.14 -0.01 0.16

HD-C 0.24 34.57% < 0.01* 0.17 0.31 0.15 0.32

HD-LD 0.16 21.59% < 0.01* 0.09 0.23 0.08 0.25

Manually 

Manipulate 

Turret/Main Gun; 

Elevate/Depress 

Main Gun (minutes)

21.45 

(2, 78) < 0.01*

LD-C 0.23 15.06% < 0.01* 0.12 0.34 0.10 0.36

HD-C 0.40 26.24% < 0.01* 0.29 0.51 0.27 0.53

HD-LD 0.17 9.72% 0.02* 0.06 0.28 0.04 0.30

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test

Statistical analysis included analysis of variance (ANOVA) and multiple comparisons 

using Tukey tests. For all tasks above, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA. For the overall time to manipulate 

main gun, the C, LD, and HD groups are all normally distributed with Shapiro-Wilk Test 

p-values of 0.03, 0.07, and 0.74, respectively. For the traverse elements of manipulate 

main gun, the C group is not normally distributed with Shapiro-Wilk Test p-values of less 

than 0.01, while the LD and HD groups are normally distributed with p-values of 0.12 

and 0.73, respectively. We proceed with presenting ANOVA results, since they are 

confirmed by a Kruskal-Wallis Test (p-value < 0.01). For the elevate/depress portion of 

manipulate main gun, the C, LD, and HD groups are all normally distributed with 

Shapiro-Wilk Test p-values of 0.61, 0.25, and 0.18, respectively.

For the overall time required to manually manipulate the turret, the C group had a mean 

time of 2.22 minutes, which was statistically significantly faster than the HD groups that

recorded a mean time of 2.89 minutes. The C group’s 30.19% faster mean time when 

compared to the HD group was statistically significant. The two additional metrics 

traverse time and elevation time shown in Table B-16 above also shows a statistical 

significance when comparing the HD group to the C group and the LD group. The

34.57% and 26.24% percentage differences equate to degradation in traverse time and 

elevation time, respectively, for HD groups when compared to the C group. 

Additionally, HD and LD groups for the three metrics above show greater variability than 

the C group as shown by the SD column. See Table B-16 and Table B-17 for detailed 

analytical results.
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B.5.5.3.3 Manually Traverse and Elevate the LAV-25 Turret by Integration Level Additional 

Insights

Observations when examined by integration level remain largely the same as by critical 

billet, although the results in the low-density integration group are less apparent.

B.5.5.4 Manually Traverse and Elevate the LAV-25 Turret by Integration Level (Excluding 

Potential Influential Points) 

See B.5.5 for task description.

B.5.5.4.1 Manually Traverse and Elevate the LAV-25 Turret by Integration Level 

(Excluding Potential Influential Points) Scatterplots

The scatter plots below display the results of integration level elapsed times to complete 

the Manually Manipulate Turret/Main Gun task. The data points contained inside dark 

black circles were determined to be data errors and were excluded from the analysis. 

Lightly colored black circles were determined to be potential influential points and were 

excluded from the analysis. 

Figure B-24. Manually Manipulate Turret/Main Gun by Integration Level (Excluding)

Integration Level
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AUGUST 2015 B-48

Figure B-25. Manually Manipulate Turret/Main Gun; Traverse by Integration Level (Excluding)

B.5.5.4.2 Manually Traverse and Elevate the LAV-25 Turret by Integration Level 

(Excluding Potential Influential Points) Data Table and Analysis

The tables below summarize the results of the Manually Manipulate Turret/Main Gun 

task by integration level. Table B-18 compares means across metrics and integration 

levels. Table B-19 presents ANOVA and Tukey test results bringing to focus those 

metrics that resulted in statistical significance along with their percentage differences.

Table B-18. Manually Manipulate Turret/Main Gun by Integration Level (Excluding)

Metric Integration 

Level 

Sample 

Size Mean SD 

Manually Manipulate Turret/Main Gun

[excluding potential influential points] 

(minutes) * 

C 28 2.19 0.19

LD 27 2.51 0.43

HD 28 2.89 0.31

Manually Manipulate Turret/Main Gun; 

Traverse Elements [excluding potential 

influential points] (minutes) * 

C 27 0.67 0.08

LD 27 0.75 0.17

HD 26 0.92 0.15

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 
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Table B-19. Manually Manipulate Turret/Main Gun by Integration Level (Excluding) ANOVA and 

Welch’s T-Test

Metric

F 

Statist

ic (df)

F Test 

P-Value 

Comp

arison

Differ

ence

% 

Differen

ce

P-Value 80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Manually 

Manipulate 

Turret/Main Gun 

[excluding 

potential 

influential points] 

(minutes)

52.37

(2, 48) < 0.01††

LD-C 0.32 14.82% < 0.01†† 0.21 0.44 0.17 0.48

HD-C 0.70 31.99% < 0.01†† 0.61 0.79 0.58 0.82

HD-LD 0.38 14.96% < 0.01†† 0.24 0.51 0.21 0.55

Manually 

Manipulate 

Turret/Main Gun; 

Traverse 

Elements 

[excluding 

influential points]

(minutes)

27.99

(2, 44) < 0.01††

LD-C 0.09 13.14% 0.02†† 0.04 0.14 0.03 0.15

HD-C 0.25 37.57% < 0.01†† 0.21 0.29 0.19 0.31

HD-LD 0.16 21.59% < 0.01†† 0.10 0.22 0.09 0.24

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances). For comparisons utilizing robust 

ANOVA, Tukey confidence intervals have been replaced by individual Welch’s T-tests with p-values compared to a Bonferroni 

corrected threshold.

Statistical analysis included ANOVA and multiple comparisons using Tukey tests. For 

the overall time to manipulate main gun, the C, LD, and HD groups are all normally 

distributed with Shapiro-Wilk Test p-values of 0.40, 0.07, and 0.74, respectively. Since 

the standard deviation of the LD group is more than twice that of the C group, we 

recommend using the robust ANOVA results presented above.

For the traverse elements of manipulate main gun, the C, LD, and HD groups are all 

normally distributed with Shapiro-Wilk Test p-values of 0.75, 0.13, and 0.73, 

respectively. Since the standard deviation of the LD group is more than twice that of the 

C group, we recommend using the robust ANOVA results presented above. 

When excluding potential influential points for the overall time required to manually 

manipulate the turret, the C group had a mean time of 2.19 minutes, which was 

statistically significantly faster than the HD groups that recorded a mean time of 2.89

minutes. The C group’s 31.99% faster mean time when compared to the HD group was 

statistically significant. The additional traverse time metric shown in Table B-19 above 

also shows a statistical significance when comparing the HD group to the C group and 

the LD group. The 37.57% percentage difference equates to degradation in traverse 

time for HD groups when compared to the C group. The elevation time metric 

contained no potential influential points and is excluded. Additionally, HD and LD 

groups for both metrics above show greater variability than the C group as shown by the 

SD column. See Table B-18 and Table B-19 for detailed analytical results
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AUGUST 2015 B-50

B.5.5.4.3 Manually Traverse and Elevate the LAV-25 Turret by Integration Level 

(Excluding Potential Influential Points) Additional Insights

Observations after excluding potential influential results remain largely the same.

B.5.6 Prep the M242 Main Gun Overview

This subtask required the LAV-25 Gunner, without assistance, to remove, disassemble, 

reassemble and install the M242 Bushmaster Cannon, weighing approximately 263 lb. 

If, after 30 minutes, the Gunner was unable to perform this task, the Driver was then 

able to assist with the process. Based on the LAV Gunnery Skills Test standards listed 

in MCWP 3-14.1, a Gunner has 30 minutes to disassemble and reassemble the main 

gun. Proficient Gunners are expected to far exceed this standard. Disassembly was 

achieved when the Gunner disassembled the bolt and track assembly and removed the 

barrel from the weapon system. In many situations, the other members of the crew will 

be unavailable to assist the Gunner in manipulation and troubleshooting of the main 

gun. A Gunner’s ability to rapidly troubleshoot, identify, and rectify any issues or a 

malfunction with the primary weapon system of the platform is absolutely vital to the 

effectiveness and survivability of the vehicle crew. Gunners were evaluated on the time 

required to disassemble and reassemble the weapon system.

The data collected for this task was analyzed both by critical billet and by integration 

level. 

B.5.6.1 Prep the M242 Main Gun by Critical Billet

Disassembly and reassembly of the M242 Main Gun is an individual task solely 

executed by the Gunner. Only after the Gunner exceeded 30 minutes was any 

assistance allowed for this task. As the low-density integration crew could have either a 

male or female serving as the Gunner, this group masks an individual Gunner’s 

performance. It is therefore beneficial to explore the results of this subtask based on 

the gender of the Gunner.

B.5.6.1.1 Prep the M242 Main Gun by Critical Billet Scatterplots

The scatter plots below display the results to complete the Prep M242 Main Gun by Gun 

task by critical billet. The data points contained inside dark black circles were 

determined to be data errors and were excluded from the analysis.
GCEITF EAR ANNEX B

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B-51 AUGUST 2015

Figure B-26. Prep M242 Main Gun by Critical Billet

Figure B-27. Prep M242 Main Gun; Disassembly by Critical Billet

Critical Billet Gender

Critical Billet Gender
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Figure B-28. Prep M242 Main Gun; Reassembly by Critical Billet

B.5.6.1.2 Prep the M242 Main Gun by Critical Billet Data Table and Analysis

The tables below summarize the results of the task by critical billet. Table B-20

compares means across metrics and integration levels. Table B-21 presents ANOVA 

and Tukey test results bringing to focus those metrics that resulted in statistical 

significance along with their percentage differences.

Table B-20. Prep M242 Main Gun by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD 

Prep M242 Main Gun (Gunner) (minutes) * 

M 27 8.99 2.68

F 27 11.06 5.06

Prep M242 Main Gun; Disassembly 

(Gunner) (minutes)

M 39 5.43 1.72

F 43 5.49 1.46

Prep M242 Main Gun; Re-assembly 

(Gunner) (minutes) * 

M 26 3.76 1.46

F 27 6.06 4.41

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

Critical Billet Gender
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Table B-21. Prep M242 Main Gun by Critical Billet ANOVA

Metric

F 

Statist

ic (df)

F Test 

PValue 

Comp

arison

Differ

ence

% 

Differen

ce

TTest 

Stati

stic 

(df)

1-Sided 

P-Value 

2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Prep M242 Main 

Gun (Gunner) 

(minutes)

3.54 

(1, 52) 0.07* F-M 2.07 23.08% 1.88 

(40) 0.03* 0.07* 0.64 3.51 0.22 3.93

Prep M242 Main 

Gun; Disassembly 

(Gunner) (minutes)

0.03 

(1, 80) 0.87 F-M 0.06 1.09% 0.17 

(75) 0.43 0.87 -0.40 0.52 -0.53 0.65

Prep M242 Main 

Gun; Re-assembly 

(Gunner) (minutes)

6.57

(1, 32) 0.02†† F-M 2.30 61.01% 2.56 

(32) < 0.01* 0.02* 1.12 3.47 0.78 3.81

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.

†Indicates statistical significance using a robust ANOVA (accounts for unequal variances).

For the overall time to prep the M242, the M and F groups are not normally distributed 

with Shapiro-Wilk p-values of less than 0.01. We proceed with presenting ANOVA 

results since they are confirmed by a Mann-Whitney Test (p-value = 0.08). For 

disassembly time of M242, we proceed with presenting ANOVA results since all 

samples are sufficiently large (n > 30). For the reassembly time of the M242, the M and 

F groups are not normally distributed with Shapiro-Wilk p-values of less than 0.01. 

Since the standard deviation of the F group is more than twice that of the M group, we 

recommend using robust ANOVA presented above. We proceed with presenting 

ANOVA results, since they are confirmed by a Mann-Whitney Test (p-value < 0.01).

For the overall time required for disassembly and reassembly, the Male group had a 

mean time of 8.99 minutes, which was statistically significantly faster than the Female 

group that recorded a mean time of 11.06 minutes. The Male group’s 23.08% faster 

mean time when compared to the Female group was statistically significant. The 

reassembly time metric also shows statistical significance when comparing the Male 

group to the Female group. The percentage differences equate to degradation in 

reassembly time for the Female Group when compared to the Male group. Additionally, 

the Female group above shows a greater variability for the overall time and reassembly 

time metrics as shown by the SD column; the Female group shows less variability for 

the disassembly time metric. See Table B-20 and Table B-21 for detailed analytical 

results. 

B.5.6.1.3 Prep the M242 Main Gun by Critical Billet Additional Insights

As the primary weapon system of the platform, upkeep and employment of the 25mm 

cannon is a Gunner’s central role. When observing breakout times, males and females 

performed nearly identically during disassembly of the weapon system. During 

reassembly, there was a large disparity between male and female gunners. 
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Reassembly requires the manipulation of heavy components by a single individual in a 

confined space. Longer times to ensure primary weapon system functionality have the 

potential to impede operations, especially when the LAV-25 is operating in a direct fire 

or support by fire role. 

B.5.6.2 Prep the M242 Main Gun by Critical Billet (Excluding Potential Influential Points)

See Section B.5.6 for task description.

B.5.6.2.1 Prep the M242 Main Gun by Critical Billet (Excluding Potential Influential Points)

Scatterplots

The scatter plots below display the results to complete the Prep M242 Main Gun task by 

critical billet. The data points contained inside dark black circles were determined to be 

data errors and were excluded from the analysis.

Figure B-29. Prep M242 Main Gun by Critical Billet (Excluding)

Critical Billet Gender
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Figure B-30. Prep M242 Main Gun; Disassembly by Critical Billet (Excluding)

Figure B-31. Prep M242 Main Gun; Reassembly by Critical Billet (Excluding)

B.5.6.2.2 Prep the M242 Main Gun by Critical Billet (Excluding Potential Influential Points) 

Data Table and Analysis

The tables below summarize the results of the task by critical billet. Table B-22

compares means across metrics and integration levels. Table B-23 presents ANOVA 

Critical Billet Gender

Critical Billet Gender
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and Tukey test results bringing to focus those metrics that resulted in statistical 

significance along with their percentage differences.

Table B-22. Prep M242 Main Gun by Critical Billet (Excluding)

Metric Integration 

Level 

Sample 

Size Mean SD 

Prep M242 Main Gun (Gunner) [excluding 

potential influential points] (minutes) * 

M 26 8.68 2.18

F 25 9.98 2.64

Prep M242 Main Gun; Disassembly 

(Gunner) [excluding potential influential 

points] (minutes)

M 38 5.30 1.54

F 42 5.47 1.47

Prep M242 Main Gun; Re-assembly 

(Gunner) [excluding potential influential 

points] (minutes) *

M 25 3.56 1.01

F 25 5.07 2.16

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

Table B-23. Prep M242 Main Gun by Critical Billet (Excluding) ANOVA

Metric

F 

Statist

ic (df)

F Test 

PValue

Comp

arison Diff % Diff

T-Test 

Statisti

c (df)

1-Sided 

P-Value 

2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Prep M242 Main 

Gun (Gunner) 

[excluding 

potential 

influential points]

(minutes)

3.67 

(1, 49) 0.06* F-M 1.30 14.95% 1.91 

(47) 0.03* 0.06* 0.41 2.18 0.16 2.44

Prep M242 Main 

Gun; Disassembly 

(Gunner) 

[excluding 

potential 

influential points] 

(minutes)

0.26 

(1, 78) 0.61 F-M 0.17 3.23% 0.51 

(76) 0.31 0.61 -0.26 0.61 -0.39 0.73

Prep M242 Main 

Gun; Re-assembly 

(Gunner)

[excluding 

potential 

influential points] 

(minutes)

10.13

(1, 34)

< 

0.01†† F-M 1.52 42.72% 3.18 

(34) < 0.01* < 0.01* 0.90 2.14 0.71 2.33

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances)

For the overall time to prep the M242, the M and F groups are normally distributed with 

Shapiro-Wilk p-values of 0.03 and 0.38, respectively. For disassembly time of M242, 

we proceed with presenting ANOVA results since all samples are sufficiently large (n > 

30). For the reassembly time of the M242, the M group is not normally distributed with 

Shapiro-Wilk p-value of less than 0.01, while the F group is normally distributed with pvalue of 0.02. Since the standard deviation of the F group is more than twice that of the 

M group, we recommend using robust ANOVA presented above. We proceed with 
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presenting ANOVA results, since they are confirmed by a Mann-Whitney Test (p-value < 

0.01).

When excluding potential influential results for the overall time required while 

disassembling and reassembling the main gun, the Male group had a mean time of 8.68

minutes, which was statistically significantly faster than the Female group that recorded 

a mean time of 9.98 minutes. The Male group’s 14.95% faster mean time when 

compared to the Female group was statistically significant. The reassembly time metric

also shows statistical significance when comparing the Male group and Female group. 

The percentage differences equate to degradation in reassembly time for the Female 

Group when compared to the Male group. The Female group above shows a greater 

variability for the overall time and reassembly time metrics as shown by the SD column; 

the Female group shows less variability for the disassembly time metric. See Table 

B-22 and Table B-23 for detailed analytical results. 

B.5.6.2.3 Prep the M242 Main Gun by Critical Billet (Excluding Potential Influential Points) 

Additional Insights

Observations after excluding potential influential results remain largely the same. 

B.5.6.3 Prepare the M242 Main Gun by Integration Level

See Section B.5.6 for task description.

B.5.6.3.1 Prepare the M242 Main Gun by Integration Level Scatterplots

The scatter plots below display the results to complete the Prep M242 Main Gun task by 

integration level. The data points contained inside dark black circles were determined 

to be data errors and were excluded from the analysis.
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Figure B-32. Prep M242 Main Gun by Integration Level

Figure B-33. Prep M242 Main Gun; Disassembly by Integration Level
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Figure B-34. Prep M242 Main Gun; Reassembly by Integration Level

B.5.6.3.2 Prepare the M242 Main Gun by Integration Level Data Table and Analysis

The tables below summarize the results of the task by integration level. Table B-24

compares means across metrics and integration levels. Table B-25 presents ANOVA 

and Tukey test results bringing to focus those metrics that resulted in statistical 

significance along with their percentage differences.

Table B-24. Prep M242 Main Gun by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Prep M242 Main Gun (minutes)

C 18 8.75 3.11

LD 18 9.83 2.78

HD 18 11.50 5.67

Prep M242 Main Gun; Disassembly 

(minutes)

C 27 5.29 1.79

LD 27 5.28 1.47

HD 28 5.81 1.45

Prep M242 Main Gun; Re-assembly 

(minutes)

C 17 3.70 1.71

LD 18 4.99 2.63

HD 18 6.04 4.95

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.
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Table B-25. Prep M242 Main Gun by Integration Level ANOVA and Tukey Test

Metric

F 

Statist

ic (df)

F Test 

PValue

Comp

arison

Differ

ence

% 

Differen

ce

P-Value 80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Prep M242 Main 

Gun (minutes) †

1.72

(2, 32) 0.20

LD-C 1.08 12.38% 0.12 0.28 -0.20 2.37 -0.58

HD-C 2.75 31.48% 0.04 0.08 0.75 4.76 0.16

HD-LD 1.67 16.99% 0.36 0.27 -0.29 3.63 -0.87

Prep M242 Main 

Gun; Disassembly 

(minutes)

1.02 

(2, 79) 0.36

LD-C -0.02 -0.30% 1.00 -0.76 0.73 -0.91 0.88

HD-C 0.52 9.77% 0.45 -0.22 1.25 -0.37 1.40

HD-LD 0.53 10.10% 0.43 -0.20 1.27 -0.35 1.42

Prep M242 Main 

Gun; Re-assembly 

(minutes) †

2.07 

(2, 50) 0.02*

LD-C 1.29 34.87% 0.02 0.35 1.30 0.22 1.48

HD-C 2.34 63.30% 0.01 0.78 1.92 0.62 2.12

HD-LD 1.05 21.07% 0.39 -0.32 1.17 -0.63 1.33

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between integration levels according to ANOVA or a non-parametric equivalent test.

†Results presented are from a Mann-Whitney non-parametric test due to non-normality.

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances). For comparisons 

utilizing robust ANOVA, Tukey confidence intervals have been replaced by individual Welch’s T-tests with p-values 

compared to a Bonferroni corrected threshold.

For the overall time to prep the M242, the C and LD groups are not normally distributed

with Shapiro-Wilk Test p-values of less than 0.01, while the HD group is normally 

distributed with p-value of 0.01, respectively. Since the standard deviation of the HD 

group is more than twice that of the LD group, we recommend using the robust ANOVA 

results presented above. We proceed with presenting robust ANOVA results since they 

are confirmed by a Kruskal-Wallis Test (p-value = 0.01). We proceed with presenting 

ANOVA results since they are confirmed by a Kruskal-Wallis Test (p-value = 0.01). For 

the disassembly portion of the time, the C, LD, and HD groups are normally distributed 

with Shapiro-Wilk Test p-values of 0.08, 0.33, and 0.63, respectively. For the assembly 

portion of the time, the C, LD, and HD groups are not normally distributed with ShapiroWilk Test p-values of less than 0.01. Because of lack of normality, we recommend 

using the results of the Kruskal-Wallis test presented in the table above.

Statistical analysis included analysis of variance (ANOVA) and multiple comparisons 

using Tukey tests. For the overall time required to disassemble and assemble the main 

gun the C group had a mean time of 8.75 minutes, which was faster than the HD groups 

that recorded a mean time of 11.50 minutes. However, the C group’s 12.38% faster 

mean time when compared to the HD group was not statistically significant. No metric 

in Table B-25 shows a statistical significance when comparing the HD group to the C

group and the LD group. See Table B-24 and Table B-25 for detailed analytical results.

B.5.6.3.3 Prepare the M242 Main Gun by Integration Level Additional Insights

Observations when examined by integration level in the low-density group are less 

apparent, reveal a variance increase, and fall below the threshold required for statistical 

significance. The analysis above shows the masking effect that analysis by integration 

level alone has on the results. When examining specific tasks for LAV gunnery it is 
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imperative to consider analysis by critical billet as it exposes the masking of analysis by 

the integration level alone.

B.5.6.4 Prepare the M242 Main Gun by Integration Level (Excluding Potential Influential 

Points) 

See B.5.6 for task description.

B.5.6.4.1 Prepare the M242 Main Gun by Integration Level (Excluding Potential Influential 

Points) Scatterplots

The scatter plots below display the results to complete the Prep M242 Main Gun task by 

integration level. The data points in lightly colored black circles were determined to be 

potential influential points. They were excluded from the analysis for this sub-section. 

The data points contained inside dark black circles were determined to be data errors 

and were excluded from the analysis.

Figure B-35. Prep M242 Main Gun by Integration Level (Excluding)
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Figure B-36. Prep M242 Main Gun; Disassembly by Integration Level (Excluding)

Figure B-37. Prep M242 Main Gun; Reassembly by Integration Level (Excluding)
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B.5.6.4.2 Prepare the M242 Main Gun by Integration Level (Excluding Potential Influential 

Points) Data Table and Analysis

The tables below summarize the results of the Prep M242 Main Gun task by integration 

level. The first table compares means across metrics and integration levels. The 

second table presents ANOVA and Tukey test results bringing to focus those metrics 

that resulted in statistical significance along with their percentage differences.

Table B-26. Prep M242 Main Gun by Integration Level (Excluding)

Metric Integration 

Level 

Sample 

Size Mean SD 

Prep M242 Main Gun [excluding potential 

influential points] (minutes) * 

C 17 8.26 2.38

LD 17 9.37 2.06

HD 17 10.31 2.66

Prep M242 Main Gun; Disassembly

[excluding potential influential points] 

(minutes)

C 26 5.10 1.52

LD 27 5.28 1.47

HD 27 5.80 1.47

Prep M242 Main Gun; Re-assembly 

[excluding potential influential points] 

(minutes) * 

C 16 3.37 1.06

LD 17 4.54 1.84

HD 17 4.98 2.11

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

Table B-27. Prep M242 Main Gun by Integration Level (Excluding) ANOVA and Tukey Test

Metric

F 

Statist

ic (df)

F Test 

PValue

Comp

arison

Differ

ence

% 

Differen

ce

P-Value 80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Prep M242 Main 

Gun [excluding 

influential points] 

(minutes)

3.17 

(2, 48) 0.05*

LD-C 1.12 13.51% 0.37 -0.31 2.54 -0.60 2.83

HD-C 2.05 24.85% 0.04* 0.63 3.47 0.34 3.77

HD-LD 0.94 9.99% 0.49 -0.49 2.36 -0.78 2.65

Prep M242 Main 

Gun; Disassembly 

[excluding 

influential points] 

(minutes)

1.58 

(2, 48) 0.21

LD-C 0.18 3.48% 0.90 -0.53 0.88 -0.67 1.03

HD-C 0.70 13.67% 0.21 -0.01 1.40 -0.15 1.55

HD-LD 0.52 9.85% 0.41 -0.18 1.22 -0.32 1.36

Prep M242 Main 

Gun; Re-assembly 

[excluding 

influential points] 

(minutes)

3.73 

(2, 47) 0.03*

LD-C 1.17 34.65% 0.14 0.11 2.23 -0.11 2.44

HD-C 1.61 47.82% 0.03* 0.55 2.67 0.33 2.89

HD-LD 0.44 9.79% 0.74 -0.60 1.49 -0.81 1.70

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.

For all tasks above, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA. For the overall time to prep the M242, the C group is

not normally distributed with Shapiro-Wilk Test p-values of less than 0.01, while the LD 

and HD groups are normally distributed with p-values of 0.97 and 0.66, respectively. 

We proceed with presenting ANOVA results since they are confirmed by a Kruskal-
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Wallis Test (p-value = 0.05). For the disassembly portion of the time, the C, LD, and HD 

group data are normally distributed with Shapiro-Wilk Test p-values of 0.09, 0.33, and 

0.71, respectively. For the assembly portion of the time, the C and LD groups are not 

normally distributed with Shapiro-Wilk Test p-values of less than 0.01, while the HD 

group is normally distributed with a p-value of 0.06. We proceed with presenting 

ANOVA results since they are confirmed by a Kruskal-Wallis Test (p-value = 0.01).

Statistical analysis included analysis of variance (ANOVA) and multiple comparisons 

using Tukey tests. When excluding potential influential results for the overall time 

required disassembling and assembling the main gun, the C group had a mean time of 

8.26 minutes, which was statistically significantly faster than the LD and HD groups that

recorded a mean time of 9.37 and 10.31 minutes, respectively. The C group’s 24.85% 

faster mean time when compared to the HD group was statistically significant. The 

reassembly time metric shown in Table B-27 also shows a statistical significance when 

comparing the HD group to the C group. The 47.82% percentage difference equates to 

degradation in reassembly time for HD groups when compared to the C group. See 

Table B-26 and Table B-27 for detailed analytical results. 

B.5.6.4.3 Prepare the M242 Main Gun by Integration Level (Excluding Potential Influential 

Points) Additional Insights

Observations after excluding potential influential results remain largely the same.

B.5.7 Load and Stow Additional Ammunition Overview

This subtask required the LAV-25 crew to load and stow a full complement of 25 mm 

ammunition into the vehicle. An LAV-25 can hold 150 rounds of High Explosive (HE) 

ammunition and 60 rounds of Armor Piercing (AP) ammunition linked and prepared in 

the vehicle’s HE and AP ready-boxes. Two additional full uploads of each ammo type is 

also stored within the vehicle in ammunition cans for a total of 180 AP and 450 HE 

rounds. Dummy rounds weighing just over a pound each were used to simulate the 

linked rounds. These dummy rounds were broken out of their containers and linked 

prior to the start of the subtask. Crews had a tendency to break apart the large belt of 

150 HE rounds to more rapidly upload the rounds into the vehicle. The two additional 

uploads were comprised of ten cans of HE training rounds, each weighing 50 lbs., and 

four cans of AP training rounds, each weighing 55 lb. Without assistance, a crew must 

be able to properly load and stow their ready rounds and additional uploads on their 

vehicle as part of normal combat preparation. Prior to any typical operation, a crew 

would depart carrying a full complement of ammunition.
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B.5.7.1 Load and Stow Additional Ammunition by Integration Level

B.5.7.1.1 Load and Stow Additional Ammunition by Integration Level Scatterplots

The scatter plots below display the results to complete the Load and Stow Additional 

Ammo task by integration level. No outliers were identified for this sub-section. 

Figure B-38. Load and Stow Additional Ammo by Integration Level

B.5.7.1.2 Load and Stow Additional Ammunition by Integration Level Data Table and 

Analysis

The tables below summarize the results of the Load and Stow Additional Ammo by 

integration level. The first table compares means across metrics and integration levels. 

The second table presents ANOVA and Tukey test results bringing to focus those 

metrics that resulted in statistical significance along with their percentage differences. 

Table B-28. Load and Stow Additional Ammo by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Load & Stow Additional Ammo (minutes)

C 29 8.84 2.90

LD 27 8.26 1.39

HD 28 9.68 3.18

*Indicates there is a statistically significant difference in a two-sided hypothesis test between integration levels 

according to ANOVA or a non-parametric equivalent test.
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Table B-29. Load and Stow Additional Ammo ANOVA and Tukey Test

Metric

F 

Statist

ic (df)

F Test 

PValue

Comp

arison

Differ

ence

% 

Differen

ce

2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Load & Stow 

Additional Ammo 

(minutes)

2.47

(2, 48) 0.10††

LD-C -0.58 -6.56% 0.34 -1.36 0.20 -1.59 0.43

HD-C 0.84 9.51% 0.30 -0.21 1.89 -0.51 2.19

HD-LD 1.42 17.20% 0.04 0.56 2.28 0.31 2.53

*Indicates there is a statistically significant difference in a two-sided hypothesis test between integration levels 

according to ANOVA or a non-parametric equivalent test. 

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances). For comparisons 

utilizing robust ANOVA, Tukey confidence intervals have been replaced by individual Welch’s T-tests with p-values 

compared to a Bonferroni corrected threshold

For the time to load and stow additional ammo, the C and LD groups are normally 

distributed with Shapiro-Wilk Test p-values of 0.03 and 0.83, respectively, while the HD 

group is not normally distributed with a p-value of less than 0.01. Since the standard 

deviation of the HD group is more than twice that of the LD group, we recommend using 

the robust ANOVA results presented above. We proceed with presenting robust 

ANOVA results since they are confirmed by a Kruskal-Wallis Test (p-value = 0.22).

Statistical analysis included analysis of variance (ANOVA) and multiple comparisons 

using Tukey tests. For the overall time load and stow ammunition the C group had a 

mean time of 8.84 minutes, which was slower than the LD group that recorded a time of 

8.26 minutes and faster than the HD group that recorded a time of 9.68 minutes. No 

results were statistically significant. Additionally, the HD group shows greater variability

when compared to the C and LD groups as shown by the SD column; the LD group 

shows the lowest variability. See Table B-28 and Table B-29 for detailed analytical 

results. 

B.5.7.1.3 Load and Stow Additional Ammunition by Integration Level Contextual 

Comments

The observed output from this task contained a high level of variance, making it difficult 

to draw a definitive conclusion. Like maintenance tasks, in real-world operations, longer 

times can translate into increased times required to prepare for a mission. 

B.5.7.2 Load and Stow Additional Ammunition by Integration Level (Excluding Potential 

Influential Points) Overview

See B.5.7 for task description. 

B.5.7.2.1 Load and Stow Additional Ammunition by Integration Level (Excluding Potential 

Influential Points) Scatterplots

The scatter plots below display the results to complete the Load and Stow Additional 

Ammo task by integration level. The data points contained inside lightly colored black 
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circles were determined to be potential influential points; they are excluded from the 

analysis. No outliers were identified for this sub-section.

Figure B-39. Load and Stow Additional Ammo by Integration Level (Excluding)

B.5.7.2.2 Load and Stow Additional Ammunition by Integration Level (Excluding Potential 

Influential Points) Data Table and Analysis

The tables below summarize the results of the Load and Stow Additional Ammo task. 

This portion of the analysis excluded potential influential points. The first table 

compares means across metrics and integration levels. The second table presents 

ANOVA and Tukey test results bringing to focus those metrics that resulted in statistical 

significance along with their percentage differences.

Table B-30. Load and Stow Additional Ammo by Integration Level (Excluding)

Metric Integration 

Level 

Sample 

Size Mean SD

Load & Stow Additional Ammo 

[excluding potential influential 

points] (minutes)

C 27 8.33 2.28

LD 27 8.26 1.39

HD 27 9.24 2.17

*Indicates there is a statistically significant difference in a two-sided hypothesis test between integration levels 

according to ANOVA or a non-parametric equivalent test.
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Table B-31. Load and Stow Additional Ammo by Integration Level (Excluding)

Metric

F 

Statisti

c (df)

F Test 

PValue

Compa

rison Diff % Diff

2-

Sided 

PValue

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UC

B 

Load & Stow 

Additional 

Ammo 

[excluding 

potential 

influential 

points] 

(minutes)

7.95 (2, 

78) 0.14

LD-C -0.07 -0.87% 0.99 -1.01 0.86 -1.20 1.05

HD-C 0.90 10.82% 0.22 -0.03 1.84 -0.22 2.03

HD-LD 0.97 11.79% 0.18 0.04 1.91 -0.15 2.10

*Indicates there is a statistically significant difference in a two-sided hypothesis test between integration levels 

according to ANOVA or a non-parametric equivalent test.

For the task above, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA. For the time to load and stow additional ammo, the C, 

LD, and HD groups are normally distributed with Shapiro-Wilk p-values of 0.16, 0.83, 

and 0.31, respectively.

Statistical analysis included ANOVA and multiple comparisons using Tukey tests. 

When excluding potential influential results for the overall time required to load and stow 

additional ammunition, the C group had a mean time of 8.33 minutes, which was slower 

than the LD group mean time of 8.26 minutes, but faster than the HD group mean time 

of 9.24 minutes. No comparisons revealed statistically significant results. Additionally, 

the C group shows a greater variability when compared to the LD and HD groups as 

shown by the SD column. See Table B-30 and Table B-31 for detailed analytical 

results. 

B.5.7.2.3 Load and Stow Additional Ammunition by Integration Level (Excluding Potential 

Influential Points) Additional Insights

Observations after excluding potential influential results remain largely the same.

B.5.8 Engage Main Gun Targets Overview

The main gun engagements portion of the live-fire trial day were conducted as crew 

events, with a large amount of the physical workload placed on the Gunner, designated 

below as the critical billet. Live-fire engagements were adapted from table VI gunnery 

qualification engagements found in MCWP 3-14.1, which all vehicle crews are required 

to fire to achieve qualified status. The culmination of a crew’s proficiency is their ability 

during gunnery to qualify and excel at identifying, engaging, and destroying targets. 

Gunnery engagements, though not nearly as physically demanding as many of the 

maintenance and prep for combat tasks, reveal the knowledge and proficiency of a 

Marine as it pertains to their role as a crewman.
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B.5.9 Main Gun Remedial Action Overview

This subtask required the LAV-25 Gunner, with assistance from the VC and Driver, to 

conduct remedial action on the main gun. It is similar in nature to the Prepare the M242 

Main Gun prep for combat task. The crew must download the ammunition from the 

main gun, remove the feeder assembly and ensure it was correctly timed, and then 

reassemble the weapon system and upload ammunition. The Vehicle Commander and 

Driver were able to assist in any way, but due to the nature of crew responsibilities and 

the position of the gun in relation to the crew members, the Gunner bore most of the 

physical workload. Disassembly was achieved when the Gunner removed the feeder 

assembly from the weapon system. This task simulates a misfire on the main gun, and 

the actions that the crew would have to take to get their vehicle back in the fight. 

Rapidly restoring the functionality of the vehicle’s primary weapon system is a critical 

task for a Gunner. The crew was evaluated on the time required to disassemble and to 

reassemble the weapon system. Times were calculated by adding the Gunner’s overall 

time with the assistance time of the Driver and the Vehicle Commander.

B.5.9.1 Main Gun Remedial Action by Critical Billet 

B.5.9.1.1 Main Gun Remedial Action by Critical Billet Scatterplots

The scatter plots below display the results to complete the Main Gun Remedial Action 

Subtask by critical billet. No outliers were identified for this sub-section. No data points 

were determined to be influential.
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Figure B-40. Main Gun Remedial Action by Critical Billet

Figure B-41. Main Gun Remedial Action; Disassembly by Critical Billet

Critical Billet Gender

Critical Billet Gender
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Figure B-42. Main Gun Remedial Action; Reassembly by Critical Billet

B.5.9.1.2 Main Gun Remedial Action by Critical Billet Data Table and Analysis

The tables below summarize the results of Main Gun Remedial Action task. The first 

table compares means across metrics and critical billets. The second table presents 

ANOVA and Tukey test results bringing to focus those metrics that resulted in statistical 

significance along with their percentage differences.

Table B-32. Main Gun Remedial Action by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD

Perform Main Gun Remedial Action 

(with assistance times) (Gunner) 

(minutes) *

M 27 12.32 5.60

F 27 16.42 6.16

Perform Main Gun Remedial Action; 

Disassembly (with assistance times) 

(Gunner) (minutes) *

M 39 4.97 1.87

F 42 6.77 3.51

Perform Main Gun Remedial Action; 

Re-assembly (with assistance times) 

(Gunner) (minutes) *

M 27 8.56 5.11

F 27 12.05 5.09

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

Critical Billet Gender
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Table B-33. Main Gun Remedial Action by Critical Billet ANOVA

Metric

F 

Statist

ic (df)

F Test 

PValue 

Comp

arison

Differ

ence

% Diff

TTest 

Stati

stic 

(df)

1-Sided 

P-Value 

2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Perform Main Gun 

Remedial Action 

(Gunner) (minutes)

6.57 

(1, 52) 0.01* F-M 4.10 33.30% 2.56 

(52) < 0.01* 0.01* 2.02 6.18 1.42 6.79

Perform Main Gun 

Remedial Action; 

Disassembly 

(Gunner) (minutes)

8.1 (1, 

79) < 0.01* F-M 1.80 36.18% 2.91 

(63) < 0.01* < 0.01* 1.00 2.60 0.77 2.83

Perform Main Gun 

Remedial Action; 

Re-assembly 

(Gunner) (minutes)

6.32 

(1, 52) 0.02* F-M 3.49 40.75% 2.51 

(52) < 0.01* < 0.02* 1.69 5.29 1.16 5.81

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between integration levels according to ANOVA or a non-parametric equivalent test.

For all tasks above, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA. For the overall time to perform main gun remedial 

action, the M group is not normally distributed with Shapiro-Wilk Test p-value of less 

than 0.01, while the F group is normally distributed with p-value of 0.11. We proceed 

with presenting the ANOVA results, since they are confirmed by a Mann-Whitney Test 

(p-value < 0.01). For the disassembly portion of perform main gun remedial action, 

sample sizes are sufficient to satisfy normality assumptions. For the reassembly portion 

of perform main gun remedial action, the M group is not normally distributed with 

Shapiro-Wilk Test p-value of less than 0.01, while the F group is normally distributed 

with p-value of 0.05. We proceed with presenting the ANOVA results, since they are 

confirmed by a Mann-Whitney Test (p-value < 0.01). 

For the overall time required to conduct remedial actions, the Male group had a mean 

time of 12.32 minutes, which was statistically significantly faster than the Female group 

that recorded a mean time of 16.42 minutes. The Male group’s 33.30% faster mean 

time when compared to the Female group was statistically significant. The disassembly 

and reassembly time metrics also show statistical significance when comparing the 

Male group and Female group. The percentage differences equate to degradation in 

disassembly and reassembly time for the Female Group when compared to the Male 

group. Additionally, the Female group above shows a greater variability for the overall 

time and disassembly time metrics as shown by the SD column; the Female group 

shows less variability for the reassembly time metric. See Table B-32 and Table B-33

for detailed analytical results. 

B.5.9.1.3 Main Gun Remedial Action by Critical Billet Contextual Comments

Remedial action of the M242 Main Gun is a task primarily executed by the Gunner. 

Although the Driver and Vehicle Commander can assist, the Gunner still assumes most 
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of the physical demand. As the low-density integration crew could have either a male or 

female serving as the Gunner, this group masks an individual Gunner’s performance. It 

is therefore beneficial to explore the results of this subtask based on the gender of the 

Gunner.

B.5.9.1.4 Main Gun Remedial Action by Critical Billet Additional Insights

Observations and context for this task are similar to those for the Prepare the M242 

Main Gun Task due to the almost identical nature of the subtasks. The key difference is 

that remedial action allows assistance from the additional crewmembers from the start, 

and Gunners are required to download ammunition prior to beginning disassembly of 

the weapon system. Longer times to ensure primary weapon system functionality have 

the potential to impede operations, especially when the LAV-25 is operating in a direct 

fire or support by fire role.

B.5.9.2 Main Gun Remedial Action by Critical Billet (Excluding Potential Influential 

Points) 

See B.5.9 and B.5.9.1 for task description. 

B.5.9.2.1 Main Gun Remedial Action by Critical Billet (Excluding Potential Influential 

Points) Scatterplots

The scatter plots below display the results to complete the Main Gun Remedial Action 

Subtask by critical billet. The data points determined to be influential are identified by 

lightly colored black circles. No outliers were identified for this sub-section.
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Figure B-43. Main Gun Remedial Action; Disassembly by Critical Billet (Excluding) 

Figure B-44. Main Gun Remedial Action; Disassembly by Critical Billet (Excluding)

Critical Billet Gender

Critical Billet Gender
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B.5.9.2.2 Main Gun Remedial Action by Critical Billet (Excluding Potential Influential 

Points) Data Table and Analysis

The tables below summarize the results of Main Gun Remedial Action task. The first 

table compares means across metrics and critical billets. The second table presents 

ANOVA and Tukey test results bringing to focus those metrics that resulted in statistical 

significance along with their percentage differences.

Table B-34. Main Gun Remedial Action by Critical Billet (Excluding)

Metric Integration 

Level 

Sample 

Size Mean SD

Perform Main Gun Remedial Action; 

Disassembly[excluding potential 

influential points] (Gunner) (minutes)* 

M 38 4.83 1.65

F 42 6.77 3.51

Perform Main Gun Remedial Action; Reassembly (Gunner) [excluding 

potential influential points] (minutes)*

M 26 7.91 3.91

F 27 12.05 5.09

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.

Table B-35. Main Gun Remedial Action by Critical Billet (Excluding)

Metric

F 

Statis

tic 

(df)

F Test 

PValue

Com

paris

on

Differ

ence

% 

Differe

nce

TTest 

Stat

istic 

(df)

1-Sided 

P-Value

2-Sided 

P-Value

80 % 

LCB

80% 

UC

B 

90% 

LCB

90% 

UC

B 

Perform Main Gun 

Remedial Action; 

Disassembly 

[excluding 

potential 

influential 

points] (Gunner) 

(minutes)

10.35

(1, 60)

< 

0.01†† F-M 1.94 40.29% 3.22 

(60) < 0.01* < 0.01* 1.16 2.73 0.93 2.95

Perform Main Gun 

Remedial Action; 

Re-assembly 

[excluding 

potential 

influential 

points] (Gunner) 

(minutes)

10.94 

(1, 51) < 0.01* F-M 4.14 52.28% 3.32 

(49) < 0.01* < 0.01* 2.52 5.75 2.05 6.22

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances)

For the disassembly portion of perform main gun remedial action, sample sizes are 

sufficient to satisfy normality assumptions. Since the standard deviation of the F group 

is more than twice that of the M group, we recommend using the robust ANOVA results 

presented above. For the reassembly portion of perform main gun remedial action, the 
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M and F groups are normally distributed with Shapiro-Wilk Test p-values of 0.01 and 

0.05, respectively. Group standard deviations for the re-assembly portion are 

sufficiently similar to satisfy the equal variance assumption of ANOVA.

When excluding potential influential results for the remedial action disassembly time the 

Male group had a mean time of 4.83 minutes, which was statistically significantly faster 

than the Female group that recorded a mean time of 6.77 minutes. The Male group’s

40.29% faster mean time when compared to the Female group was statistically 

significant. The reassembly time metric also shows statistical significance when 

comparing the Male group and Female group. The percentage differences equate to 

degradation in reassembly time for the Female Group when compared to the Male 

group. Overall remediation time contained no influential points and is omitted. 

Additionally, the Female group above shows a greater variability for disassembly and 

reassembly time metrics as shown by the SD column. The overall time to conduct 

remedial actions metric contained no potential influential points. See Table B-34 and 

Table B-35 for detailed analytical results.

B.5.9.2.3 Main Gun Remedial Action by Critical Billet (Excluding Potential Influential 

Points) Additional Insights

Observations after excluding potential influential results remain largely the same.

B.5.9.3 Main Gun Remedial Action by Integration Level

See B.5.9 for task description. 

B.5.9.3.1 Main Gun Remedial Action by Integration Level Scatterplots

The scatter plots below display the results to complete the Main Gun Remedial Action 

Subtask by integration level. No outliers were identified for this sub-section. The 

analysis included all potential influential points. 
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Figure B-45. Main Gun Remedial Action by Integration Level

Figure B-46. Main Gun Remedial Action; Disassembly by Integration Level
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Figure B-47. Main Gun Remedial Action; Reassembly by Integration Level

B.5.9.3.2 Main Gun Remedial Action by Integration Level Data Table and Analysis

The tables below summarize the results of Main Gun Remedial Action task. The first 

table compares means across metrics and integration level. The second table presents 

ANOVA and Tukey test results bringing to focus those metrics that resulted in statistical 

significance along with their percentage differences.

Table B-36. Main Gun Remedial Action by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD

Perform Main Gun Remedial Action 

(minutes)

C 18 12.16 4.79

LD 18 14.74 7.08

HD 18 16.22 6.10

Perform Main Gun Remedial Action; 

Disassembly (minutes) * 

C 27 4.94 1.91

LD 27 5.85 2.60

HD 27 6.92 3.82

Perform Main Gun Remedial Action; 

Re-assembly (minutes)

C 18 8.42 4.14

LD 18 10.81 6.48

HD 18 11.67 4.89

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 
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Table B-37. Main Gun Remedial Action by Integration Level ANOVA and Tukey Test

Metric

F 

Statis

tic 

(df)

F Test 

PValue

Comp

ariso

n 

Diffe

renc

e 

% 

Differe

nce

PValue80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UC

B 

Perform Main 

Gun Remedial 

Action (minutes)

2.06 

(2, 51) 0.14

LD-C 2.57 21.15% 0.42 -0.95 6.09 -1.67 6.82

HD-C 4.05 33.32% 0.12 0.53 7.57 -0.19 8.30

HDLD 1.48 10.05% 0.75 -2.04 5.00 -2.76 5.72

Perform Main 

Gun Remedial 

Action; 

Disassembly 

(minutes) †

3.19 

(2, 78) 0.12

LD-C 0.92 18.61% 0.16 0.08 1.43 -0.13 1.62

HD-C 1.98 40.19% 0.05 0.37 2.08 0.17 2.35

HDLD 1.07 18.20% 0.48 -0.40 1.53 -0.57 1.75

Perform Main 

Gun Remedial 

Action; Reassembly 

(minutes)

1.84 

(2, 51) 0.17

LD-C 2.39 28.37% 0.37 -0.67 5.44 -1.29 6.07

HD-C 3.25 38.57% 0.16 0.19 6.30 -0.44 6.93

HDLD 0.86 7.94% 0.88 -2.20 3.91 -2.83 4.54

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between integration levels according to ANOVA or a non-parametric equivalent test.

 †Results presented are from a Mann-Whitney non-parametric test due to non-normality

For all tasks above, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA. For the overall time to perform main gun remedial 

action, the C, LD, and HD groups are normally distributed with Shapiro-Wilk Test pvalues of 0.06, 0.14, and 0.46, respectively. For the disassembly portion of the time, 

the C and LD group data are normally distributed with Shapiro-Wilk Test p-values of 

0.02 and 0.01, respectively, while the HD group is not normally distributed with p-value 

of less than 0.01. We recommend using the Kruskal-Wallis Test results shown in the 

table above. For the assembly portion of the time, the C, LD, and HD groups are

normally distributed with Shapiro-Wilk Test p-values of 0.08, 0.09, and 0.16, 

respectively. 

Statistical analysis included ANOVA and multiple comparisons using Tukey tests. For 

the overall time to conduct remedial action, the C group had a mean time of 12.16

minutes, which was faster than the LD and HD groups that recorded times of 14.74 

minutes and 16.22 minutes, respectively. The only statistically significant result is the C 

group’s 40.19% faster mean time when compared to the HD group during disassembly. 

Additionally, the HD and LD groups show greater variability when compared to the C 

group as shown by the SD column. See Table B-36 and Table B-37 for detailed 

analytical results.
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B.5.9.3.3 Main Gun Remedial Action by Integration Level Additional Insights

Observations when examined by integration level remain largely the same as by critical 

billet, although results in the low-density group are less apparent and many results fall 

below the threshold required for statistical significance.

B.5.9.4 Main Gun Remedial Action by Integration Level (Excluding Potential Influential 

Points) 

See B.5.9 for task description. 

B.5.9.4.1 Main Gun Remedial Action by Integration Level (Excluding Potential Influential 

Points) Scatterplots

The scatter plots below display the results to complete the Main Gun Remedial Action 

Subtask by integration level. No outliers were identified for this sub-section. Influential 

points are identified by lightly colored black circles. 

Figure B-48. Main Gun Remedial Action; Disassembly by Integration Level (Excluding)
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Figure B-49. Main Gun Remedial Action; Reassembly by Integration Level (Excluding)

B.5.9.4.2 Main Gun Remedial Action by Integration Level (Excluding Potential Influential 

Points) Data Table and Analysis

The tables below summarize the results of Main Gun Remedial Action task. The first 

table compares means across metrics and integration level. The second table presents 

ANOVA and Tukey test results bringing to focus those metrics that resulted in statistical 

significance along with their percentage differences. 

Table B-38. Main Gun Remedial Action (Excluding)

Metric Integration 

Level 

Sample 

Size Mean SD

Perform Main Gun Remedial Action; 

Disassembly (with assistance times)

[excluding potential influential 

points] (minutes)*

C 26 4.72 1.58

LD 27 5.85 2.60

HD 27 6.92 3.82

Perform Main Gun Remedial Action; 

Re-assembly (with assistance times) 

[excluding potential influential 

points] (minutes)

C 18 8.42 4.14

LD 17 9.95 5.52

HD 18 11.67 4.89

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.
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Table B-39. Main Gun Remedial Action (Excluding) ANOVA and Tukey Test

Metric

F 

Statis

tic 

(df)

F 

Test 

PValue

Comp

ariso

n 

Diffe

renc

e 

% 

Differe

nce

PValue80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UC

B 

Perform Main 

Gun Remedial 

Action; 

Disassembly 

[excluding 

potential 

influential 

points] (minutes)

†

3.99 

(2, 77) 0.07*

LD-C 1.13 24.00% 0.10 0.20 1.52 0.02 1.75

HD-C 2.20 46.56% 0.03* 0.50 2.15 0.28 2.47

HDLD 1.07 18.20% 0.48 -0.40 1.53 -0.57 1.75

Perform Main 

Gun Remedial 

Action; Reassembly 

[excluding 

potential 

influential 

points] (minutes)

2 (2, 

50) 0.15

LD-C 1.53 18.17% 0.62 -1.34 4.40 -1.93 4.99

HD-C 3.25 38.57% 0.12 0.42 6.08 -0.16 6.66

HDLD 1.72 17.26% 0.55 -1.15 4.59 -1.74 5.18

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between integration levels according to ANOVA or a non-parametric equivalent test.

†Results presented are from a Mann-Whitney non-parametric test due to non-normality.

For the disassembly portion of perform main gun remedial action, the C and LD groups 

are normally distributed with Shapiro-Wilk Test p-values of 0.19 and 0.01, respectively, 

while the HD group is not normally distributed with a p-value of less than 0.01. 

Additionally, the standard deviation of the HD group is more than twice that of the C 

group, which would indicate that at a minimum, a robust ANOVA is needed. However, 

due to lack of normality, we recommend using the Kruskal-Wallis results shown in the 

table above. For the assembly portion of the time, the C, LD, and HD groups are 

normally distributed with Shapiro-Wilk Test p-values of 0.08, 0.06, and 0.16, 

respectively. 

Statistical analysis included analysis of variance (ANOVA) and multiple comparisons 

using Tukey tests. When excluding potential influential results for disassembly time, the 

C group had a mean time of 4.72 minutes, which was faster than the LD group and HD 

group mean times of 5.85 minutes and 6.92 minutes, respectively. The 46.56% 

difference between the C group and HD group during disassembly was the only 

statistically significant result. Additionally, the HD and LD groups show greater 

variability when compared to the C group as shown by the Standard Deviation (SD) 

column. See Table B-38 and Table B-39 for detailed analytical results. 
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B.5.9.4.3 Main Gun Remedial Action by Integration Level (Excluding Potential Influential 

Points) Additional Insights

Observations after excluding potential influential results remain largely the same.

B.5.10 Gunner’s Defensive Manual Engagement Overview

The second live-fire defensive engagement was conducted from a defensive battle 

position. This engagement required the gunner to use AP ammunition to engage a 

vehicle target without using the Gunner’s hand control. The Gunner used the manual 

traverse and elevation controls within the turret to acquire and destroy the target. 

Crews had 80 seconds to acquire, identify, engage, and destroy the target. The time to 

engage the target and number of bursts required to kill the target was recorded. Livefire engagements were adapted from MCWP 3-14.1 Table VI gunnery qualification 

engagements, which all vehicle crews are required to fire to achieve qualified status. 

Manual engagements require a greater amount of physical exertion because the 

Gunner does not rely on the electric turret to traverse and elevate.

B.5.10.1 Gunner’s Defensive Manual Engagement by Critical Billet 

See B.5.9 for task description.

B.5.10.1.1 Gunner’s Defensive Manual Engagement by Critical Billet Scatterplots

Figure B-50 shows a scatter plot displaying the results to complete the Defensive 

Manual Engagement by critical billet task. No outliers were identified for this subsection. Important to note is only successful engagements are displayed on the scatter 

plot and analyzed for time comparison. Figure B-51 shows a mosaic plot displaying 

engagement outcomes on a pass or fail scale. This plot displays the pass rate for each 

group and includes all data points. 
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Figure B-50. Defensive Manual Engagement by Critical Billet - Passed Engagement

Figure B-51. Defensive Manual Engagement by Critical Billet - Pass/Fail

B.5.10.1.2 Gunner’s Defensive Manual Engagement by Critical Billet Data Table and 

Analysis

The tables below summarize the results of Defensive Manual Engagement task. The 

first table compares means across metrics and critical billets. The second table 

Critical Billet Gender
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presents ANOVA and Tukey test results bringing to focus those metrics that resulted in 

statistical significance along with their percentage differences. Each table only 

examines successful (passed) engagements. 

Table B-40. Defensive Manual Engagement by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD 

Engage Defensive Targets (#2) - Manual 

(Gunner) (seconds)

M 31 24.13 8.46

F 34 26.68 13.84

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.

Table B-41. Defensive Manual Engagement by Critical Billet

Metric

F 

Statist

ic (df)

F Test 

PValue 

Comp

arison

Differ

ence

% 

Differen

ce

TTest 

Stati

stic 

(df)

1-Sided 

P-Value 

2-

Sided 

PValue 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Engage Defensive 

Targets (#2) - 

Manual (Gunner) 

(seconds)

0.78 

(1, 63) 1.38 F-M 2.55 10.56% 0.9 (55) 0.19 0.37 -1.11 6.20 -2.17 7.26

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.

For the task above, we proceed with presenting ANOVA results since all samples are 

sufficiently large (n > 30). Additionally, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA.

During successful live-fire engagements, M group had a mean time of 24.13 seconds, 

which was faster than the F group mean time of 26.68 seconds. The 10.56% difference 

is not statistically significant. When observing the binary pass/fail criteria for the 

engagement, there is no difference in percent kill between M and F gunners in a 

Chi-Square (likelihood ratio) Test (p-value = 0.47). 

B.5.10.1.3 Gunner’s Defensive Manual Engagement by Critical Billet Contextual 

Comments

Live-fire engagements are primarily executed by the Gunner. Although the Driver and 

Vehicle Commander can assist, the Gunner still assumes most of the physical demand. 

As the low-density integration crew could have either a male or female serving as the 

Gunner, this group masks an individual Gunner’s performance. It is therefore beneficial 

to explore the results of this subtask based on the gender of the Gunner.

B.5.10.1.4 Gunner’s Defensive Manual Engagement by Critical Billet Additional Insights

The observed output from this task contained a high level of variance, making it difficult 

to draw a definitive conclusion. A high pass rate and a proficient Gunner are desired to 
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ensure a vehicle crew’s effectiveness. Male and female Gunners performed similarly, 

with males acquiring and engaging targets slightly faster while females having a slightly 

higher engagement pass rate. 

B.5.10.2 Gunner’s Defensive Manual Engagement by Integration Level

See B.5.10 for task description

B.5.10.2.1 Gunner’s Defensive Manual Engagement by Integration Level Scatterplot and 

Mosaic Plot

Figure B-52 shows a scatter plot displaying the results of passed engagement results 

for the Defensive Manual Engagement by integration level task. No outliers were 

identified for this sub-section. Only successful engagements are displayed on the 

scatter plot and analyzed for time comparison. Figure B-53 shows a mosaic plot 

displaying engagement outcomes on a pass or fail scale. This plot displays the pass 

rate for each group and includes all data points. 

Figure B-52. Defensive Manual Engagement- Passed Engagements
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Figure B-53. Defensive Manual Engagement Pass/Fail

B.5.10.2.2 Gunner’s Defensive Manual Engagement Data by Integration Level Table and 

Analysis

The tables below summarize the results of Engage Defensive Targets task. The first 

table compares means across metrics and integration levels. The second table 

presents ANOVA and Tukey test results bringing to focus those metrics that resulted in 

statistical significance along with their percentage differences. Each table only 

examines successful (passed) engagements.

Table B-42. Engage Defensive Targets-Manual

Metric Integration 

Level 

Sample 

Size Mean SD

Engage Defensive Targets (#2) - 

Manual (seconds)

C 22 23.00 8.67

LD 22 29.18 10.65

HD 21 24.14 14.39

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.

Table B-43. Engage Defensive Targets-Manual ANOVA and Tukey Test

Metric

F 

Statist

ic (df)

F 

Test 

PValue

Comp

arison

Differ

ence

% 

Differen

ce

PValu

e 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Engage 

Defensive 

Targets (#2) - 

Manual (seconds)

1.82 

(2, 62) 0.17

LD-C 6.18 26.88% 0.18 0.20 12.17 -1.02 13.39

HD-C 1.14 4.97% 0.94 -4.91 7.20 -6.15 8.43

HDLD -5.04 -17.27% 0.32 -11.09 1.01 -12.33 2.25

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.
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For the task above, the C, LD, and HD groups are not normally distributed with ShapiroWilk Test p-values of less than 0.01. Additionally, group standard deviations are 

sufficiently similar to satisfy the equal variance assumption for ANOVA. We proceed 

with presenting ANOVA results since they are confirmed by a Kruskal-Wallis Test (pvalue = 0.39).

During successful live-fire engagements, C group had a mean time of 23.00 seconds, 

which was faster than the LD and HD group mean times of 29.18 seconds and 24.14 

seconds, respectively. No result comparisons are statistically significant. When 

observing the binary pass/fail criteria for the engagement, there is no difference in 

percent kill between C, LD, and HD groups in a binomial logistic regression/effect 

likelihood ratio test (P-value = 0.66)

B.5.10.2.3 Additional Insights

Observations when examined by integration level remain largely the same as by critical 

billet.

B.5.11 Conduct Maintenance Actions Overview

While a maintenance task does not always convey the same sense of urgency typically 

found in a casualty evacuation or live-fire task, they remain no less important. The 

ability to effectively perform continuing maintenance actions is a vital necessity of 

sustained operations. Vehicles require extensive preventative maintenance even in 

garrison, and austere terrain and expeditionary operating conditions only magnify these 

demands. This work is often physically demanding because the parts, tools, and 

equipment organic to LAR units are large and heavy. The ability of a vehicle crew to 

work with their maintainers to keep their vehicles in the fight is an everyday necessity. 

The maintenance actions portion of the non-live-fire trial day consisted of three separate 

subtasks; remove scout hatch armor, remove side panel armor, and a tire change. The 

tire change subtask was modeled, and is subsequently discussed below. For 

descriptive statistics on remove scout hatch and side panel armor, reference Appendix

to Annex B. Each of these tasks was evaluated on the time to reach the mid-point of 

the task and the overall time to completion. 

B.5.12 Mount/Remove Spare Tire Overview

The vehicle crew used the SL-3 associated with the LAV-25 to remove a tire, weighing 

approximately 200 lb, and mount the spare. For the first half of the subtask, the crew 

would jack up the vehicle, remove a vehicle tire, mount the vehicle’s spare tire and 

completely tighten the lug nuts. The crew would then remove the spare tire, mount the 

original tire and completely tighten the lug nuts, and finally return the spare tire and all 

additional equipment to the proper location. The crew would manually lift the spare tire 

from the ground to its mounting bracket on the side of the LAV-25. This was 
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accomplished in a variety of ways, although two methods were most often observed. If 

the Gunner and Driver possessed the required strength, they would lift the tire straight 

up and mount it on the side of the vehicle. If one or both did not have the strength to 

conduct the lift, they would roll the vehicle up the side of the vehicle, a slower method of 

mounting the tire. If the two crewmen were unable to accomplish either method, they 

would request assistance from the Vehicle Commander to complete the tire re-mount. 

B.5.12.1 Mount/Remove Spare Tire by Integration Level

B.5.12.1.1 Mount/Remove Spare Tire by Integration Level Scatterplots

The scatter plots below display the results of Mount/Remove Spare Tire by integration 

level task. No outliers were identified for this task.

Figure B-54. Mount/Remove Spare Tire
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Figure B-55. Mount/Remove Spare Tire; Mounting Spare

Figure B-56. Mount/Remove Spare Tire; Re-Mounting Original

B.5.12.1.2 Mount/Remove Spare Tire by Integration Level Data Table and Analysis

The tables below summarize the results for the Mount/Remove Spare Tire task. The 

first table compares means across metrics and integration levels. The second table 

presents ANOVA and Tukey test results bringing to focus those metrics that resulted in 

statistical significance along with their percentage differences. 
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Table B-44. Mount/Remove Spare Tire

Metric Integration 

Level 

Sample 

Size Mean SD

Remove/Mount Spare Tire (minutes)

C 26 61.84 18.15

LD 27 61.93 18.36

HD 28 65.95 16.58

Remove/Mount Spare Tire; Mounting 

Spare (minutes)

C 27 30.80 9.28

LD 27 31.83 9.63

HD 28 32.38 8.27

Remove/Mount Spare Tire; ReMounting Original (minutes)

C 27 31.04 10.27

LD 28 30.40 9.40

HD 28 33.57 9.65

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test. 

Table B-45. Mount/Remove Spare Tire ANOVA and Tukey Test

Metric

F 

Statist

ic (df)

F Test 

PValue

Comp

arison

Differ

ence

% 

Differen

ce

PValue 80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Remove/Mount 

Spare Tire 

(minutes)

0.48 

(2, 78) 0.62

LD-C 0.09 0.15% 1.00 -8.33 8.51 -10.04 10.22

HD-C 4.10 6.64% 0.67 -4.24 12.45 -5.93 14.14

HD-LD 4.01 6.48% 0.68 -4.25 12.28 -5.93 13.96

Remove/Mount 

Spare Tire; 

Mounting Spare 

(minutes)

0.21 

92, 79) 0.81

LD-C 1.03 3.34% 0.91 -3.24 5.30 -4.11 6.17

HD-C 1.58 5.13% 0.80 -2.65 5.81 -3.51 6.67

HD-LD 0.55 1.74% 0.97 -3.68 4.79 -4.54 5.65

Remove/Mount 

Spare Tire; ReMounting Original 

(minutes)

0.82 

(2, 80) 0.44

LD-C -0.64 -2.07% 0.97 -5.20 3.92 -6.13 4.85

HD-C 2.53 8.14% 0.61 -2.04 7.09 -2.96 8.01

HD-LD 3.17 10.42% 0.45 -1.35 7.69 -2.27 8.61

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between integration levels according to ANOVA or a non-parametric equivalent test.

For all tasks above, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA. For the overall time to remove/mount the spare tire, 

the C, LD, and HD groups are all normally distributed with Shapiro-Wilk Test p-values of 

0.35, 0.92, and 0.23, respectively. For the mount spare portion of the time, the C, LD, 

and HD groups are all normally distributed with Shapiro-Wilk Test p-values of 0.04, 

0.23, and 0.37, respectively. For the re-mount original portion of the time, the C, LD, 

and HD groups are all normally distributed with Shapiro-Wilk Test p-values of 0.19, 

0.81, and 0.79, respectively.

All times are expressed in man-minutes derived from the amount of time the Gunner 

and Driver required to complete the tire change and the addition of the time when the 

Vehicle Commander assisted in the process. Statistical analysis included analysis of 

variance (ANOVA) and multiple comparisons using Tukey tests. For the overall time to 

mount and remove the spare tire, the C group had a mean composite time of 61.84
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minutes, which was faster than the LD and HD group mean composite times of 61.93

minutes and 65.95 minutes, respectively. No result is statistically significant. Results 

show differing levels of variance as shown by the SD column. See Table B-44 and 

Table B-45 for detailed analytical results. 

B.5.12.1.3 Mount/Remove Spare Tire by Integration Level Contextual Comments

The observed output from this task contained a high level of variance, making it difficult 

to draw a definitive conclusion about this task. As one of the lengthiest subtasks, 

observed, times of integrated and non-integrated crews were largely the same, with C 

groups slighter faster when compared to HD groups. The ability to rapidly change a tire 

has critical implications to ensuring mission accomplishment, especially during longrange movements. Depending on the terrain, it would not be unusual for a vehicle crew 

to change multiple tires throughout the course of an operation. 

B.5.12.1.4 Mount/Remove Spare Tire by Integration Level Additional Insights

Subjective comments and test manager observation reveal that a large portion of highdensity crews and many low-density crews required assistance or struggled to remount 

the spare tire on the side of the vehicle. A large portion of the control-group crews 

performed a straight lift without assistance from the Vehicle Commander when 

mounting the spare tire. Vehicle Commander assistance or additional manpower to 

compensate during such tasks can detract from local security or concurrent actions. 

Compiled subjective comment results can be found in section 5.6.

B.5.12.2 Mount/Remove Spare Tire by Integration Level (Excluding Potential Influential 

Points) 

See B.5.18 for task description.

B.5.12.2.1 Mount/Remove Spare Tire by Integration Level (Excluding Potential Influential 

Points) Scatterplots

The scatter plots below display the results of Mount/Remove Spare Tire by integration 

level task. No outliers were identified for this task. Influential points are identified by 

lightly colored black circles. 
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Figure B-57. Mount/Remove Spare Tire (Excluding)

B.5.12.2.2 Mount/Remove Spare Tire by Integration Level (Excluding Potential Influential 

Points) Data and Analysis

The tables below summarize the results for the Mount/Remove Spare Tire task. The 

first table compares means across metrics and integration levels. The second table 

presents ANOVA and Tukey test results bringing to focus those metrics that resulted in 

statistical significance along with their percentage differences. 

Table B-46. Mount/Remove Spare Tire (Excluding)

Remove/Mount Spare Tire [excluding 

potential influential points] (minutes)

C 25 60.74 17.62

LD 26 60.20 16.32

HD 28 65.95 16.58

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.

Table B-47. Mount/Remove are Tire (Excluding) ANOVA and Tukey Test

Metric

F 

Statisti

c (df)

F 

Test 

PValue

Com

paris

on

Diff % Diff 2- side 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Remove/Mount 

Spare Tire 

[excluding 

infuential 

points] 

(minutes)

0.97 (2, 

76) 0.39

LD-C -0.55 -0.90% 0.99 -8.71 7.62 -10.37 9.28

HD-C 5.20 8.57% 0.50 -2.82 13.22 -4.45 14.85

HDLD 5.75 9.55% 0.43 -2.19 13.69 -3.80 15.30
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*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA or a non-parametric equivalent test.

For the overall time to remove/mount the spare tire, the C, LD, and HD groups are all 

normally distributed with Shapiro-Wilk Test p-values of 0.23, 0.90, and 0.23, 

respectively. Additionally, group standard deviations are sufficiently similar to satisfy 

the equal variance assumption for ANOVA. 

When excluding potential influential results to accomplish the task, the C group mean 

time of 60.74 minutes was slower than the LD group time of 60.20 minutes, but faster 

than HD group composite time of 65.95 minutes. None of the results were statistically 

significant. There were no potential influential points identified for the mounting spare or 

remounting original metrics and they were thus omitted. Results show greater variance 

in the HD and C groups as shown by the SD column. See Table B-46 and Table B-47

for detailed analytical results. 

B.5.12.2.3 Mount/Remove Spare Tire by Integration Level (Excluding Potential Influential 

Points) Additional Insights

Observations after excluding potential influential results remain largely the same. 

B.6 Statistical Modeling Results 

B.6.1 Statistical Modeling Results Overview

The previous section presented results in terms of integration levels and critical billets. 

This section describes statistical modeling, which applied here, is to estimate, 

simultaneously, the effect of gender-integration levels and other relevant variables on 

LAV crew performance. Refer to the Methodology Annex for a broad overview of the 

analysis plan and the variables used in the models. 

For the selected tasks described in the previous section, this section presents an 

overview of the analysis and results, and then presents the modeling results for each 

task. 

For each task, we describe the significant variables in the model and whether these 

variables are either positively or negatively correlated with the result. A negative 

correlation indicates the increase in that variable will result in a decrease in the 

response variable, which is a desired outcome for elapsed time.

B.6.2 0313 Selected Tasks Method of Analysis

A linear mixed model was not suitable for these data because some volunteers only 

participated in a particular billet one to two times. Therefore, the 0313 selected tasks 

were modeled using Ordinary Least Squares regression. In addition to the Gunners’ 

and Drivers’ physical characteristics used as variables in the model, we also included a 

fixed effect for the VC to evaluate the leadership impact on task completion. 
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The statistical model included integration level and personnel data for each 

crewmember. Age, height, and other variables for each member of the crew and 

integration level were modeled with the result (response time) as the response variable. 

For tasks that had critical billets, i.e., only one or two Marines performing the task 

without help from the others, only their personnel variables and gender were included in 

the model. Where possible, a backward stepwise regression, using AIC, determined 

which variables were optimal in the model. In case of missing values, backward 

stepwise could not run and significant variables were automatically reported based on 

p-values from the overall model. Variables reported as significant were significant 

based on at least a one-sided test. 

B.6.3 Selected Tasks Overall Modeling Results

There were no personnel data variables that were statistically significant and had a 

practical impact to the model. Each time personnel data variables are statistically 

significant in a model, their effects are practically negligible, conflicting, and/or 

incomplete for the crew; i.e., there are no tasks for which a variable is significant for all, 

or even most, members of the crew. 

Refer to Section B.4 for the ANOVA summary for each below-mentioned 0313 task. 

B.6.3.1 Manually Traverse and Elevate the LAV-25 Turret (Critical Billet)

We modeled elapsed time for the manually manipulating the turret as a function of the 

personnel variables and gender of the Gunner performing the task. The covariates in 

each model are the values of each personnel variable for each volunteer member in the 

LAV crew. We report statistically significant positive and negative correlations and 

whether we observe any patterns.

There was one potentially influential point for these results. However, investigation 

showed no effect on regression results so it was included in the analysis. The critical 

billet variable was eliminated with the AIC criterion during variable selection, meaning it 

wasn’t a good predictor of elapsed time given the other variables in the model. 

The models for the following variables do not run due to missing values:

• None.

The integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• None.

The integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables:

• None.
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The following personnel variables are significant in their respective models and are

positively correlated with manually manipulating the turret: 

• Height 

• AFTQ

• CFT MUF. 

The following personnel variables are significant in their respective models and are 

negatively correlated with manually manipulating the turret: 

• Age 

• GT Score 

• Weight 

• CFT MTC

• PFT Crunch Score 

• PFT Run Time. 

The model identified a small effect of the VC with respect to leadership impact on task 

completion.

There are no patterns for any personnel variables for manually manipulating the turret. 

See section B.5.5.1.2 for the ANOVA summary of this task. 

B.6.3.2 Prep M242 Main Gun (Critical Billet)

We model elapsed time for prepping the M242 Main Gun as a function of the personnel 

variables and gender of the Marine performing the task. The covariates in each model 

are the values of each personnel variable for the Gunner and Driver. We report 

statistically significant positive and negative correlations and whether we observe any 

patterns.

There were three potentially influential points in the analysis of this task. Running the 

models with and without these points gives slightly different results on the Gunner’s and 

Driver’s covariates. However, both models, when put through the AIC variable selection 

process, exclude the gender of the Gunner as a predictor. Because we consider the 

potentially influential points as valid data, and because their inclusion makes no 

difference on our variable of interest, we present the results of the model that include 

them in the analysis.

The models for the following variables do not run due to missing values:

• None.
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The integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• None.

The integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables:

• None.

The following Gunner personnel variables are significant in their respective models and 

are positively correlated with prepping the M242 Main Gun: 

• Age 

• GT

• CFT MTC 

• PFT Crunch Score.

The following Gunner personnel variables are significant in their respective models and 

are negatively correlated with prepping the M242 Main Gun: 

• Height 

• AFQT 

• Rifle Range Score.

There are no patterns for any personnel variables for prepping the M242 Main Gun. 

See section B.5.6 for the ANOVA summary of this task. 

The VC’s and Driver’s personnel variables had no significant relationship with time to 

Prep M242 Main Gun. The opposing relationships between Gunner’s GT and AFQT 

scores poses difficulties establishing any correlation between mental performance and 

task effectiveness. Anaerobic capability can be correlated to faster times to complete 

this task, as displayed by the correlation of the Gunner’s Movement to Contact time and 

crunch score. The negative correlation with height may also be a determining factor 

due to the difficulty of lifting heavy objects in a confined space. 

B.6.3.3 Conduct Casualty Evacuation

We model elapsed time for evacuating a casualty from the LAV as a function of each 

personnel variable for each crewmember and integration level. The covariates in each 

model are the values of each personnel variable for each volunteer member in the LAV

crew. We report statistically significant positive and negative correlations and whether 

we observe any patterns.
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The AIC criterion chooses a model in which gender integration is a significant variable. 

Specifically, the HD crews took, on average, 1 minute longer to complete the task than 

all-male crews, holding other variables constant. LD crews did not show a significant 

difference from C group crews.

The models for the following variables do not run due to missing values:

• None.

The integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• None.

The integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables:

• None.

The following Gunner personnel variables are significant in their respective models and 

are positively correlated with evacuating a casualty from the LAV: 

• Age 

• CFT MTC. 

The following Gunner personnel variables are significant in their respective models and 

are negatively correlated with evacuating a casualty from the LAV: 

• GT 

• Weight 

• PFT Run Time 

• PFT Crunch Score. 

There are no patterns for any personnel variables for evacuating a casualty from the 

LAV time. See section B.5.2.2 for the ANOVA summary of this task 

The VC’s and Driver’s personnel variables had no significant relationship with time to

evacuate casualty from the LAV. Due to the opposing correlation between Gunner’s 

CFT MTC and PFT run time, it is difficult to establish a correlation between physical 

performance variables and task effectiveness. The Gunner’s weight could also be a 

determining factor on elapsed time to complete task since a heavier crewman could 

utilize more leverage when extracting a casualty from the turret. 

B.6.3.4 Perform Main Gun Remedial Action (with assistance times)

We model elapsed time for performing remedial action on the main gun as a function of 

each personnel variable for each crewmember and integration level. The covariates in 
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each model are the values of each personnel variable for each volunteer member in the 

LAV crew. We report statistically significant positive and negative correlations and 

whether we observe any patterns.

The task was examined by critical billet and integration level. In both models, the 

gender variables were eliminated with the AIC criterion during variable selection. The 

remaining results were similar between the two.

The models for the following variables do not run due to missing values:

• None.

The integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• None.

The integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables:

• None.

The following Driver personnel variables are significant in their respective models and 

are positively correlated with performing remedial action on the main gun: 

• Weight 

• PFT Run Time.

The following personnel variables are significant in their respective models and are 

negatively correlated with performing remedial action on the main gun: 

• Gunner Weight 

• Gunner AFQT 

• Gunner PFT Run Time

• Driver Age

• Driver CFT MTC 

• Driver PFT Crunch Score. 

There are no patterns for any personnel variables for performing remedial action on the 

main gun. See section B.5.9 for the ANOVA summary of this task. 

The model identified a large effect of the VC with respect to leadership impact on task 

completion. Proficient VC’s with higher experience levels will have a positive effect on 

the overall time to complete this task, while the least experienced VC will yield a 

detrimental effect. The Gunner’s weight can be a determining factor as a heavier 
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crewman could utilize more leverage when manipulating heavy objects in a confined 

space. Due to the opposing correlation between Driver’s Movement to Contact time 

and PFT run time, it is difficult to establish a correlation between Driver’s physical 

performance variables and task effectiveness. 

B.6.3.5 Remove / Mount Spare Tire; with assistance time

We model elapsed time for removing/mounting a spare tire as a function of each 

personnel variable for each crewmember and integration level. The covariates in each 

model are the values of each personnel variable for each volunteer member in the LAV

crew. We report statistically significant positive and negative correlations and whether 

we observe any patterns.

There were two potentially influential points for analysis in this task. Upon investigation, 

they did not make a sizeable difference on the model, so we report results with the 

points included. The AIC variable selection process yields a model that does not 

include integration level, meaning that in presence of additional variables in did not have 

a strong linear relationship with the time to complete this task.

The models for the following variables do not run due to missing values:

• None.

The integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• None.

The integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables:

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with removing/mounting a spare tire: 

• CFT MTC of the Gunner

• PFT Crunch Score of the Gunner 

• Age of the Driver

• PFT Crunch Score of the Driver.

The following personnel variables are significant in their respective models and are 

negatively correlated with removing/mounting a spare tire: 

• Weight of the Gunner 

• CFT MUF of the Gunner, 
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• Rifle Range Score of the Gunner

• Height of the Driver 

• Rifle Range Score of the Driver.

Due to the opposing correlation between Gunner’s MTC and MANUF, it is difficult to 

establish a correlation between the Gunner’s physical performance variables and task 

effectiveness. A Vehicle Commander’s experience could correlate to faster times. 

Crunch score could correlate to better core strength when lifting and mounting the 

heavy tires. Additionally, height could be correlated to faster times when lifting the 

spare tire to mount on the side of the vehicle

There are no patterns for any personnel variables for removing/mounting a spare tire. 

See section B.5.12 for the ANOVA summary of this task.

B.6.3.6 Load & Stow Additional Ammunition

We model elapsed time for loading and stowing additional ammunition as a function of 

each personnel variable for each crew member and integration level. The covariates in 

each model are the values of each personnel variable for each volunteer member in the 

LAV crew. We report statistically significant positive and negative correlations and 

whether we observe any patterns.

The models for the following variables do not run due to missing values:

• None.

The integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• None.

The integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables:

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with loading and stowing additional ammunition: 

• AFQT score of the Driver

The following personnel variables are significant in their respective models and are 

negatively correlated with loading and stowing additional ammunition: 

• GT of the Gunner 

• Weight of the Gunner 
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• PFT Run Time of the Gunner

• Age of the Driver 

• GT of the Driver 

• CFT MTC of the Driver.

Due to the opposing correlation between Driver’s GT and AFQT scores, it is difficult to 

establish a correlation between mental performance and task effectiveness. Anaerobic 

capability could be correlated to faster times during the execution of this task as 

displayed by the correlation of the Gunner’s PFT run time and the Driver’s CFT MTC. 

There are no patterns for any personnel variables for loading and stowing additional 

ammunition. See Section B.5.7 for the ANOVA summary of this task.

B.6.3.7 Engage Defensive Targets (#2) – Manual (Critical Billet)

We model elapsed time for engaging defensive targets as a function of the personnel 

variables and gender of the Marine performing the task. The covariates in each model 

are the values of each personnel variable for each volunteer member in the LAV crew. 

We report statistically significant positive and negative correlations and whether we 

observe any patterns.

For this task, the measurement of interest is time to kill. The data are right censored 

because crews exceeded the maximum time of 80 seconds to complete the task. 

Therefore, we modeled time to kill using a Cox Proportional Hazards Model. The result 

of the model shows that gender of the Gunner has no significant effect.

The models for the following variables do not run due to missing values:

• None.

The integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• None.

The integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables:

• None.

The following personnel variables are significant in their respective models and are

positively correlated with engaging defensive targets: 

• Age of the Gunner 

• Rifle Score of the Gunner,
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• Height of the Driver 

• CFT MTC of the Driver

• AFQT of the Driver.

The following personnel variables are significant in their respective models and are 

negatively correlated with engaging defensive targets: 

• Weight of the Gunner 

• Age of the Driver

• CFT MTC of the Driver 

• PFT Crunch Score of the Driver. 

There were also no statistically significant differences in first hit success rates when 

accounting for the gender of the Marine in the Gunner billet

There are no patterns for any personnel variables for engaging defensive targets. See 

section B.5.8 for the ANOVA summary of this task.

B.6.3.8 Prep M240 Coaxial Machine Gun (Critical Billets)

We model elapsed time for preparing M240 Coaxial Machine Gun as a function of the 

personnel variables and gender of the Marine performing the task. The covariates in 

each model are the values of each personnel variable for the Gunner. We report 

statistically significant positive and negative correlations and whether we observe any 

patterns.

Including the influential points into analysis yields a statistically significant effect of the 

gender of the Marine in the Gunner billet (women are almost 4 minutes slower, on 

average). 

Excluding the influential points from analysis yields a smaller but still significant effect of 

a female Gunner (1.56 minutes slower). The signs of the remaining effect stay the 

same as in the previous model, except the sign on the PFT run time becomes negative.

The models for the following variables do not run due to missing values:

• None.

The integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• None.

The integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables:
GCEITF EAR ANNEX B

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• None.

The following Gunner personnel variables are significant in their respective models and 

are positively correlated with preparing M240 Coaxial Machine Gun: 

• Age 

• GT 

• CFT MTC 

• PFT Crunch Score.

The following Gunner personnel variables are significant in their respective models and 

are negatively correlated with preparing M240 Coaxial Machine Gun: 

• AFQT

• Rifle Range Score.

There are no patterns for any personnel variables for preparing M240 Coaxial Machine 

Gun. See section B.5.4 for the ANOVA summary of this task.
GCEITF EAR ANNEX B 

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B-105 AUGUST 2015

Appendix to Annex B 

0313 Supplemental Information

This appendix provides supplemental information for the 0313 portion of the GCEITF

experiment. It provides information regarding the GCEITF subjective comments and 

additional descriptive and basic inferential statistics not described in Annex B. 

Section 1: Subjective Comments

Subjective comments were gathered and reported from daily observation and 

interaction with volunteers during the execution of the experiment. Table B A displays a 

summary of these comments broken down by task, integration level, gender, and type 

of comment. Comments were both positive and negative depending on the observation. 

For example, the table shows that 2 males in a C group and 14 females in an HD group 

executing the Mount/Remove Spare Tire task required extra assistance to complete the 

task. 

Table B A - Summary Subjective Comments

Task Description Gender Grand 

Total

CG LD HD Total CG HD LD Total CG HD LD Total CG HD LD Total CG HD LD Total CG LD HD Total

Female 2 0 0 2 1 2 2 5 3 2 0 5 0 1 0 1 1 1 0 2 1 0 0 1 16

Male 0 0 0 0 1 0 0 1 1 1 2 4 0 0 0 0 13 0 2 15 0 0 0 0 20

M/F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Female 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

Male 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M/F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Female 0 0 0 0 0 1 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

Male 0 0 0 0 2 0 0 2 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 3

M/F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Female 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

Male 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 1 2

M/F 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

Female 0 0 0 0 2 14 2 18 0 0 0 0 0 0 0 0 0 9 0 9 0 0 0 0 27

Male 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 11 0 0 0 0 11

M/F 0 0 0 0 0 1 3 4 0 0 0 0 0 0 0 0 0 0 14 14 0 0 0 0 18

Female 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2

Male 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M/F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Female 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1

Male 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M/F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Female 0 0 1 1 0 8 1 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10

Male 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1

M/F 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2

Female 0 0 0 0 0 5 2 7 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 8

Male 0 0 0 0 0 1 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2

M/F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Grand Total 2 0 1 3 6 37 16 59 5 3 2 10 0 1 2 3 25 10 17 52 2 2 0 4 131

Maintenance Day SubTasks

Cohesion Extra Assistance Failed to do task 

properly Marine avoiding task Needs No Assistance Stamina and Strength

Casevac

Live Fire Sub-Tasks

Load and Stow Additional 

Ammo

Mount/Remove Spare Tire

Prep For Combat 

Prep M242 Main Gun

Rig for Recovery

Rig For Tow
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Section 2: Additional Task Basic and Inferential Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. The experiment included a number of tasks and associated metrics 

conducted to enhance operational realism and maintain consistent application of the 

experimental process. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

This section presents results for additional 0313 tasks. Annex B contains the 

descriptive statistics for the remainder of the 0313 tasks. The words “metric” and “task” 

are used interchangeably throughout this Appendix. They both refer to the experimental 

task. 

The tables below display results, to include metrics and integration levels with their 

respective sample sizes, means, standard deviations, and percent difference between 

integration levels. Also ANOVA results, including metrics and integration levels, and pvalues suggesting statistical significance. For each task, an ANOVA and t-test were 

conducted to compare groups. If p-values are less than the a-priori determined 

significance level of 0.10, we conclude there is statistical evidence that the response for 

the LD and HD groups are different from that in the C group.

Section 3: Additional Task Results

Table B B – 0313 Selected Task Results

Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

Evac Operator Stations (seconds)*

C 29 23.17 4.44

LD 28 24.04 4.98 3.72% 14.20% 10.10%

HD 28 26.46 6.56

Upload Main Gun (minutes)

C 29 1.52 1.00

LD 25 1.58 0.78 3.74% -13.10% -16.24%

HD 27 1.32 0.57

Upload M240 (minutes)

C 29 1.59 0.73

LD 27 1.73 0.80 8.81% -14.15% -21.10% 

HD 28 1.36 0.47

Engage Defensive Targets (#1) 

(seconds)

C 27 37.67 16.98

LD 25 36.12 16.99 -4.11% 1.31% 5.65% 

HD 25 38.16 22.20

Engage Offensive Targets (#1) 

(seconds)

C 27 15.26 4.39

LD 25 14.72 4.16 -3.53% 5.91% 9.79% 

HD 25 16.16 7.80

Engage Offensive Targets (#2) 

(seconds)

C 27 14.30 5.74

LD 25 14.84 7.79 3.79% 15.55% 11.32% 

HD 25 16.52 6.21
GCEITF EAR ANNEX B 

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*Indicates there is a statistically significant difference in a two-sided hypothesis test between the 

metric’s mean or percent hits values for the Integration Level

Table B C - 0313 Selected Task ANOVA and T-test Results

Metric F statistic 

(df)

F Test

P-value Comparison Difference % Difference 2-sided 

p-Value

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Evac Operator 

Stations 

(seconds)*

2.84 

(2, 82) 0.06* 

LD-C 0.86 3.72% 0.82 -1.61 3.34 -2.11 3.84 

HD-C 3.29 14.20% 0.06* 0.82 5.76 0.32 6.27 

HD-LD 2.43 10.10% 0.22 -0.07 4.92 -0.57 5.43 

Engage Defensive 

Targets (#1) 

(seconds)

0.08 

(2, 74) 0.92 

LD-C -1.55 -4.11% 0.95 -10.60 7.51 -12.45 9.35 

HD-C 0.49 1.31% 0.99 -8.56 9.55 -10.41 11.39 

HD-LD 2.04 5.65% 0.92 -7.19 11.27 -9.07 13.15 

Engage Offensive 

Targets (#1) 

(seconds)

0.41 

(2, 74) 0.66 

LD-C -0.54 -3.53% 0.94 -3.26 2.19 -3.82 2.74 

HD-C 0.90 5.91% 0.83 -1.82 3.63 -2.38 4.18 

HD-LD 1.44 9.79% 0.64 -1.34 4.22 -1.90 4.78 

Engage Offensive 

Targets (#2) 

(seconds)

0.79 

(2, 74) 0.46 

LD-C 0.54 3.79% 0.95 -2.64 3.72 -3.28 4.37 

HD-C 2.22 15.55% 0.45 -0.96 5.40 -1.60 6.05 

HD-LD 1.68 11.32% 0.64 -1.56 4.92 -2.22 5.58

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s 

mean or percent hits values for the Integration Level

Evacuate Operator Stations. All crewmen (VC, Gunner, and Driver) were required to 

exit the vehicle safely and move as a crew to the rally point 25 m away. Marines wore 

fighting loads and carried individual weapons, as would be expected when evacuating a 

vehicle in a tactical environment. Although the crew evacuation subtask was not as 

physically demanding as extracting a casualty from an LAV-25 turret, the ability to 

evacuate a vehicle quickly is important in the event of a vehicle fire or other lifethreatening issue. 

For this task, the C and HD groups are normally distributed as evidenced by a ShapiroWilk Test p-value of 0.16 and 0.01 respectively, while the LD group is not normally 

distributed with Shapiro-Wilk p-value of less than 0.01. We proceed with presenting the 

ANOVA results shown above which are confirmed by a Kruskal-Wallis Test (p-value = 

0.10). Additionally, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA.

For the overall time required to evacuate the vehicle, the C group had a mean time of 

23.17 seconds, which was statistically significant and faster when compared to the HD 

group time of 26.46 seconds. The C group’s 14.20% faster mean time when compared 

to the HD group was statistically significant. Additionally, the LD and HD groups show 

greater variability than the C group as shown by the Standard Deviation (SD) column. 
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• Contextual Comments. In the event of a vehicle casualty, egress from the 

vehicle is essential. Longer times to egress could lead to greater exposure to 

various threats, such as a vehicle fire.

• Additional Insights. The time differences between groups in this task are very 

small. When viewed as a standalone event, the differences are minor. When 

viewed in conjunction with additional requirements or tasks, such differences 

have the potential to accumulate and cause greater mission effects. 

Upload Main Gun. This subtask required the LAV-25 crew to upload the HE and AP 

rounds from their respective ready-boxes into the M242 main gun. This was 

accomplished by ratcheting the rounds from the ready box, through the gun’s feed 

chutes, and into the feeder assembly on the gun. The AP ready-box is located near the 

Driver, while the HE ready-box is located next to the Gunner. Without assistance, a 

crew must upload their weapons systems as part of normal combat preparation. 

The C group had a mean time of 1.52 minutes, which was faster than the LD group time 

of 1.58 minutes but slower than the HD group of 1.32 minutes. None of the results were 

statistically significant. Additionally, the C group shows greater variability than the LD 

and HD groups as shown by the Standard Deviation (SD) column. 

• Additional Insights. The observed output from this task contained a high level 

of variance, and because of this it is difficult to draw a definitive conclusion. After 

it has been loaded into the vehicle, uploading ammunition requires little physical 

exertion but remains a key component of combat preparation. 

Upload M240 Coax. This subtask required the LAV-25 Gunner, without assistance, to 

upload a belt of 200 7.62-mm rounds from coax ready box into the M240 coaxially 

mounted machine gun. This was accomplished by feeding the rounds through the feed 

chute that extends across the turret and onto the feed tray of the M240 coax. Without 

assistance, a crew must upload their weapons systems as part of normal combat 

preparation. 

The C group had a mean time of 1.59 minutes, which was faster than the LD group time 

of 1.73 minutes but slower than the HD group time of 1.36 minutes. None of the results 

were statistically significant. Additionally, groups showed differing levels of variability as 

shown by the Standard Deviation (SD) column. 

• Additional Insights. Like the Upload Main Gun task, these results show a very 

high level of variability and make it difficult to draw any definitive conclusions. As 

stated above, uploading ammunition requires little physical exertion but remains 

a key component of combat preparation. 
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Defensive Engagement #1. The first live-fire engagement was conducted from a 

defensive battle position. The crews engaged two vehicle targets, one with AP and one 

with HE ammunition. The time to engage each target and number of bursts required to 

kill each target was recorded. Crews had 80 seconds to acquire, identify, engage, and 

destroy the target. Live fire engagements were adapted from MCWP 3-14.1 Table VI 

gunnery qualification engagements, which all vehicle crews are required to fire to 

achieve qualified status. 

For this task, the HD group is normally distributed as evidenced by a Shapiro-Wilk Test 

p-value of 0.06, while the C and LD groups are not normally distributed with ShapiroWilk p-values of less than 0.01. We proceed with presenting the ANOVA results shown 

above which are confirmed by a Kruskal-Wallis Test (p-value = 0.92). Additionally, 

group standard deviations are sufficiently similar to satisfy the equal variance 

assumption for ANOVA. 

The C group had a mean time of 37.67 seconds, which was slower than the LD group 

time of 36.12 seconds but faster than the HD group time of 38.16 seconds. None of the 

results were statistically significant. Additionally, the HD group showed greater 

variability than the C and LD groups as shown by the Standard Deviation (SD) column. 

• Additional Insights. The results above indicate the time required to initially 

acquire and begin to engage identified targets. These results show a very high 

level of variability and make it difficult to draw any definitive conclusions. A high 

pass rate and a proficient Gunner is desired to ensure a vehicle crew’s 

effectiveness. 

Offensive Engagement #1. The first live-fire offensive engagement was conducted on 

the move through a maneuver box. The crews engaged one vehicle target with the 

LAV-25 main gun and a bank of troop targets with the coaxially mounted machine gun. 

The time to engage each target and number of bursts required to kill the main gun 

target was recorded. Live fire engagements were adapted from MCWP 3-14.1 Table VI 

gunnery qualification engagements, which all vehicle crews are required to fire to 

achieve qualified status. 

For this task, the C and LD groups are normally distributed as evidenced by ShapiroWilk Test p-values of 0.02 and 0.44, respectively, while the HD group is not normally 

distributed with Shapiro-Wilk p-value of less than 0.01. We proceed with presenting the 

ANOVA results shown above which are confirmed by a Kruskal-Wallis Test (p-value = 

0.93). Additionally, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA.

The C group had a mean time of 15.26 seconds, which was slower than the LD group 

time of 14.72 seconds but faster than the HD group time of 16.16 seconds. None of the 
GCEITF EAR ANNEX B 

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AUGUST 2015 K-110

results were statistically significant. Additionally, the HD group showed greater 

variability than the C and LD groups as shown by the Standard Deviation (SD) column.

• Additional Insights. The results above indicate the time required to initially 

acquire and begin to engage identified targets. These results show a very high 

level of variability and make it difficult to draw any definitive conclusions. A high 

pass rate and a proficient Gunner is desired to ensure a vehicle crew’s 

effectiveness.

Offensive Engagement #2. The second live-fire offensive engagement was conducted 

on the move through a maneuver box as a retrograde engagement. With the turret 

oriented over the rear end of the vehicle, the crews engaged one vehicle target with the 

LAV-25 main gun and a bank of troop targets with the coaxially mounted machine gun. 

The time to engage each target and number of bursts required to kill the main gun 

target was recorded. Live fire engagements were adapted from MCWP 3-14.1 Table VI 

gunnery qualification engagements, which all vehicle crews are required to fire to 

achieve qualified status. 

For this task, the C, LD, and HD groups are all not normally distributed as evidenced by 

Shapiro-Wilk Test p-values of less than 0.01. We proceed with presenting the ANOVA 

results shown above which are confirmed by a Kruskal-Wallis Test (p-value = 0.12). 

Additionally, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA.

The C group had a mean time of 14.30 seconds which was faster than the LD group 

time of 14.84 seconds and the HD group time of 16.52 seconds. None of the results 

were statistically significant. Additionally, groups showed differing levels of variability as 

shown by the Standard Deviation (SD) column.

• Additional Insights. The results above indicate the time required to initially 

acquire and begin to engage identified targets. These results show a very high 

level of variability and make it difficult to draw any definitive conclusions. A high 

pass rate and a proficient Gunner is desired to ensure a vehicle crew’s 

effectiveness.
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B-111 AUGUST 2015

Vehicle Recovery and Tow Operations Overview. Recovery operations are an 

integral part of an LAR unit’s mobility and versatility when operating independently. 

Should a vehicle become mired or lose power, crews must quickly and efficiently work 

together to perform this critical skill. All recovery tasks were conducted as crew events.

Rig for Recovery. This sub-task required the LAV-25 crew to utilize the winch mounted 

on the front of the vehicle and the snatch blocks mounted on the side of the LAV-25 and 

the LAV Logistics Variant (LAV-L). With the two vehicles spaced ten meters apart, the 

crewmen would pay out the winch cable and utilize two snatch blocks, each weighing 75 

lbs., to create a three-point recovery system with the shackles and tow-points of the 

vehicles. The ability to quickly recover a mired vehicle is an important skill that all 

crewmen must possess. A three point recovery system is often used as it only requires 

two vehicles to establish and can be accomplished fairly quickly. Crews were evaluated 

on the time required to set-up the three point recovery as well as the time to break down 

and stow all of the tools and equipment used in the process. 

Rig for Recovery by Integration Level. The tables below display results, to include 

metrics and integration levels with their respective sample sizes, means, standard 

deviations, and percent difference between integration levels. Also ANOVA results, 

including metrics and integration levels, and p-values suggesting statistical significance. 

For each task, an ANOVA and t-test were conducted to compare groups. If p-values 

are less than the a-priori determined significance level of 0.10, we conclude there is 

statistical evidence that the response for the LD and HD groups are different from that in 

the C group.

Table B D - Rig for Recovery by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

% 

Difference

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

Rig for Recovery; Rig and Stow 

(minutes)

C 29 13.76 3.87

LD 27 12.92 2.56 -6.07% 7.89% 14.86% 

HD 28 14.84 3.82

Rig for Recovery; Rig Only (with 

remediation) (minutes)

C 28 5.62 1.92

LD 28 6.05 2.57 7.60% 18.04% 9.71% 

HD 28 6.63 1.82

Rig for Recovery; Stow Only 

(minutes)

C 27 7.23 2.27

LD 27 6.65 1.26 -7.98% 7.44% 16.76% 

HD 28 7.77 2.57
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Table B E - Rig for Recovery by Integration Level ANOVA and Tukey Test

Metric F Statistic 

(df)

F Test 

PValue

Compa

rison Diff % Diff 2-sided p-Value

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Rig for Recovery; 

Rig and Stow 

(minutes)

2.11 (2, 

81) 0.13

LD-C -0.83 -6.07% 0.64 -2.45 0.78 -2.77 1.10

HD-C 1.09 7.89% 0.47 -0.51 2.68 -0.84 3.01

HD-LD 1.92 14.86% 0.11 0.29 3.55 -0.04 3.88

Statistical analysis included analysis of variance (ANOVA) and multiple comparisons 

using Tukey tests. 

For the overall time to rig for recovery, the C, LD, and HD groups are all normally 

distributed as evidenced by Shapiro-Wilk Test p-values of 0.53, 0.12, and 0.12, 

respectively. Additionally, group standard deviations are sufficiently similar to satisfy the 

equal variance assumption for ANOVA. For the overall time to rig for recovery the C 

group had a mean time of 13.76 minutes, which was slower than the LD group mean 

time of 12.92 minutes but faster than the HD group mean time of 14.84 minutes. None 

of the results are statistically significant. Results show differing levels of variance as 

shown by the Standard Deviation (SD) column. 

• Contextual Comments. Crews will almost always conduct a vehicle recovery 

under some sort of duress, as a mired vehicle has the potential to severely 

impact timelines and hinder mission accomplishment. Thus, vehicle crews must 

be able to execute recoveries as quickly as possible. While not necessarily 

retaining the urgency of a casualty evacuation or live fire task, recovery is an 

essential skill each crewman must possess. MCWP 3-14, Employment of the 

Light Armored Reconnaissance Battalion, describes the importance of 

maintenance and self-recovery, and ensuring vehicles are properly configured to 

conduct recovery operations. 

• Additional Insights. During this task, Vehicle Commanders had a large influence 

on the performance of their crew, regardless of gender composition. The 

performance of vehicle crews was also highly variable for this task, leading to our 

failure to reject the null hypothesis. Observed times of integrated and nonintegrated crews were largely the same, with C groups performing slightly faster 

than HD groups.
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Rig for Recovery by Integration Level (Excluding Potential Influential Points). The tables 

below display results, to include metrics and integration levels with their respective 

sample sizes, means, standard deviations, and percent difference between integration 

levels. Also ANOVA results, including metrics and integration levels, and p-values 

suggesting statistical significance. For each task, an ANOVA and t-test were conducted 

to compare groups. If p-values are less than the a-priori determined significance level 

of 0.10, we conclude there is statistical evidence that the response for the LD and HD 

groups are different from that in the C group. 

Table B F - Rig for Recovery by Integration Level (Excluding) 

Metric Integration 

Level 

Sample 

Size Mean SD 

% 

Difference

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

Rig for Recovery; Rig Only (with 

remediation) [excluding potential 

influential points] (minutes)*

C 27 5.4 1.56

LD 28 6.05 2.57 11.92% 22.79% 9.71% 

HD 28 6.63 1.82

Rig for Recovery; Stow Only

[excluding potential influential 

points] (minutes)

C 27 7.23 2.27

LD 27 6.65 1.26 -7.98% 4.64% 13.72% 

HD 27 7.56 2.38

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level

Statistical analysis included analysis of variance (ANOVA) and multiple comparisons 

using Tukey tests. When excluding potential influential results for rig time, the C group 

had a mean time of 5.40 minutes, which was faster than the LD group and HD group 

mean times of 6.05 minutes and 6.63 minutes, respectively. The 22.79% difference 

between the C group and HD group during disassembly was the only statistically 

significant result. There were no potential influential points identified for the overall time 

metric and it was thus omitted. Results show differing levels of variance as shown by 

the Standard Deviation (SD) column. 

• Additional Insights. Observations after excluding potential influential results 

remain largely the same, with the exception of statistically significant results for 

the time to rig metric comparison between C and HD groups. C groups 

performed slightly faster than HD groups. 

Rig for Tow Overview. This sub-task required the LAV-25 crew to utilize the LAV tow 

bar, weighing approximately 175 lbs., located on the side of the LAV-L. With the two 

vehicles spaced ten meters apart, the crewmen would detach the tow bar from the LAVL and connect it to the tow points on the LAV-25. They would then ground guide the 

LAV-L and, with one crewman holding the tow bar, attach the eye of the tow bar to the 

tow pintle of the LAV-L. The subtask was completed when all tools and equipment were 

returned to their proper locations. Vehicles will often break down, either due to 

mechanical issues or enemy action, and the ability to quickly rig a vehicle for towing 
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directly affects combat effectiveness. Crews were evaluated on the time required to setup the tow configuration as well as the time to break down and stow all of the tools and 

equipment used in the process

Rig for Tow by Integration Level. The tables below display results, to include metrics 

and integration levels with their respective sample sizes, means, standard deviations, 

and percent difference between integration levels. Also ANOVA results, including 

metrics and integration levels, and p-values suggesting statistical significance. For 

each task, an ANOVA and t-test were conducted to compare groups. If p-values are 

less than the a-priori determined significance level of 0.10, we conclude there is 

statistical evidence that the response for the LD and HD groups are different from that in 

the C group.

Table B G - Rig for Tow by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

% 

Difference

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

Rig for Tow; Rig and Stow 

(minutes)

C 29 9.99 2.13

LD 28 10.68 2.61 6.89% 6.27% -0.58% 

HD 28 10.62 2.72

Rig for Tow; Rig Only (minutes)

C 29 5.92 1.33

LD 28 6.34 1.49 7.10% 5.81% -1.2% 

HD 28 6.26 1.73

Rig for Tow; Stow Only (minutes)

C 28 3.8 0.92

LD 28 4.07 1.35 6.99% 8.36% 1.27% 

HD 28 4.12 1.17

Table B H - Rig for Tow by Integration Level ANOVA and Tukey Test

Metric

F 

Statistic 

(df)

F Test 

PValue

Comp

arison Diff % Diff 2-sided p-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Rig for Tow; Rig 

and Stow 

(minutes)

0.67 (2, 

82) 0.52

LD-C 0.69 6.89% 0.55 -0.46 1.83 -0.69 2.06

HD-C 0.63 6.27% 0.61 -0.52 1.77 -0.75 2.00

HD-LD -0.06 -0.58% 1.00 -1.22 1.09 -1.45 1.33

Statistical analysis included ANOVA and multiple comparisons using Tukey tests. 

For the overall time to rig for tow, the C, LD, and HD groups are all normally distributed 

as evidenced by Shapiro-Wilk Test p-values of 0.78, 0.23, and 0.07, respectively. 

Additionally, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA. For the overall time to rig for tow the C group had a 

mean time of 9.99 minutes, which was faster than the LD and HD group mean times of 

10.68 minutes and 10.62 minutes, respectively. None of the results are statistically 

significant. Additionally, the HD and LD groups show greater variability when compared 

to the C group as shown by the Standard Deviation (SD) column. 
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• Contextual Comments. The context for this sub-task is very similar to the rig for 

recovery sub-task discussed above. The ability to rapidly rig a downed vehicle for 

tow is a crucial skill that a vehicle crew must retain. 

• Additional Insights. During this task, Vehicle Commanders had a large influence 

on the performance of their crew, regardless of gender composition. The 

performance of vehicle crews was also highly variable for this task, leading to our 

failure to reject the null hypothesis. Observed times of integrated and nonintegrated crews were largely the same, with C groups performing slightly faster 

than HD groups.

Rig for Tow by Integration Level (Excluding Potential Influential Points). The tables 

below display results, to include metrics and integration levels with their respective 

sample sizes, means, standard deviations, and percent difference between integration 

levels. Also ANOVA results, including metrics and integration levels, and p-values 

suggesting statistical significance. For each task, an ANOVA and t-test were conducted 

to compare groups. If p-values are less than the a-priori determined significance level 

of 0.10, we conclude there is statistical evidence that the response for the LD and HD 

groups are different from that in the C group. 

Table B I - Rig for Tow by Integration Level (Excluding)

Metric Integration 

Level 

Sample 

Size Mean SD 

% 

Difference

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

Rig for Tow; Rig and Stow 

[excluding potential influential 

points] (minutes)

C 29 9.99 2.13

LD 28 10.68 2.61 6.89% 3.13% -3.52% 

HD 27 10.31 2.19

Rig for Tow; Rig Only (with 

remediation) [excluding potential 

influential points] (minutes)

C 29 5.92 1.33

LD 28 6.34 1.49 7.10% 3.09% -3.74% 

HD 27 6.1 1.53

Rig for Tow; Stow Only (with 

remediation) [excluding potential 

influential points] (minutes)

C 27 3.7 0.76

LD 26 3.96 1.2 6.96% 7.43% 0.44% 

HD 27 3.98 0.91

Table B J - Rig for Tow by Integration Level (Excluding) ANOVA and Tukey Test

Metric

F 

Statistic 

(df)

F Test 

PValue

Comp

arison Diff % Diff 2-Sided 

p-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Rig for Tow; Rig 

and Stow 

[excluding 

potential 

influential 

points] (minutes)

0.63 (2, 

81) 0.54

LD-C 0.69 6.89% 0.50 -0.38 1.75 -0.59 1.97

HD-C 0.31 3.13% 0.87 -0.76 1.39 -0.98 1.60

HD-LD -0.38 -3.52% 0.82 -1.46 0.71 -1.68 0.93

Statistical analysis included analysis of variance (ANOVA) and multiple comparisons 

using Tukey tests. 
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For the overall time to rig for tow (excluding influential points), the C, LD, and HD 

groups are all normally distributed as evidenced by Shapiro-Wilk Test p-values of 0.78, 

0.23, and 0.34, respectively. Additionally, group standard deviations are sufficiently 

similar to satisfy the equal variance assumption for ANOVA. When excluding potential 

influential results for the overall time to rig for tow, the C group had a mean time of 9.99 

minutes, which was faster than the LD group and HD group mean times of 10.68 

minutes and 10.31 minutes, respectively. None of the results were statistically 

significant. Additionally, the HD and LD groups show greater variability when compared 

to the C group as shown by the Standard Deviation (SD) column. 

• Additional Insights. Observations after excluding potential influential results 

remain largely the same, with the C group performing slightly faster than LD and 

HD groups.

Conduct Maintenance Actions Overview. While a maintenance task does not always 

convey the same sense of urgency typically found in a casualty evacuation or live fire 

task, they remain no less important. The ability to effectively perform continuing 

maintenance actions is a vital necessity of sustained operations. Vehicles require 

extensive preventative maintenance even in garrison, and austere terrain and 

expeditionary operating conditions only magnify these demands. This work is often 

physically demanding because the parts, tools, and equipment organic to LAR units are 

large and heavy. The ability of a vehicle crew to work with their maintainers to keep their 

vehicles in the fight is an everyday necessity. The maintenance actions portion of the 

non-live fire trial day consisted of three separate subtasks; remove scout hatch armor, 

remove side panel armor, and a tire change. Each of these tasks was evaluated on the 

time to reach the mid-point of the task and the overall time to completion.

The vehicle crew used the tools and equipment (SL-3) associated with the LAV-25 to 

remove each of the armor panels mounted on the back hatches of the vehicle. Each 

panel is a solid piece of composite armor weighing approximately 125 lbs. The crew 

would drop and remount first one hatch panel, followed by the second. Crews were 

evaluated on the time required to mount and remove each of the scout hatch panels.

Mount/Remove Scout Hatch Armor by Integration Level. The tables below display 

results, to include metrics and integration levels with their respective sample sizes, 

means, standard deviations, and percent difference between integration levels. Also 

ANOVA results, including metrics and integration levels, and p-values suggesting 

statistical significance. For each task, an ANOVA and t-test were conducted to 

compare groups. If p-values are less than the a-priori determined significance level of 

0.10, we conclude there is statistical evidence that the response for the LD and HD 

groups are different from that in the C group. 
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Table B K - Mount/Remove Scout Hatch Armor by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

% 

Difference

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

Scout Hatch Panels (minutes)*

C 29 6.56 2.56

LD 27 6.71 2.25 2.23% 28.91% 26.1% 

HD 28 8.46 2.6

Scout Hatch Panels; 1st Panel 

removal & remount (minutes)*

C 29 3.28 1.26

LD 27 3.6 1.41 9.88% 33.23% 21.25% 

HD 28 4.36 1.57

Scout Hatch Panels; 2nd Panel 

removal & remount (minutes)*

C 29 3.29 1.5

LD 27 3.11 1.11 -5.38% 24.62% 31.7% 

HD 28 4.1 1.38

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level

Table B L - Mount/Remove Scout Hatch Armor by Integration Level ANOVA and Tukey Test

Metric

F 

Statistic 

(df)

F Test 

P-Value 

Compar

ison Diff % Diff 2-Sided 

p-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Scout Hatch 

Panels 

(minutes)

5.1 (2, 

81) < 0.01*

LD-C 0.15 2.23% 0.97 -1.00 1.29 -1.23 1.53

HD-C 1.90 28.91% 0.01* 0.76 3.03 0.53 3.26

HD-LD 1.75 26.10% 0.03* 0.59 2.91 0.36 3.14

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level

Statistical analysis included ANOVA and multiple comparisons using Tukey tests. 

For the overall time to mount and remove scout hatch panels, the C, LD, and HD groups 

are all normally distributed as evidenced by Shapiro-Wilk Test p-values of 0.18, 0.04, 

and 0.28, respectively. Additionally, group standard deviations are sufficiently similar to 

satisfy the equal variance assumption for ANOVA. For the overall time required to 

mount and remove the scout hatch panels the C group had a mean time of 6.56

minutes, which was statistically significantly faster than the HD groups that recorded a 

mean time of 8.46 minutes. The C group’s 28.91% faster mean time when compared to 

the HD group was statistically significant. Results show differing levels of variance as 

shown by the Standard Deviation (SD) column. 

• Contextual Comments. Removing armor panels, while not conducted as 

regularly as other maintenance actions, is required should the panels become 

damaged or during wash-downs and cleaning after extended operations. Longer 

times to conduct regular or routine maintenance could lead to lower readiness 

levels.

• Additional Insights. The statistical significance of the large performance gap 

between low density and high density crews suggests that the other crew 

members, specifically males, are less able to compensate for their counterpart’s 

performance at higher integration levels. In real world operations, this difference 
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can translate into increased times required to prepare for a mission, perform 

repairs in the midst of an operation, or perform maintenance after an operation. 

Mount/Remove Scout Hatch Armor by Integration Level (Excluding Potential 

Influential Points). The tables below display results, to include metrics and integration 

levels with their respective sample sizes, means, standard deviations, and percent 

difference between integration levels. Also ANOVA results, including metrics and 

integration levels, and p-values suggesting statistical significance. For each task, an 

ANOVA and t-test were conducted to compare groups. If p-values are less than the apriori determined significance level of 0.10, we conclude there is statistical evidence that 

the response for the LD and HD groups are different from that in the C group. 

Table B M - Mount/Remove Scout Hatch Armor by Integration Level (Excluding)

Metric Integration 

Level 

Sample 

Size Mean SD 

% 

Difference

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

Scout Hatch Panels2nd Panel 

removal & remount [excluding 

potential influential points]

(minutes) *

C 29 3.29 1.5

LD 26 2.98 0.91 -9.23% 20.16% 32.38% 

HD 27 3.95 1.17

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level

Statistical analysis included analysis of variance (ANOVA) and multiple comparisons 

using Tukey tests. When excluding potential influential results for 2nd scout hatch time, 

the C group had a mean time of 3.29 minutes, which was faster than the HD group time 

of 3.95 minutes but slower than the LD group mean time of 2.98 minutes. The 32.38% 

difference between the LD group and HD group was the only statistically significant 

result. 

• Additional Insights. Observations after excluding potential influential results 

remain largely the same, although it places the C-HD group comparison just 

outside the threshold for statistical significance. 

Mount/Remove Side-Panel Armor Overview. The vehicle crew used the SL-3 

associated with the LAV-25 to remove each of the front-most armor panels mounted on 

the left and right sides of the vehicle. Each panel is a solid piece of composite armor 

weighing approximately 60 lbs. The crew would drop and remount first one panel, 

followed by the second. Crews were evaluated on the time required to mount and 

remove each of the armor panels.
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Mount/Remove Side-Panel Armor by Integration Level. The tables below display 

results, to include metrics and integration levels with their respective sample sizes, 

means, standard deviations, and percent difference between integration levels. Also 

ANOVA results, including metrics and integration levels, and p-values suggesting 

statistical significance. For each task, an ANOVA and t-test were conducted to 

compare groups. If p-values are less than the a-priori determined significance level of 

0.10, we conclude there is statistical evidence that the response for the LD and HD 

groups are different from that in the C group.

Table B N - Mount/Remove Side Panel Armor by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

% 

Difference

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

Front Side Armor Panels (minutes)

C 29 3.88 1.78

LD 28 4.07 1.57 4.80% 11.86% 6.74% 

HD 28 4.34 1.16

Front Side Armor Panels; 1st panel 

removal and remount (minutes)

C 29 2.19 1.33

LD 28 2.2 1.06 0.34% 0.66% 0.33% 

HD 28 2.2 0.58

Front Side Armor Panels; 2nd 

panel removal and remount 

(minutes)

C 29 1.62 0.71

LD 28 1.72 0.71 5.96% 23.1% 16.18% 

HD 28 2 0.91

Table B O - Mount/Remove Side Panel Armor by Integration Level ANOVA and Tukey Test

Metric

F 

Statistic 

(df)

F Test 

PValue

Comp

arison Diff % Diff 2-Sided p-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Front Side Armor 

Panels (minutes)

0.65 (2, 

82) 0.52

LD-C 0.19 4.80% 0.89 -0.52 0.89 -0.66 1.03

HD-C 0.46 11.86% 0.49 -0.24 1.16 -0.38 1.30

HD-LD 0.27 6.74% 0.78 -0.43 0.98 -0.58 1.13

Statistical analysis included analysis of variance (ANOVA) and multiple comparisons 

using Tukey tests. 

For the overall time to mount and remove side panels, the C and LD groups are not 

normally distributed as evidenced by Shapiro-Wilk Test p-values of less than 0.01, while 

the HD is normally distributed with Shapiro-Wilk p-value of 0.16. We proceed with 

presenting ANOVA results since they are confirmed by a Kruskal-Wallis Test (p-value = 

0.10). Additionally, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA. 

• Contextual Comments. Removing armor panels, while not conducted as 

regularly as other maintenance actions, is required should the panels become 

damaged or during wash-downs and cleaning after extended operations. 
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• Additional Insights. The observed output from this task contained a high level 

of variance, and because of this it is difficult to draw a definitive conclusion. As 

discussed during the scout hatch armor sub-task, longer times to conduct regular 

or routine maintenance could lead to lower readiness levels. In real world 

operations, this difference can translate into increased times required to prepare 

for a mission, perform repairs in the midst of an operation, or perform 

maintenance after an operation.

Mount/Remove Side-Panel Armor by Integration Level (Excluding Potential 

Influential Points). The tables below display results, to include metrics and integration 

levels with their respective sample sizes, means, standard deviations, and percent 

difference between integration levels. Also ANOVA results, including metrics and 

integration levels, and p-values suggesting statistical significance. For each task, an 

ANOVA and t-test were conducted to compare groups. If p-values are less than the apriori determined significance level of 0.10, we conclude there is statistical evidence that 

the response for the LD and HD groups are different from that in the C group.

Table B P - Mount/Remove Side Panel Armor (Excluding)

Metric Integration 

Level 

Sample 

Size Mean SD 

% 

Difference

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

Front Side Armor Panels 

[excluding potential influential 

points] (minutes)

C 28 3.67 1.37

LD 27 3.87 1.17 5.47% 18.45% 12.31% 

HD 26 4.34 1.16

Front Side Armor Panels; 1st panel 

removal and remount [excluding 

potential influential points] 

(minutes)

C 28 1.91 0.67

LD 27 2.03 0.62 6.77% 15.7% 8.37% 

HD 26 2.2 0.58

Front Side Armor Panels; 2nd 

panel removal and remount 

[excluding potential influential 

points] (minutes)

C 28 1.55 0.6

LD 27 1.65 0.64 6.94% 24.69% 16.6% 

HD 26 1.93 0.87

Table B Q - Mount/Remove Side Panel Armor (Excluding)ANOVA and Tukey Test

Metric

F 

Statisti

c (df)

F Test 

P-Value 

Comp

arison Diff % Diff 2-Sided p-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Front Side Armor 

Panels

[excluding 

potential 

influential 

points] (minutes)

2.19 (2, 

80) 0.12

LD-C 0.20 5.47% 0.56† -0.24† 0.65 -0.38 0.78

HD-C 0.68 18.45% 0.05† 0.24 1.12 0.11 1.25

HD-LD 0.48 12.31% 0.14† 0.07 0.89 -0.05 1.00

†Due to lack of normality, p-values and confidence intervals have been replaced with Mann-Whitney Test results.

For the overall time to mount and remove side panels (excluding influential points), the 

C and LD groups are not normally distributed as evidenced by Shapiro-Wilk Test pvalues of less than 0.01, while the HD is normally distributed with Shapiro-Wilk p-value 
GCEITF EAR ANNEX B 

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of 0.16. Group standard deviations are sufficiently similar to satisfy the equal variance 

assumption for ANOVA, however, we recommend using Kruskal-Wallis results shown 

above due to lack of normality and conflicting results with the standard ANOVA. When 

excluding potential influential results for the overall time, the C group had a mean time 

of 3.67 minutes, which was faster than the LD and HD group times of 3.87 minutes and

4.34 minutes, respectively. None of the results comparisons were statistically

significant. Results show differing levels of variance as shown by the Standard 

Deviation (SD) column. 

• Additional Insight. Observations after excluding potential influential results 

remain largely the same.
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Annex C. 

Infantry Machine Gunner (MOS 0331)

This annex details the Infantry Machine Gunner (MOS 0331) portion of the Ground 

Combat Element Integrated Task Force (GCEITF) experiment executed from 2 March – 

26 April 2015 at Range 107 and Range 110, aboard the Marine Corps Air Ground 

Combat Center (MCAGCC), Twentynine Palms, CA. The sections outline the Infantry 

Machine gunner Scheme of Maneuver (SOM), Limitations, Deviations, Data Set 

Description, Descriptive and Basic Inferential Statistics, and Modeling Results.

C.1 Scheme of Maneuver

C.1.1 Experimental Cycle Overview

The Infantry Machine Gunner (MOS 0331) assessment of the GCEITF took place in a 

field environment aboard MCAGCC, Twentynine Palms, CA. The assessment 

consisted of 21 trial cycles, each of which was a 2-day test cycle, conducted over the 

course of 55 days. the Marines spent 1 recovery day at Camp Wilson After every 4 

days of trials. Every machinegun squad consisted of three volunteers and a directassignment (non-volunteer) squad leader. Each member of the squad was trained to fill 

each billet within the squad: gunner, assistant gunner, and ammo man. For the sake of 

consistency throughout the report, the term “squad” will be used for the M240B medium 

machinegun squad. The assessment was executed under the supervision of MCOTEA 

functional test managers and a range Officer in Charge (OIC)/Range Safety Officer 

(RSO) from the GCEITF. 

C.1.2 Experimental Details

The 2-day 0331 assessment replicated offensive and defensive tasks. The 0331s 

began each cycle on the Day 1/Offensive task. Three 0331 squads executed each trial 

cycle: a control (C) non-integrated group, a low-density (LD) integrated group with one 

female, and a high-density (HD) integrated group with two females.

Day 1 of the trial cycle was executed on Range 107 and consisted of supporting a 

squad attack from the support-by-fire (SBF) position then displaced to the limit of 

advance (LOA). The Machine gunners repelled an enemy counterattack by fire for 90 

seconds. Finally, each squad conducted a 100-meter CASEVAC of a 220-lb dummy. 

Day 2 of the trial cycle was executed on Range 110 and consisted of defensive actions. 

The day started with a 7-km forced march from Range 107 to Range 110 wearing an 

approach load and carrying personal weapons, crew-served weapons, and ammunition. 

Each heavy machinegun squad prepared a M2 heavy machine gun for employment. 

The squads engaged three targets based on a prescribed course of fire with 400 rounds 
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of .50-cal ammunition. Immediately upon the gun going out of action, the machinegun

squad displaced the machine gun to a designated location. The trials concluded with a 

mount and dismount of the M2 machine gun to a HMMWV. At the conclusion of Day 2, 

the Marines reorganized into new squads for the next experimental cycle.

C.1.3 Additional Context

Throughout the assessment, Marines bivouacked at Range 107, sleeping in 2-man 

tents. Prior to the experiment, each machine gun was zeroed to maximize accuracy. 

During trial execution, Marines wore/carried prescribed loads for each task. Weighing 

packs each day prior to the 7-km forced march ensured consistency. After each trial 

day, the Marines operated under the guidance of their Company leadership, performing 

minimal physically demanding tasks. The Marines who were not part of an assessed 

squad conducted the same experimental subtasks after the assessed squads to ensure 

equity between individuals participating in a trial cycle and those not chosen for that 

particular cycle. These tasks will be discussed in detail in the loading section below.

Fatigue surveys were designed to capture the volunteers’ cumulative fatigue level at the 

beginning and end of each day’s trials. The data collected provide additional insight into 

apparent aberrations in the performance level of a given volunteer on a specific day. It 

allows for outside fatigue-related factors (minor illness, lack of sleep the night before, 

etc.) to be accounted for in the analysis of the performance data. Workload surveys 

collected the volunteers’ perceived average and maximal level of exertion during the 

performance specified tasks. Cohesion surveys provided a method of collecting 

subjective data relating to each squad’s ability to work as a team and their overall 

perspective on the cohesiveness of the squad.

C.1.4 Experimental Tasks

C.1.4.1 1-km Movement 

Assaulting an enemy position never starts from a static position; first, a movement must 

be conducted to the assault position (AP). The distance from the line of departure to 

the AP is dependent upon myriad factors. Based on time and space constraints, this 

distance was set at just under 1 km for the experimental event. Each machinegun

squad moved this distance as quickly as possible while carrying an assault load in 

addition to the M240B machine gun, tripod, spare barrel, and ammunition (600 rounds 

of 7.62 mm) divided among the members. 

C.1.4.2 Occupy and Engagement from SBF Position 

Prior to commencing an assault, it is common for the machinegun section to occupy a 

position of overwatch and provide SBF for the attacking unit. Movement to a SBF 

position varies in distance based on the terrain, which is often challenging. From the 

SBF position, the machinegun squad must rapidly get their gun into action, acquire 
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targets, and accurately engage the enemy. During the assessment, each machinegun

squad moved approximately 100 meters from an AP to the SBF position and emplaced

the M240B. Once the squad leader confirmed “gun up,” they engaged targets 

presented in a predetermined course of fire. Three targets and 400 rounds were 

allocated during this course of fire. This task determined how quickly the squad could 

move to a SBF position and get the gun into action, as well as determined the squad’s

accuracy while engaging targets. 

C.1.4.3 Displace to the LOA

After providing initial suppressive fires from a SBF position to support an assault, 

machinegun squads generally move to another position of advantage. Given the 

command, they must break down their weapon system and displace to a follow-on firing 

position, quickly. During the assessment, each machinegun squad displaced from their 

initial SBF position approximately 300 meters to a LOA/secondary SBF position. From 

this new position, they prepared to repel the enemy counterattack. This task 

determined how much time it took for a machinegun squad to displace and prepare for 

an enemy counterattack.

C.1.4.4 Repel Counterattack

At the conclusion of every assault, the attacking unit must be prepared for the enemy to 

regroup and organize a counterattack. Upon consolidation at the LOA, the squad

oriented its weapons in the direction of the enemy’s retreat. Upon targets being 

presented, the counterattack commenced for 90 seconds. Two targets and 200 rounds 

were allocated during the machinegun counterattack course of fire. 

C.1.4.5 CASEVAC

Casualties are an inevitable part of conducting combat operations. Units train to 

become proficient in triaging, handling, and transporting a casualty. When a casualty is 

sustained, it is essential to move with a sense of urgency to get the injured Marine to 

the appropriate level of care. At the conclusion of the live-fire and counterattack, each 

machinegun squad moved a 220-lb dummy 100 meters from a position of cover to a 

casualty collection point (CCP) while also transporting their assault packs and crewserved weapon system (M240B, tripod, and spare barrel). The machinegun squads

could use a variety of techniques for transport but had to carry the dummy off the 

ground. This task determined the machinegun squad’s proficiency in moving a 

simulated casualty to a CCP. After the CASEVAC, each Marine took a fatigue and 

workload survey to assess overall fatigue and workload of the entire offensive task (see 

GCEITF Experimental Assessment Plan [EAP], Annex D). 
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C.1.4.6 7-km Hike

Infantry units must move through all sorts of terrain on foot. Units train by conducting a 

forced march with an approach load at a sustained rate of march. For the assessment, 

each machinegun squad moved a distance of 7.2 km as quickly as possible while 

carrying an approach load, and the M240B machine gun, tripod, spare barrel, and 

ammunition spread-loaded across all three members. This task determined the squad’s 

rate of movement over a 7.2-km route while carrying the approach load and their crewserved weapon. Each Marine took a fatigue and workload survey after completion of 

the 7.2-km hike.

C.1.4.7 M2 Emplacement, Engagement, and Displacement 

Providing defensive fires with the M2 heavy machine gun entails moving the system to a 

position of advantage, engaging the enemy, and conducting a rapid displacement. 

Oftentimes, the M2 is employed from the tripod. During the assessment, each 

machinegun squad emplaced the M2 on a tripod at a specified firing location. The 

assessment began with targets exposed and engaged by the squad. Three targets and 

400 rounds were allocated for this course of fire. Immediately upon going out of action, 

the squad displaced from the firing line to a designated location, moving a heavy load a 

short distance, manipulating a weapon while fatigued, and accurately engaging targets. 

This task determined accuracy and displacement times. 

C.1.4.8 M2 Mount and Dismount

The M2 heavy machine gun is often employed from a vehicular platform, such as a 

HMMWV. To mount this system, the squad must lift all components from the ground to 

the turret and assemble the system. Similarly, to dismount the system, the squad must 

manually lower each component to the ground. During the assessment, each 

machinegun squad worked together to mount and dismount an M2 from a HMMWV. 

This task determined the time for a squad of three Marines to fully mount and dismount 

the M2 from a tactical vehicle and required the strength to lift, manipulate, and lower 

heavy components. At completion of the mount and dismount tasks, Marines took a 

fatigue and workload survey to assess their fatigue and workload during execution (see 

GCEITF EAP, Annex D). 

At the completion of the 2-day cycle, Marines took a cohesion survey to record their 

cohesion during execution of the 2-day trial cycle.

C.1.5 Loading Plan

Due to the number of volunteers, several Marines were not part of an assessed squad 

each 2-day cycle. The loading plan ensured, to the greatest extent possible, equity of 

physical activity amongst all volunteers throughout the duration of the experimental 

assessment. Collaboration with the Company leadership determined the best method 
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of loading non-assessed Marines was to have them perform the same tasks as an 

assessed squad to experience the same conditions and physical strain. Minor 

modifications were permitted due to the reduced size of the squad, such as conducting 

a trial as the fourth Marine in a 3-Marine element when not enough individuals were 

available to form another squad. Every trial and task was conducted in the same 

manner and sequence to ensure consistency. 

C.1.6 Scheme of Maneuver Summary

The 0331 experiment consisted of a 2-day trial cycle comprising an offensive and 

defensive day. The offensive day involved five subtasks based around supporting a 

squad attack: 1-km movement, movement to and occupy a SBF position, displacement, 

repel a counterattack, and CASEVAC. The defensive day involved four subtasks: a 

7-km forced march, M2 engagement, displacement, and mount/dismount drill. During 

the course of the experiment, the 0331 machinegun squad executed 2 pilot trial cycles 

and 21 record trial cycles. During trial execution, Marines rotated through every billet 

within the machinegun squad, carrying components of the crew-served load. 

C.2 Limitations 

C.2.1 0331 Limitations Overview

The GCEITF experiment was designed to allow operationally relevant tasks to occur as 

naturally as possible, while gathering unbiased measurements. Most tasks were 

performed in a similar manner to those in an operational environment. However, under 

certain situations, artificial limitations or interruptions were introduced that changed or 

altered the way a task would normally be performed. While these limitations represent 

a degree of artificiality, they do not detract significantly from our abilities to generalize 

the conclusions of this experiment to the performance of Marines in a field environment. 

The following limitations were observed for 0331 assessment. 

C.2.2 Relative Difficulty of Record Test

The 0331 GCEITF assessment was designed to gather data associated with some of 

the most physically demanding tasks within the 0331 MOS. These tasks in isolation did

not fully replicate life experienced by a Marine during a typical field exercise (FEX) or a

combat environment and did not obtain the maximum cumulative load that could be 

placed on an 0331 Marine. With limited time available, only selected 0331 tasks were 

assessed. Other tasks/duties outside of the assessment were minimized due to specific 

experimental constraints and human factors. During a typical FEX, it is common for 

Marines to conduct 24-hour operations that include day and nighttime 

operations/patrols, standing firewatch or a security post, and conducting continuing 

tactical actions. The offensive day SOM took squads approximately 1 hour to complete, 

and the defensive day SOM took approximately 3 hours to complete. Outside the 
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assessed trials, there were minimal tasks required of the volunteers that demanded any 

degree of physical strain. 

Another concern in designing the 0331 assessment was making it was achievable and 

sustainable for a 60-day period. The 7-km forced march distance was selected based 

on the training time available prior to the assessment. However, many of the loads 

carried were decreased; the crew-served load was altered from the M2 heavy machine

gun to the M240B medium machinegun. Marines were authorized 1 day off after every 

4 days of training; this artificial recovery period is not achievable when conducting 

training or combat operations. 

A final factor affecting the relative difficulty of the record test pertains to the intangible 

physiological impact of the volunteers’ ability to DOR at any point during a trial. Any

time a volunteer dropped during a trial cycle, that squad performed the following 

subtasks with fewer personnel. This factor could have affected the cohesion of each 

squad and influenced its performance. 

C.2.3 Geometries of Fire and Conditions Set 

Several artificialities were present during the M240B live-fire portion of the assessment. 

Although the SBF position was realistic, the geometries of fire for the initial and 

secondary position were offset to prevent fires from interfering with the rifle-squad 

assessment. The machinegun course of fire began when they reached the SBF 

position, rather than waiting for the tactical conditions to be established. The loss of 

tactical realism in basing fires off a maneuver element resulted in this task being less 

challenging than in training or combat, in which the squad leader and gunner must 

make intuitive decisions regarding rates of fire, target precedence, and shifting and 

ceasing criteria.

C.2.4 Number of Volunteer Participants

For the 0331 experiment, six male and six female volunteers began the experiment, but 

by the end five males and six females completed the assessment. The results 

presented in this annex are based on the performance of 11 to 12 Marines. 

C.2.5 Limitations Summary

The 0331 assessment was designed to replicate realistic training in a field environment. 

The end-state was to create an experiment in which the volunteers felt they were 

conducting realistic and operationally relevant tasks, but unavoidable limitations to the 

assessed tasks and non-assessed operating environment introduced a level of 

artificiality not normally present in a field training or combat environment. 
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C.3 Deviations 

C.3.1 M2 Heavy Machine Gun Employment

The EAP stated that just prior to the M2 .50-cal engagement, the Marines would be 

assessed moving the M2 and ammunition approximately 100 meters to the firing line. 

Discussion with Company leadership about the relevancy of this subtask informed the 

decision not to make the emplacement a timed event, but to administratively move the 

M2 to the firing line. This subtask was not assessed as a standalone measurement.

C.4 Data Set Description 

C.4.1 Data Set Overview

The 0331 portion of the experiment consisted of 2 pilot trial cycles and 21 record trial 

cycles. The pilot trial cycles were conducted from 2 March 2015 to 6 March 2015. Pilot 

trial data are not used in analysis due to variations in the conduct of the test. We based 

all analysis on the 21 record trial cycles executed from 7 March 2015 to 26 April 2015.

C.4.2 Record Test Volunteer Participants

At the beginning of the first record trial cycle, there were six male 0331 volunteers and 

six female volunteers. There was one male DOR. 

C.4.3 Planned, Executed and Analyzed Trial Cycles.

Table C-1 displays the number of trial cycles planned, executed and analyzed by task. 

The planned number of trials for the 0331 MOS per Section 7.5.3 of the GCEITF EAP 

was 120 trial cycles or 40 per integration level (C, LD, and HD). The original plan called 

for 6 squads per day (2 per integration level) over the 20 trial cycles. However, due to 

the number of Marines who voluntarily withdrew or were involuntarily withdrawn from 

the experiment prior to the execution of the first record trial cycle, only one squad of the 

C and HD integration levels remained. The planned number of trial cycles in Table C-1

reflects 21 planned trial cycles for each integration level. 

Of note, there are several occurrences of missing data for the 7-km hike by individual 

kilometer. The individual kilometer times were derived from GPS data. Early in the 

experiment, the Garmin GPS’s were set to record a volunteer’s position every second. 

Due to the storage space on the GPS and length of the trial, when volunteers executed 

the 7-km hike and then follow-on tasks, the GPS could not hold all of the data and 

overwrote the hike data. Once the problem was found, the GPS’s were corrected to 

record location every 2 seconds. 
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Table C-1. 0331 Planned, Executed, and Analyzed Trial Cycles1

Task and 

Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

Trials 

Conducted 

Number of 

Trials Used 

in Analysis

Notes

7-km Hike

C 21 21 21

LD 21 18 18

HD 21 21 21

M240B 

Movement & 

Emplacement

C 21 20 20 Mar 19 did not execute due to range fire

LD 21 18 18

HD 21 20 20 Mar 19 did not execute due to range fire

M240B 

Engagement

C 21 20 18 Missing Mar 27 (no TRACR); TIR Mar 12; Did not 

execute Mar 19

LD 21 18 16 Missing Mar 27 (no TRACR); TIR Apr 11

HD 21 20 19 Missing Apr 18 

CASEVAC to 

CPP

C 21 20 20 Mar 19 did not execute due to range fire

LD 21 18 18

HD 21 20 19 TIR Mar 29; Mar 19 did not execute due to range 

fire

Mount/Dismo

unt Total 

Elapsed Time

C 21 21 21

LD 21 18 18

HD 21 21 21

Displace to 

LOA; Elapsed 

Time

C 21 20 20 Mar 19 did not execute due to range fire

LD 21 18 18

HD 21 20 20 Mar 19 did not execute due to range fire

M2 

Displacement

C 21 21 21

LD 21 18 18

HD 21 21 21

1-km Hike; 

Elapsed Time

C 21 20 20

LD 21 18 18

HD 21 20 20

7-km Hike; 

1km Time

C 21 20 18 Missing Mar 13 and Mar 15

LD 21 18 15 Missing Mar 10, Mar 15, Mar 18

HD 21 21 16 Missing Mar 8, Mar 10, Mar 13, Mar 15, Mar 18 

data

7-km Hike; 

2km Time

C 21 20 18 Missing Mar 13 and Mar 15

LD 21 18 15 Missing Mar 10, Mar 15, Mar 18

HD 21 21 16 Missing Mar 8, Mar 10, Mar 13, Mar 15, Mar 18 

data

7-km Hike; 

3km Time

C 21 20 18 Missing Mar 13 and Mar 15

LD 21 18 16 Missing Mar 15 and Mar 18

HD 21 21 17 Missing Mar 8, Mar 10, Mar 15, Mar 18 data

7-km Hike; 

4km Time

C 21 20 20 Missing Mar 18 data

LD 21 18 17 Missing Mar 18 data

HD 21 21 18 Missing Mar 8, Mar 15 and Mar 18 data

7-km Hike; 

5km Time

C 21 20 20 Missing Mar 18

LD 21 18 17 Missing Mar 18

HD 21 21 19 Missing Mar 8 and Mar 18 data

7-km Hike; 

6km Time

C 21 20 20 Missing Mar 18

LD 21 18 17 Missing Mar 18 data

HD 21 21 20 Missing Mar 18 data

7-km Hike; C 21 20 19 Missing Mar 18 data; Mar 8 likely GPS data error

 

1 A TIR in this table refers to a Test Incident Report, which is a report the test team or direct assignment 

leaders completed when an incident occurred that affected the natural execution of a trial. If a data point 

is removed due to a TIR, it is because the TIR affected the data in such a way that it is not comparable to 

the rest of the data set.
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Task and 

Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

Trials 

Conducted 

Number of 

Trials Used 

in Analysis

Notes

7km Time LD 21 18 17 Missing Mar 18

HD 21 20 20 Missing Mar 18 data

M240B 

Movement

C 21 20 20 Mar 19 did not execute due to range fire

LD 21 18 18

HD 21 20 20 Mar 19 did not execute due to range fire

M240B 

Emplacement

C 21 20 20 Mar 19 did not execute due to range fire

LD 21 18 18

HD 21 20 20 Mar 19 did not execute due to range fire

M240B 

Engagement; 

Attack Hits on 

Target

C 21 20 20 Did not execute Mar 19

LD 21 18 17 Missing Apr 11

HD 21 20 20 Did not execute Mar 19

M240B 

Engagement; 

Counterattack 

hits on Target

C 21 20 18 Missing Mar 12 (TIR) and Mar 27 (no TRACR); Did 

not execute Mar 19

LD 21 18 16 Missing Mar 27 (no TRACR) and Apr 11

HD 21 20 18 Missing Apr 11 and Apr 18 run 3; Did not execute 

Mar 19

Mount M2; 

Elapsed Time

C 21 21 21

LD 21 18 18

HD 21 21 21

Dismount M2; 

Elapsed Time

C 21 21 21

LD 21 18 18

HD 21 21 21

M2 Percent 

Hits

C 21 21 21

LD 21 18 17 Mar 13 TRACR recorded greater than 400 hits

HD 21 21 19 Apr 2 and Apr 9 TRACR recorded greater than 400 

hits

C.5 Descriptive and Basic Inferential Statistics 

C.5.1 Descriptive Statistics Overview

Performance metrics were measured during the conduct of common infantry tasks and 

are indicative of unit-level proficiency during either field exercises or combat operations. 

This section presents the descriptive statistics results for 7 tasks out of 21 tasks. The 

Appendix to this Annex contains the descriptive statistics for the remainder of the 0331 

tasks. The words “metric” and “task” are used interchangeably throughout this Annex; 

both refer to the experimental task.

Each machinegun squad consisted of three volunteer Marines: the gunner, assistgunner, and ammo man. A direct assignment (non-volunteer) squad leader led each 

squad. There were three integration levels for all tasks. A C group was all male, a LD

group had one female, and a HD group had two females.

This section includes experimental results based on descriptive statistics, analysis of 

variance (ANOVA), Tukey Tests (or non-parametric tests as necessary), and scatter 

plots. The subsequent sections will cover each task in detail. Lastly, contextual 

comments, additional insights, and subjective comments (as applicable) tying back to 

each experimental task are incorporated.
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Special caution should be taken when comparing similar tasks executed by different 

MOSs within the GCEITF experiment. Comparative analysis may be misleading due to 

differing factors between MOS tasks, such as distances, techniques, leadership, load 

carried, group size, and group composition.

C.5.2 0331 Selected Tasks Descriptive Statistics Results

The two tables below display the results for the seven selected 0331 metrics. Table C-2

displays the metrics and integration levels with their respective sample sizes, means, 

and standard deviations. Table C-3 displays ANOVA and Tukey Test results, including 

metrics and integration levels, p-values suggesting statistical significance, integration 

level elapsed time differences, and percentage differences between integration levels. 

For each task, an ANOVA was conducted to compare the three groups and Tukey Tests 

were conducted to compare each pair of two groups. If non-parametric tests were 

needed, Table C-3 displays these results instead of ANOVA and Tukey Test results. If 

p-values are less than the a-priori determined significance level of 0.10, we conclude 

that there is statistical evidence that the response was not found to be the same across 

all three groups. 

Table C-2. 0331 Selected Task Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD

7km Hike (minutes)*

C 21 86.44 6.76

LD 18 113.29 14.75

HD 21 117.30 14.65

M240B Movement & 

Emplacement

(minutes)*

C 20 2.55 0.31

LD 18 2.90 0.37

HD 20 3.32 0.46

M240B Engagement

(% hits)† 

C 18 33.08% 17.23%

LD 16 38.07% 15.07%

HD 19 27.34% 12.75%

CASEVAC

(minutes)† 

C 20 2.23 0.51

LD 18 3.11 1.72

HD 19 3.95 1.88

CASEVAC [excluding 

potential influential 

points] (minutes)*

C 20 2.23 0.51

LD 15 2.41 0.65

HD 17 3.38 0.86

M2 Mount/Dismount

(minutes)

C 21 3.95 0.81

LD 18 3.94 0.64

HD 21 4.35 1.03

M240B Displace to LOA 

(minutes)† 

C 20 3.75 0.36

LD 18 4.58 0.68

HD 20 4.74 0.69
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Metric Integration 

Level

Sample 

Size Mean SD

M2 Displacement 

(minutes)*

C 21 1.11 0.24

LD 18 1.18 0.26

HD 21 1.42 0.36

M2 Displacement 

[excluding potential 

influential points]

(minutes)*

C 21 1.11 0.24

LD 18 1.18 0.26

HD 20 1.34 0.16

*Indicates there is a statistically significant difference a two-sided 

hypothesis test between integration levels according to ANOVA or a nonparametric equivalent test. 

†Indicates contradicting statistical significance results between ANOVA 

and a non-parametric equivalent test.

Table C-3. 0331 Selected Task ANOVA and Tukey Test Results

Metric

F 

Statistic 

(df)

F Test 

P-Value Comparison Difference % 

Difference

PValue80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

7km Hike (minutes)†† 113.77 < 0.01*

LD-C 26.85 31.06% < 0.01* 21.86 31.83 20.37 33.32

HD-C 30.86 35.70% < 0.01* 26.24 35.48 24.87 36.85

HD-LD 4.01 3.54% 0.40 -2.15 10.18 -3.96 11.97

M240B Movement & 

Emplacement 

(minutes)*

20.07 (2, 

55) < 0.01*

LD-C 0.35 13.68% 0.02* 0.13 0.57 0.09 0.61

HD-C 0.76 29.92% < 0.01* 0.55 0.97 0.51 1.02

HD-LD 0.41 14.28% < 0.01* 0.20 0.63 0.15 0.67

M240B Engagement 

(% hits)* 

2.22 (2, 

50) 0.12

LD-C 0.05 15.08% 0.45† -0.02† 0.14† -0.03† 0.15†

HD-C -0.06 -17.35% 0.25† -0.10† 0.01† -0.13† 0.03†

HD-LD -0.11 -28.18% 0.02† -0.16† -0.04† -0.19† -0.03†

CASEVAC (minutes)* 20.56‡ < 0.01‡ 

LD-C 0.87 39.10% 0.14† 0.03† 0.63† -0.02† 0.80†

HD-C 1.71 76.67% < 0.01† 0.95† 1.55† 0.82† 1.72†

HD-LD 0.84 27.01% 0.02† 0.48† 1.25† 0.27† 1.37†

CASEVAC [excluding 

potential influential 

points] (minutes)*

14.65 (2, 

49) < 0.01*

LD-C 0.17 7.76% 0.74 -0.23 0.58 -0.31 0.66

HD-C 1.15 51.54% < 0.01* 0.76 1.54 0.68 1.62

HD-LD 0.98 40.62% < 0.01* 0.56 1.40 0.47 1.48

M2 Mount/Dismount 

(minutes)

1.54 (2, 

57) 0.22

LD-C -0.02 -0.48% 1.00 -0.49 0.45 -0.59 0.55

HD-C 0.39 9.98% 0.30 -0.06 0.85 -0.15 0.94

HD-LD 0.41 10.50% 0.29 -0.06 0.89 -0.16 0.98

M240B Displace to 

LOA (minutes)*

16.01 (2, 

55) < 0.01*

LD-C 0.83 22.23% < 0.01† 0.52† 0.87† 0.48† 0.92†

HD-C 1.00 26.58% < 0.01† 0.88† 1.22† 0.82† 1.27†

HD-LD 0.16 3.56% 0.10† 0.07† 0.55† 0.00† 0.58†

M2 Displacement 

(minutes)*

6.28 (2, 

57) < 0.01*

LD-C 0.07 5.98% 0.40† -0.03† 0.15† -0.05† 0.17†

HD-C 0.31 27.61% < 0.01† 0.22† 0.35† 0.18† 0.38†

HD-LD 0.24 20.40% 0.01† 0.13† 0.30† 0.10† 0.33†

M2 Displacement 

[excluding potential 

influential points]

(minutes)*

6.06 (2, 

56) < 0.01*

LD-C 0.07 5.98% 0.62 -0.06 0.19 -0.08 0.22

HD-C 0.23 21.15% < 0.01* 0.11 0.35 0.09 0.38

HD-LD 0.17 14.31% 0.06* 0.04 0.29 0.02 0.32
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*Indicates there is a statistically significant difference in a two-sided hypothesis test between integration 

levels according to ANOVA or a non-parametric equivalent test.

**Tukey intervals have familywise confidence of the indicated percentage, each interval is not of the given 

confidence level on its own. 

†Results presented are from Kruskal-Wallis and Mann-Whitney non-parametric tests due to nonnormality.

††Indicates results presented are from Robust ANOVA and Welch’s t-tests with p-values compared to 

0.033 for Bonferroni adjustment due to unequal variances. The reported F-statistic is a Chi-square 

statistic from Robust ANOVA, and the F-test p-value is the Robust ANOVA p-value. The p-values in 

columns labeled “2-sided P-value” and “1-sided P-value” are p-values from Welch’s t-tests, and the 

confidence intervals are from Welch’s t-tests.

‡Indicates results presented are from Robust ANOVA due to unequal variances. The reported F-statistic 

is a Chi-square statistic from Robust ANOVA, and the F-test p-value is the Robust ANOVA p-value.

C.5.2.1 7-km Hike Results

C.5.2.1.1 7-km Hike Overview

This experimental task assessed a squad of three Marines moving 7.2 km while each 

Marine carried an approach load, and individual weapon (M-4), and a portion of the 

crew-served weapon load. The crew-served load consisted of an M240B medium 

machinegun, tripod, A-bag with spare barrel, and four cans of ammo, resulting in a 

cumulative load of 118-130 lb per Marine. The recorded time for this task started when 

the squad departed the Range 107 start point and stopped when the squad arrived at 

the Range 110 stop point. The squads moved as fast as the slowest person and could 

take as many breaks as necessary.

Figure C-1 displays all 0331 7-km hike data. All data on the scatter plot are valid for 

analysis.
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Figure C-1. 7-km Hike

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.82 for the C group, 0.18 for the LD group, and 0.89 for the HD group. 

The C group had a mean time of 86.44 minutes. This time is statistically significantly 

faster than the LD mean time of 113.29 minutes and the HD mean time of 117.30 

minutes. These differences result in 31.06% (26.85 minutes) and 35.70% (30.86

minutes) degradations in time for the LD and HD groups, respectively. Additionally, the 

LD and HD groups had greater variability as shown by the 7.99- and 7.89-minute, 

respective, increases in standard deviation (SD) (6.76 minutes for the C group, 14.75 

minutes for the LD group, and 14.65 minutes for the HD group). The LD group was 

faster, on average, than the HD group. There was a 3.54% (4.01 minutes) degradation 

in hike time from the LD to HD group, but this difference is not statistically significant. 

See Table C-2 and Table C-3 for detailed analytical results.

C.5.2.1.2 7-km Hike Contextual Comments

C.5.2.1.2.1 USMC Hike Standards

The 7-km hike is a task that the following MOSs completed during the experiment: 

0311, 0331, 0341, 0351, and 0352, Provisional Infantry, Provisional Machine Gunners, 

and Combat Engineers. There are varying standards to which we can compare this 

result. The following sections define those standards as well as the one we choose as 

a comparison.

The Infantry T&R Manual (30 Aug 2013) identifies minimum standards that Marines 

must be able to perform in combat, to include standards for tactical marches. In 
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Chapter 8 of the Infantry T&R Manual in the MOS 0300 Individual Events section, task 

“0300-COND-1001: March under an approach load” is applicable to all 03XX MOSs, 

ranks PVT – LtCol. The condition and standard established by this task is: “Given an 

assignment as a member of a squad, individual weapon, and an approach load, 

complete a 20 kilometer march in under 5 hours.” The march pace required by this 

standard is 4 kilometers per hour (km/h). In Chapter 9 of the Infantry T&R Manual in the 

MOS 0302/0369 Individual Events section, tasks “0302-OPS-2001: Lead an approach 

march” and “0369-OPS-2501: Lead an approach march” are applicable to MOS 0302 

and 0369, ranks SSgt – MGySgt and 2ndLt – LtCol. The condition and standard 

established by these tasks is: “Given a mission, time constraints, an approach march 

load, organic weapons, and a route, move 24.8 miles (40 km) in a time limit of 8 hours.” 

The march pace required by this standard is 5 km/h. Appendix E of the Infantry T&R 

Manual (Load Terms and Definitions) states: “The approach march load will be such 

that the average infantry Marine will be able to conduct a 20-mile hike in 8 hours with 

the reasonable expectation of maintaining 90% combat effectiveness.” The march pace 

required by this definition is 4.02 km/h.

Chapter 3 of Fleet Marine Force Reference Publication (FMFRP) 3-02A, Marine 

Physical Readiness Training for Combat (16 Jun 2004) states: “The normal pace is 

30 inches. A pace of 30 inches and a cadence of 106 steps per minute result in a 

speed of 4.8 km/h or 3 mi/h and a rate of 4 km/h or 2.5 mi/h if a 10-minute rest halt per 

hour is taken.” Common Infantry practice today is to hike for 50 minutes and take a 10-

minute break, while maintaining an overall pace of 4 km/h (resulting in a hiking pace of 

4.8 km/h). 

Driven by the need to pick an evaluative reference standard, this report follows the T&R 

Manual’s intent to establish minimum standards and uses the 4 km/h march pace for a 

20-km march established by task 0300-COND-1001 and supported by the definition of 

an approach load. Further, while an established reference standard is required to 

anchor observed performance to the T&R program, more important information is 

provided by performance differences observed between gender integrated and nongender integrated units.

C.5.2.1.2.2 0331 7-km Hike Pace

This result is relevant to both the training and combat environment as it will take 

integrated squads more time to conduct foot movements. Per the tactical march 

standards noted above, the Marine Corps standard of hiking is 4.0 km/h. The LD and 

HD groups failed to meet this standard. The C group average pace was 5.00 km/h; the 

LD group average pace was 3.81 km/h; and the HD group average pace was 3.68 km/h, 

finishing 26.85 and 30.86 minutes behind the C group, respectively. To extrapolate this 

pace over a 20-km movement (an optimistic assumption that does not account for any 

further degradation of performance), it would take the C group 4.0 hr, the LD group 
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5.25 hr, and the HD group 5.43 hr to complete the 20-km movement, meaning the LD 

and HD groups would finish 75 and 85.8 minutes, respectively, behind the C group. 

Furthermore, on any given day (under the same environmental conditions), the C group 

was faster than the LD group 90.5% of the time (19 of 21 trial cycles) and faster than 

the HD group 100% of the time. With the exception of 5 out of 39 total integrated trials, 

the slowest C group was faster than the fastest HD group. Based on the standard 

deviations, the variation in performance of the LD and HD group is greater than twice as 

much as the variation in performance of the C group. This inconsistency in the 

performance of the integrated squads leads to greater uncertainty and less confidence 

in their future performance around their average time.

C.5.2.1.3 7-km Hike Additional Insights

The high degree of variability within the HD group can be explained by a variety of 

factors: the weather, Day 2 vs. Day 4 hike execution, or most notably the crew-served 

load that varied from 118-130 lb.

Based on the USMC standard of a 4 km/h pace over a 7.2-km route (which would result 

in a 108-minute hike completion time over the 7.2 km), the LD and HD groups were 5.29 

and 9.3 minutes slower, respectively, than that standard. In a battlefield situation, in 

which speed is essential, this delay is advantageous for the enemy. An enemy 

maneuvering at 4 km/h would have the time to move between 353-620 meters, shift 

indirect fires from preplanned targets, commit the employment of their least engaged 

unit, or conduct a spoiling attack.

Marine Corps Doctrinal Publications (MCDP) consistently emphasize the importance of 

speed. MCDP 1-3 Tactics devotes an entire chapter to “Being Faster” and states, 

“Physical speed, moving more miles per hour, is a powerful weapon in itself.” MCDP-6 

Command and Control also speaks to speed relative to the enemy and states, “The 

speed differential does not necessarily have to be a large one: a small advantage 

exploited repeatedly can quickly lead to decisive results.” Further insights may be 

gleaned from the Appendix, which shows the difference in speed by kilometer. In 

general, the difference in performance increased as the movement got longer.

C.5.2.1.4 7-km Hike Subjective Comments

For subjective comments relating to this task, see the Appendix. 

C.5.2.2 M240B Movement & Emplacement

C.5.2.2.1 M240B Movement & Emplacement Overview

This experimental task assessed the time for a three Marine squad to move

approximately 100 meters to a SBF position and prepare the M240B medium 

machinegun for firing. This task was conducted immediately after completing a 1-km 
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movement. The recorded time started immediately upon completing the 1-km 

movement, and stopped when the gunner yelled “Gun up,” indicting that it was ready to 

fire. During the emplacement process, the squad assembled the M240B, checked 

headspace and timing, and loaded the source of ammunition. A direct-assignment 

squad leader verified all procedures.

Figure C-2 displays all 0331 M240B Movement & Emplacement data. All data on the 

scatter plot are valid for analysis.

Figure C-2. M240B Movement & Emplacement

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.38 for the C group, 0.10 for the LD group, and 0.44 for the HD group.

The C group had a mean time of 2.55 minutes. This time is statistically significantly 

faster than the LD mean time of 2.90 minutes and the HD mean time of 3.32 minutes. 

These differences result in 3.68% (0.35 minute) and 29.92% (0.76 minute) degradations 

in time for the LD and HD groups, respectively. Additionally, the LD and HD groups had 

greater variability as shown by the 0.06- and the 0.15-minute, respective, increases in 

SD (0.31 minutes for the C group, 0.37 minutes for the LD group, and 0.46 minutes for 

the HD group). There was a 14.28% (0.41 minute) statistically significant degradation 

from the LD to the HD group. See Table C-2 and Table C-3 for detailed analytical 

results. 

C.5.2.2.2 M240B Movement and Emplacement Contextual Comments

This result is relevant to the combat environment as it will take integrated squads more 

time to move and initiate supporting fires. On average, it took the LD group 27 seconds 

longer and the HD group 46 seconds longer to conduct this movement and 
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emplacement. Furthermore, on any given day (under the same environmental 

conditions), the C group was faster than the LD group 82.4% of the time (14 of 17 trial

cycles) and faster than the HD group 95% of the time (19 of 20 trial cycles).

C.5.2.2.3 M240B Movement and Emplacement Additional Insights 

A purely objective evaluation of 27-46 seconds is elusive but may possess some 

practical significance on the battlefield that would reduce the survivability of an 

integrated squad. Considering the 650 rounds-per-minute sustained rate of fire for the 

Russian RPK-47 machinegun, a single enemy machinegun squad would have the 

opportunity fire 292-498 rounds against the pinned down squad prior to the initiation of 

friendly suppression by an integrated squad. The resultant trade in casualty exchange 

could be significant.

C.5.2.2.4 M240B Movement and Emplacement Subjective Comments

For subjective comments relating to this task, see the Appendix. 

C.5.2.3 M240B Engagement

C.5.2.3.1 M240B Engagement Overview

This experimental task assessed the accuracy of a medium machinegun squad 

engaging GTSs with 400 rounds during an attack and 200 rounds during a 

counterattack. Machine gun squads engaged three GTSs during the attack and two 

during the counterattack. Each GTS captured the precise location of a round that 

passes within 3 meters of the location of hit and miss (LOMAH) sensor. A significant 

limitation of the GTS was that it did not capture any data that impacted the low (the 

berm of the target). The accuracy was determined by dividing the number of rounds 

detected on each target by the total amount of ammunition expended by each squad.

Figure C-3 displays all 0331 M240B Engagement data. All data on the scatter plot are 

valid for analysis.
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Figure C-3. M240B Engagement

The data for the C and LD groups are normally distributed as evidenced by the ShapiroWilk Test that resulted in p-values of 0.46 and 0.05, respectively, but not normally 

distributed for the HD group, which had a p-value of 0.01. The Kruskal-Wallis Test does 

not run due to unequal samples between integration levels. 

The C group had an average percent hit of 33.08%; the LD, 38.07%; and the HD, 

27.34%. These differences from the C group result in a 15.08% (4.99 percentage 

points) degradation from the LD group and a 17.35% (5.74 percentage points) 

improvement from the HD group. Additionally, the LD group had less variability as 

shown by the 2.16 percentage point increase in SD from the C group, and the HD had 

less variability as shown by the 4.48 percentage point decrease in SD from the C group 

(17.23% for the C group, 15.07% for the LD group, and 12.75% for the HD group). 

There was a 28.18% (10.73 percentage point) degradation from the LD to the HD 

group. 

The difference in percent hits was not statistically significant between the LD and C 

groups and the HD and C groups in a two-sided Mann-Whitney Test. The difference in 

percentage hits was statistically significant between the HD and LD groups in a MannWhitney Test. This difference was not statistically significant between the HD and LD 

groups in a Tukey Test. Because of a lack of normality, we recommend using the 

Mann-Whitney test results (reported in Table C-3). See Table C-2 and Table C-3 for 

detailed analytical results. 
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C.5.2.3.2 M240B Engagement Contextual Comments

In combat operations, accuracy is highly desirable in destroying or effectively 

suppressing an enemy position. The LD squads had the highest accuracy of 38.07% 

hits, which also relates to the best conservation of ammunition.

C.5.2.3.3 M240B Engagement Additional Insights 

Although the assistance gunner has a role to play in adjusting fire, machinegun 

accuracy primarily rests on the skill of the gunner. It is important to note that during the 

course of the experiment, there were a total of 16 LD trials. Of these LD trials, a female 

served as the gunner on only 2 occasions (12.5%), both times during which the 

accuracy was below the LD mean. Conversely, of 19 total HD trials a female served as 

the gunner on 14 occasions (73.7%). It is also interesting to note that the overall 

accuracy of each group had a downward (negative) trend over the course of the 

experiment. One would have expected the accuracy to improve overtime. This result 

can primarily be attributed to a loss in interest due to the repetitive nature of the task 

and a lack of feedback to the volunteers.

C.5.2.3.4 M240B Engagement Subjective Comments

For subjective comments relating to this task, see the Appendix. 

C.5.2.4 CASEVAC

C.5.2.4.1 CASEVAC Overview

This experimental task assessed the machinegun squad’s ability to move a 210-lb 

dummy a distance of 100 meters to a casualty collection point (CCP) while wearing an 

assault load, individual weapon (M4), and the M240B crew-served load. Squads could 

use a variety of techniques, but they had to move all personnel and gear the entire 

distance, as well as carry the dummy off the ground. The machinegun squad 

conducted this task at the conclusion of the counterattack engagement. Techniques 

varied from the 1-Marine (fireman) to 2-Marine carry. The recorded time started when 

Marines touched the dummy and it stopped when the dummy and all members of the 

squad arrived at the CCP.

Figure C-4 displays all 0331 M240B CASEVAC data. There are five potential influential 

points: the LD and HD on trial cycle 2, the LD and HD on trial cycle 4, and the LD on 

trial cycle 15. Because the impact of these points is unknown, we perform all analysis 

with and without these points. All data on the scatter plot are valid for analysis with 

potential influential points circled.
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Figure C-4. CASEVAC with Potential Influential Points Circled

The inclusion of the potential influential points does not change the statistical 

significance between groups. It does, however, change the SD and percent differences 

between the integration levels. Once we remove the potential influential points, the 

percent differences between the C group and LD group, as well as the C group and HD 

group, decrease. The percent difference between the LD and HD group increases. The 

SD for both the LD and HD groups decrease without the potential influential points. The 

following sections discuss results with and with the potential influential points. The 

removal of the potential influential points results in the data for the LD and HD groups 

being normally distributed.

C.5.2.4.1.1 CASEVAC Descriptive Statistics with Potential Influential Points 

The data for the C group is normally distributed as evidenced by the Shapiro-Wilk Test 

that resulted in p-value of 0.08 but not normally distributed for the LD and HD groups, 

which both had a p-values of <0.01. The Kruskal-Wallis Test does not run due to 

unequal samples between integration levels.

The C group had a mean time of 2.23 minutes; the LD, 3.11 minutes; and the HD, 3.95 

minutes. The difference from the C group results in 39.10% (0.87 minutes) and 76.67% 

(1.71 minutes) degradations in time for the LD and HD groups, respectively. 

Additionally, the LD and HD groups had greater variability, as shown by the 1.21-minute 

and 1.37-minute, respective, increases in SD (0.51 minutes for the C group, 1.72 

minutes for the LD group, and 1.88 minutes for the HD group). There was a 27.01% 

(0.84 minute) degradation in time from the LD to the HD group. 
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The difference in CASEVAC time was not statistically significant between the LD and C 

groups in a two-sided Mann-Whitney Test but is statistically significant in a one-sided 

Mann-Whitney Test. The difference in CASEVAC time was statistically significant 

between the HD and C group as well as the HD and LD group in a Mann-Whitney Test. 

The difference in CASEVAC time was not statistically significant in for the LD and C 

group in a Tukey Test. Because of a lack of normality, we recommend using the MannWhitney test results (reported in Table C-3). However, the one-sided significance

(between the LD and C groups) of the non-parametric results suggest that further study 

of this task is warranted. See Table C-2 and Table C-3 for detailed analytical results.

C.5.2.4.1.2 CASEVAC Descriptive Statistics without Potential Influential Points 

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

p-values of 0.08 for the C group, 0.10 for the LD group, and 0.22 for the HD group.

The C group had a mean time of 2.23 minutes. This time is not statistically significant 

but faster than the LD mean time of 2.41 minutes, and it is statistically significantly 

faster the HD mean time of 3.38 minutes. These differences result in a 7.76% (0.17

minutes) and 51.54% (1.15 minutes) degradation in times for the LD and HD groups, 

respectively. The LD and HD groups had greater variability, as shown by the 0.14- and 

0.35-minute, respective, increases in SD (0.51 minutes for the C group, 0.65 minutes for 

the LD group, and 0.86 minutes for the HD group). There was a 40.62% (0.98 minutes) 

statistically significant degradation from the LD to the HD group. See Table C-2 and 

Table C-3 for detailed analytical results.

C.5.2.4.2 CASEVAC Contextual Comments 

The implications of this task contain relevance to both the training and combat 

environment as a casualty must be moved expediently to a higher echelon of medical 

care. The data demonstrate that the LD group took 0.88 minutes longer than the C 

group, and the HD group took 1.72 minutes longer than the C group. Furthermore, on 

any given day (under the same environmental conditions), the C group was faster than 

the LD group 75% of the time (15 of 20 trial cycles), and faster than the HD group 100% 

of the time (19 of 19 trial cycles). Based on the standard deviations, the variation in 

performance of the LD and HD group is greater than twice as much as the variation in 

performance of the C group. This inconsistency in the performance of the integrated 

squads leads to greater uncertainty and less confidence in their future performance 

from the mean.

C.5.2.4.3 CASEVAC Additional Insights 

While the “Golden Hour” is a common medical planning construct for C2 and logistical 

support, medical literature supports a “Platinum Ten” philosophy of first response. The 

U.S. National Library of Medicine references a French article that espouses, “on the 

battlefield, the majority of casualties die within ten minutes of the trauma.” (Wounded in 
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Action: The Platinum Ten Minutes and the Golden Hour, Daban) The fundamental 

principle is that a patient needs to be correctly triaged and moved to medical care as 

fast as possible. Any time degradation will reduce the probability of survival.

C.5.2.4.4 CASEVAC Subjective Comments

There are seven instances in the leadership subjective logs that indicate integrated 

squads required extra breaks, compared to zero comments for the C group squads. 

The implication is that a C group could have maintained their CASEVAC pace for a 

longer distance, while the integrated groups could not have maintained their CASEVAC 

pace over a longer distance. Of the 21 instances stating that a Marine fireman-carried 

the dummy during integrated trials, three instances (14.3%) applied to a female, and 17 

instances (85.7%) applied to male, implying that the males were doing more of the 

workload and contributing to better performance. This is confirmed by the fact that six 

of the seven fastest LD group times were instances of a male carrying the casualty the 

entire distance.

For more subjective comments relating to this task, see the Appendix. 

C.5.2.5 M2 Mount/Dismount

C.5.2.5.1 M2 Mount/Dismount Overview

This experimental task assessed the machinegun squad’s ability to mount an M2 heavy 

machinegun onto a tactical vehicle (HMMWV) and then dismount it. A brief, nonassessed administrative pause was conducted between the mounting and dismounting 

sub-tasks. This task was conducted immediately following the M2 live-fire portion of the 

experiment. The recorded time started when Marines touched a component of the M2 

and it stopped when the last component of the M2 was back on the deck.

Figure C-5 displays all 0331 M2 Mount/Dismount data. All data on the scatter plot are 

valid for analysis.
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Figure C-5. M2 Mount/Dismount

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

p-values of 0.04 for the C group, 0.87 for the LD group, and 0.25 for the HD group.

The C group had mean time of 3.95 minutes. This time is slower (but not statistically 

significantly) than the LD mean time of 3.94 minutes but faster (but not statistically 

significantly) than the HD mean time of 4.35 minutes. These differences result in a 

0.48% (0.02 minutes) degradation from the LD group and a 9.98% (0.39 minutes) 

improvement from the HD group. Additionally, the LD group had less variability as 

shown by the 0.17-minute increase in SD from the C group, the HD had more variability 

as shown by the 0.22-minute increase in SD from the C group (0.81 minutes for the C 

group, 0.64 minutes for the LD group, and 1.03 minutes for the HD group). There was a 

10.50% (0.41 minutes) degradation from the LD to the HD group that was not 

statistically significant. See Table C-2 and Table C-3 for detailed analytical results.

C.5.2.5.2 M2 Mount/Dismount Contextual Comments 

The challenging aspect of mounting and dismounting the M2 heavy machinegun is the 

weight of the components. On average, it took the LD group less than 1 second less, 

and the HD group 24 seconds more than the C group. 

C.5.2.5.3 M2 Mount/Dismount Additional Insights 

This task began with all the equipment prestaged on the deck within 2 meters of the 

HMMWV. The Marines were not required to move the components to/from a secured 

location (armory). For an indication of the performance when moving heavy objects, 
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see the TOW Engagement data, which involved moving a 50-lb missile a distance of 

100 meters.

C.5.2.5.4 M2 Mount/Dismount Subjective Comments

For subjective comments relating to this task, see the Appendix. 

C.5.2.6 M240B Displace to LOA

C.5.2.6.1 M240B Displace to LOA Overview

This experimental task assessed a medium machinegun squad moving approximately 

300 meters to a LOA immediately after engaging targets from a SBF position. The 

recorded time started when the squad was told to displace and stopped when the tripod 

was down at the LOA.

Figure C-6 displays all 0331 M240B Displace to LOA data. All data on the scatter plot 

are valid for analysis.

Figure C-6. M240B Displace to LOA

The data for the C and HD are normally distributed as evidenced by the Shapiro-Wilk 

Test that resulted in a p-value of 0.02 and 0.05, respectively, but not normally 

distributed for the LD group, which had a p-value of <0.01. The Kruskal-Wallis Test 

does not run due to unequal samples between integration levels.

The C group had a mean time of 3.75 minutes; the LD, 4.58 minutes; and the HD. 4.74 

minutes. The difference from the C group result in a 22.23% (0.83 minutes) and 

26.58% (1.00 minute) degradation in times for the LD and HD groups, respectively. 

Additionally, the LD and HD groups had greater variability as shown by the 0.32- and 
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0.33-minute, respective, increase in SD (0.36 minutes for the C group, 0.68 minutes for 

the LD group, and 0.69 minutes for the HD group). The LD group was faster than the 

HD group. There was a 3.56% (0.16-minute) degradation in hike time from the LD to 

HD group. 

The difference in time was not statistically significant between the HD and LD groups in 

a two-sided Mann-Whitney Test but was statistically significant in a one-sided MannWhitney Test. This difference was not statistically significant in a Tukey Test. The 

difference in time was statistically significant between the LD and C groups and HD and 

C groups in a Mann-Whitney Test. Because of a lack of normality, we recommend 

using the Mann-Whitney test results (reported in Table C-3). See Table C-2 and Table 

C-3 for detailed analytical results.

C.5.2.6.2 M240B Displace to LOA Contextual Comments

The ability to close with the objective after having conducted an attack is a crucial 

aspect to maintaining the momentum during offensive operations. On average, the LD 

group took 50 seconds longer and the HD group took 59 seconds longer, which results 

in that much less time to prepare for a counterattack. Furthermore, on any given day 

(under the same environmental conditions), the C group was faster than the LD group 

94.1% of the time (16 of 17 trials) and faster than the HD group 95% of the time (19 of 

20 trials). Based on the standard deviations, the variation in performance of the LD and 

HD group is nearly than twice as much as the variation in performance of the C group. 

This inconsistency in the performance of the integrated squads leads to greater 

uncertainty and less confidence in their future performance from the mean.

C.5.2.6.3 M240B Displace to LOA Additional Insights

A purely objective evaluation of 50-59 seconds is elusive but may possess some 

practical significance on the battlefield that would reduce the survivability of an 

integrated squad. Considering the 650 rounds-per-minute sustained rate of fire for the 

Russian RPK-47 machinegun, a single enemy machinegun squad would have the 

opportunity to fire 541-639 rounds against an integrated squad while it moved to the 

LOA and was exposed to enemy fire. Similarly, the integrated squad would have that 

much less time to provide reinforcing fires against an enemy counterattack. The 

resultant trade in casualty exchange could be significant.

C.5.2.6.4 M240B Displace to LOA Subjective Comments

For subjective comments relating to this task, see the Appendix. 
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C.5.2.7 M2 Displacement

C.5.2.7.1 M2 Displacement Overview 

This experimental task assessed the machinegun squad’s ability to move an M2 heavy 

machinegun approximately 100 meters from a firing position to a rally point. The 

recorded time started when the machinegun squad yelled, “Out of action” and the time 

stopped when the entire squad arrived at the rally point.

Figure C-7 displays all 0331 M2 displacement data. There was one influential point: the 

HD on trial cycle 16. Because the impact of these points is unknown, we perform all 

analysis with and without this point. All data on the scatter plot are valid for analysis 

with the potential influential point circled.

Figure C-7. M2 Displacement with Potential Influential Point Circled

The inclusion of the potential influential points does not change the statistical 

significance between groups. It does change the SD and percent differences between 

the integration levels. Once we remove the potential influential points, the percent 

difference between both the C group and HD and the LD and HD group decreases. The 

SD for the HD groups decreases without the potential influential point. Additionally, the 

removal of the potential influential points results in the data for HD group being normally 

distributed. The following sections discuss results with and with the potential influential 

points.
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C.5.2.7.1.1 M2 Displacement Descriptive Statistics with Potential Influential Points

The data for the C and LD groups are normally distributed as evidenced by the ShapiroWilk Test that resulted in p-values of 0.03 and 0.11, respectively, but not normally 

distributed for the HD group, which had a p-value of <0.01. The Kruskal-Wallis Test 

does not run due to unequal samples between integration levels. Because of a lack of 

normality, we recommend using the Mann-Whitney test results (reported in Table C-3). 

We proceed with presenting ANOVA results because they were confirmed by MannWhitney Tests.

The C group had a mean time of 1.11 minutes. This time is faster (but not statistically 

significantly) than the LD mean time of 1.18 minutes, and it is statistically significantly 

faster the HD mean time of 1.42 minutes. These differences result in 5.98% (0.07

minutes) and 27.61% (0.31 minutes) degradations in time for the LD and HD groups, 

respectively. There was a 20.40% (0.04 minutes) statistically significant degradation 

from the LD to the HD group. See Table C-2 and Table C-3 for detailed analytical 

results. 

C.5.2.7.1.2 M2 Displacement Descriptive Statistics without Potential Influential Points

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

p-values of 0.03 for the C group, 0.11 for the LD group, and 0.26 for the HD group.

The C group had a mean time of 1.11 minutes. There is no change between the C and 

LD groups. The C group is still statistically significantly faster than the HD group as the 

HD group mean is 1.34 minutes, which results in a 21.15% (0.23-minutes) degradation. 

The HD group is still less variable than the C group (0.16 minutes for the HD group). 

There was a 14.31% (0.17 minutes) statistically significant degradation from the LD to 

the HD group. See Table C-2 and Table C-3 for detailed analytical results.

C.5.2.7.2 M2 Displacement Contextual Comments 

After an engagement, a machinegun squad must be able to breakdown their weapon 

system and move to a position of cover as rapidly as possible. On average, the LD 

group took 4 seconds longer and the HD group took 19 seconds longer, which 

translates to longer enemy exposure. On any given day (under the same environmental 

conditions), the C group was faster than the LD group 50% of the time (9 of 18 trials) 

and faster than the HD group 85% of the time (17 of 20 trials).

C.5.2.7.3 M2 Displacement Additional Comments 

One interesting comparison can be made between this task and the M240B 

Displacement. The M2 Displacement involved a shorter movement of 100 meters with 

a heavier load versus the M240B Displacement that involved a longer movement of 

300 meters with a lighter load. The data that were statistically significant (HD-C 
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comparison) reveals roughly the exact same result: a 27.61% difference and 26.58% 

difference, respectively, between the two different tasks.

C.5.2.7.4 M2 Displacement Subjective Comments

For subjective comments relating to this task, see the Appendix.

C.6 Statistical Modeling Results 

C.6.1 Statistical Modeling Overview

The previous section discussed results only as they pertain to differences due to 

integration level alone. The goal of statistical modeling as applied here is to estimate, 

simultaneously, the effect of gender integration levels and other relevant variables on 

machinegun squad performance. Refer to the Methodology Annex for a broad overview 

of the analysis plan and the variables used in the models.

For the same seven selected tasks described in the previous section, this section 

presents an overview of the analysis and results and then presents the modeling results 

for each of the tasks.

For each task, we describe the significant variables in the model and whether these 

variables are either positively or negatively correlated with the result. A negative 

correlation indicates an increase in that variable will result in a decrease in the response 

variable, which is a desired outcome for elapsed time but not a desired outcome for the 

percent hits outcome. The results report where certain patch numbers are significant 

for a given variable. The experiment tracked Marines within the machinegun squad by 

a patch number that associated their random position within the squad to a specific 

billet. Table C-4 displays the patch numbers and associated billet titles for the 

machinegun squad.

Table C-4. Patch Numbers and Billet Titles for the Machinegun Squad

Patch Number Billet Title

1 Gunner

2 Assistant Gunner

3 Ammo Man

C.6.2 0331 Selected Tasks Method of Analysis

Due to the small number of trials, a mixed effects model with all machinegun squad

members and all types of personnel data does not work for the 0331 data set. Thus, we 

model each personnel variable with integration level separately with a random effect for

who filled each position within the machinegun squad. For example, age for each 

member of the machinegun squad (three variables), a random effect for who filled each 
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billet, and integration level are modeled with the result (response time or percentage

hits) as the response variable. Where maximum likelihood estimation converged, AIC 

was used for variable selection. Otherwise, we comment on the significance of 

individual variables in the full model. Variables reported as significant are concluded to 

be significant based on at least a one-sided test.

C.6.3 0331 Selected Tasks Overall Modeling Results

There are no personnel data variables that are both statistically significant and have a 

practical impact to the model. Each time personnel data variables are statistically 

significant in a model, their effects are practically negligible, conflicting, and/or 

incomplete for the machinegun squad; i.e., there are no tasks for which a variable is 

significant for all members of the machinegun squad. 

The HD and LD integration levels are significant for all models for the 7-km hike, M240B 

Movement & Emplacement, and M240B Displace to the LOA tasks. Only the HD 

integration level was significant for both the M2 Mount/Dismount task and the M2 

Displacement tasks. For each task, modeling the random effects for individuals 

participating in the task resulted in changes from the initial results in the descriptive 

statistics. These changes are described in the respective task paragraphs.

The CASEVAC and M2 Displacement tasks had potential influential points, and we 

model these tasks with and without the influential points. When modeling the 

CASEVAC with influential points, the final model with integration level has HD and LD 

integration levels significant but only the LD integration level is significant without 

influential points. Additionally, not all of the same variables remain significant when 

modeled with and without influential points. Analysis with and without potential 

influential points for the M2 Displacement task does not change the overall result of the 

effect of the integration levels. 

The M240B engagement task did not have a final model with any significant variables. 

Refer to the Section C.5.2.3 for this task for the ANOVA results.

C.6.3.1 7-km Hike

We model elapsed time for the 7-km hike as a function of each personnel variable and 

integration level in a separate mixed model. The covariates in each model are the 

values of each personnel variable for each patch number, integration level, and a 

random effect of who filled each position within the machinegun squad. For each 

model, we report statistically significant positive and negative correlations and whether 

we observe any patterns.

The models for the following variables do not run due to missing values: 

• None.
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Both the HD and the LD integration levels are significant and positively correlated with 

the response for the models that include the following personnel variables: 

• All.

Both the HD and the LD integration levels are significant and negatively correlated with 

the response for the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the 7-km hike time: 

• Height of patch 2,

• Rifle score of patches 2 and 3.

The following variables are significant in their respective models and are negatively 

correlated with the 7-km hike time: 

• Squad leader,

• Weight of patches 1 and 3, 

• AFQT score of patch 1, 

• GT score of patch 3, 

• CFT MTC of patch 2, 

• CFT MANUF time of patch 2,

• PFT crunches of patch 2,

• PFT three-mile run time of patch 2.

Because the effects of the personnel variables do not have any patters and their effects

are often negligible, our final model includes integration level only where HD has a 

difference of 31.48 minutes when compared to a C group. The comparison yields a 

statistically significant p-value of <0.01. This difference is an increase from the 30.86-

minute difference identified in the descriptive statistics, which is a 2.01% change. The 

LD integration level has a statistically significant difference of 25.13 minutes when 

compared to a C group and a p-value of <0.01. This difference is a decrease from the 

26.85-minute difference identified in the descriptive statistics, which is a 6.41% change.

C.6.3.2 M240B Movement & Emplacement

We model elapsed time for the M240B Movement & Emplacement as a function of each 

personnel variable and integration level in a separate mixed model. The covariates in 

each model are the values of each personnel variable for each patch number, 

integration level, and a random effect of who filled each position within the machinegun 
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squad. For each model, we report statistically significant positive and negative 

correlations and whether we observe any patterns.

The models for the following variables do not run due to missing values: 

• None.

Both the HD and the LD integration levels are significant and positively correlated with 

the response for the models that include the following personnel variables: 

• All.

Both the HD and the LD integration levels are significant and negatively correlated with 

the response for the models that include the following personnel variables: 

• None. 

The following variables are significant in their respective models and are positively 

correlated with the M240B movement and emplacement time:

• Age of patches 1 and 2,

• Height of patch 3,

• Weight of patch 3,

• CFT MANUF time of patches 1 and 2.

The following variables are significant in their respective models and are negatively 

correlated with the M240B movement and emplacement time:

• AFQT score of patch 2,

• GT score of patch 2,

• CFT MTC of patch 3.

Because the effects of the personnel variables do not have any patters and their effects 

are often negligible, our final model includes integration level only where HD has a 

difference of 0.80 minutes when compared to a C group and a statistically significant pvalue of <0.01. This difference is an increase from the 0.76-minute difference identified 

in the descriptive statistics, which is a 5.26% change. The LD integration level has a 

difference of 0.38 minutes when compared to a C group with a statistically significant pvalue of <0.01. This difference is an increase from the 0.35-minute difference identified 

in the descriptive statistics, which is an 8.57% change.

C.6.3.3 M240B Engagement

We model percent hits for the M240B engagement as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and 
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a random effect of who filled each position within the machinegun squad. For each 

model, we report statistically significant positive and negative correlations and whether 

we observe any patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

model that includes the following variables:

• None.

The LD integration level is significant and positively correlated with the response for the 

model that includes the following variables:

• AFQT score, 

Both the HD and LD integration levels are significant and negatively correlated with the 

response for the model that includes the following variable:

• PFT crunches.

The HD integration level is significant and negatively correlated with the response for 

the model that includes the following variable:

• PFT 3-mile run.

The following variables are significant in their respective models and are positively 

correlated with the M240B engagement percent hits: 

• AFQT score of patches 1 and 2,

• GT score of patch 1.

The following variable is significant in its respective models and is negatively correlated 

with the M240B engagement percent hits: 

• Age of patch 1.

The models for the following variables have no significant variables in the model: 

• Squad leader, 

• Height, 

• Weight, 

• CFT MTC,

• CFT MANUF, 

• Rifle score.
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Because integration level is not significant in the final model and there are no variables 

that are significant for the whole squad, there is no final mixed effects model for this 

task. Refer to Section C.5.2.3 for this task to see the ANOVA results for differences 

between integration levels. 

C.6.3.4 CASEVAC

We model elapsed time for the CASEVAC as a function of each personnel variable and 

integration level in a separate mixed model. The covariates in each model are the 

values of each personnel variable for each patch number, integration level, and a 

random effect of who filled each position within the machinegun squad. For each 

model, we report statistically significant positive and negative correlations and whether 

we observe any patterns.

There were five potential influential points for this task. Therefore, we model this task 

with and without the influential points to determine if the influential points affect the 

outcome.

C.6.3.4.1 CASEVAC with potential influential points

The models for the following variables do not run due to missing values: 

• None.

Both the HD and LD integration levels are significant and positively correlated with the 

response for the models that include the following variables: 

• Squad leader, 

• Age, 

• Height, 

• CFT MANUF, 

• PFT crunches, 

• Rifle score.

The HD integration level is significant and positively correlated with the response for the 

model that includes the following variable:

• GT score.

The LD integration level is significant and positively correlated with the response for the 

model that includes the following variable:

• PFT 3-mile run.
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Both the HD and LD integration levels are significant and negatively correlated with the 

response for the models that include the following variables: 

• None.

The following variables are significant in their respective models and are positively 

correlated with the CASEVAC time: 

• Age of patches 1 and 3,

• Height of patch 3, 

• CFT MTC of patches 1 and 2.

The following variables are significant in their respective models and are negatively 

correlated with the CASEVAC time: 

• Height of patch 1,

• Weight of patch 1

• AFQT score of patch 1.

Because the effects of the personnel variables do not have any patters and their effects 

are often negligible, our final model includes integration level only where HD has a 

statistically significant difference of 1.43 minutes when compared to a C group and a pvalue of 0.05. This difference is a decrease from the 1.71-minute difference identified in 

the descriptive statistics, which is a 16.37% change. The LD integration level has a 

difference of 0.79 minutes when compared to a C group and a one-sided statistically 

significant p-value of 0.05. This difference is a decrease from the 0.87-minute 

difference identified in the descriptive statistics, which is a 9.20% change.

C.6.3.4.2 CASEVAC without potential influential points

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following variables: 

• All. 

The LD integration level is significant and positively correlated with the response for the 

models that include the following variables:

• CFT MTC, 

• PFT 3-mile run.

Both the HD and LD integration levels are significant and negatively correlated with the 

response for the models that include the following variables: 
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• None.

The following variables are significant in their respective models and are positively 

correlated with the CASEVAC time: 

• Age of patches 2 and 3, 

• CFT MANUF time of patch 2.

The following variables are significant in their respective models and are negatively 

correlated with the CASEVAC time: 

• AFQT score of patches 2 and 3,

• GT score of patches 2 and 3,

• CFT MTC of patches 1 and 3,

• PFT three-mile run time of patch 1.

Because the effects of the personnel variables do not have any patters and their effects 

are often negligible, the final model includes integration level only where HD has a 

statistically significant difference of 1.17 minutes when compared to a C group and a pvalue of <0.01. This difference is an increase from the 1.15-minute difference identified 

in the descriptive statistics, which is a 1.74% change. The LD integration level was not 

significant in the final model.

C.6.3.5 M2 Mount/Dismount 

We model elapsed time for the M2 Mount/Dismount as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and 

a random effect of who filled each position within the machinegun squad. For each 

model, we report statistically significant positive and negative correlations and whether 

we observe any patterns. 

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following variables:

• GT score, 

• CFT MTC. 

The LD integration level is significant and positively correlated with the response for the 

models that include the following variables:

• None.
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Both the HD and LD integration levels are significant and negatively correlated with the 

response for the models that include the following variables: 

• None.

The following variables are significant in their respective models and are positively 

correlated with the M2 mount/dismount time:

• Rifle score of patch 2. 

The following variables are significant in their respective models and are negatively 

correlated with the M2 mount/dismount time:

• CFT MTC of patch 3,

• PFT three-mile run of patch 3.

The models for the following variables have no significant variables in the model: 

• Squad leader, 

• Age, 

• Height, 

• Weight, 

• AFQT score, 

• CFT MANUF.

Because the effects of the personnel variables do not have any patters and their effects 

are often negligible, the final model includes integration level only where HD has a 

statistically significant difference of 0.41 minutes when compared to a C group and a 

one-sided p-value of 0.07. This difference is an increase from the 0.39-minute 

difference identified in the descriptive statistics, which is a 5.13% change. The LD 

integration level was not significant in the final model.

C.6.3.6 M240B Displace to the LOA

We model elapsed time for M240B displace to the LOA as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and 

a random effect of who filled each position within the machinegun squad. For each 

model, we report statistically significant positive and negative correlations and whether 

we observe any patterns.

The models for the following variables do not run due to missing values: 

• None.
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Both the HD and LD integration levels are significant and positively correlated with the 

response for the following models:

• All.

Both the HD and LD integration levels are significant and negatively correlated with the 

response for the models that include the following variables: 

• None.

The following variables are significant in their respective models and are positively 

correlated with the M240B displace to the LOA time: 

• Age of patches 1 and 2,

• Height of patch 2,

• Weight of patch 2,

• CFT MANUF time of patches 1 and 3,

• PFT three-mile run time of patch 1. 

The following variables are significant in their respective models and are negatively 

correlated with the M240B displace to the LOA time: 

• AFQT score of patch 3,

• GT score of patch 3,

• CFT MTC of patch 2,

• PFT crunches of patch 3.

Because the effects of the personnel variables do not have any patters and their effects 

are often negligible, our final model includes integration level only where HD has a 

statistically significant difference of 1.14 minutes when compared to a C group and a pvalue of <0.01. This difference is an increase from the 1.00-minute difference identified 

in the descriptive statistics, which is a 14.00% change. The LD integration level has a 

statistically significant difference of 0.90 minutes when compared to a C group and a pvalue of <0.01. This difference is an increase from the 0.83-minute difference identified 

in the descriptive statistics, which is an 8.43% change.

C.6.3.7 M2 Displacement

We model elapsed time for the M2 displacement as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and 

a random effect of who filled each position within the machinegun squad. For each 
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model, we report statistically significant positive and negative correlations and whether 

we observe any patterns.

There was one potential influential point for this task. Therefore, we model this task 

with and without the influential point to determine if the influential points affect the 

outcome.

C.6.3.7.1 M2 Displacement with potential influential points

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following variables: 

• Squad leader, 

• Age, 

• Height, 

• Weight, 

• AFQT score, 

• GT score, 

• CFT MANUF, 

• PFT crunches, 

• Rifle score.

The LD integration level is significant and positively correlated with the response for the 

models that include the following variables: 

• None.

Both the HD and LD integration levels are significant and negatively correlated with the 

response for the models that include the following variables: 

• None. 

The following variables are significant in their respective models and are positively 

correlated with the M2 displacement time: 

• Age of patch 3,

• CFT MTC of patches 1 and 2. 

The following variables are significant in their respective models and are negatively 

correlated with the M2 displacement time: 
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• AFQT score of patch 3,

• GT score of patch 3,

• PFT crunches of patch 1.

The model for the following variable has no significant variables in the model:

• PFT 3-mile run.

Because the effects of the personnel variables do not have any patters and their effects 

are often negligible, our final model includes integration level only where HD has a 

statistically significant difference of 0.31 minutes when compared to a C group and a pvalue of <0.01. This difference is the same as the 0.31 minute difference identified in 

the descriptive statistics. The LD integration level was not significant in the final model.

C.6.3.7.2 M2 Displacement without potential influential points

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following variables: 

• Squad leader, 

• Age, 

• Height, 

• Weight, 

• AFQT score, 

• GT score, 

• CFT MANUF, 

• PFT crunches, 

• Rifle score. 

The LD integration level is significant and positively correlated with the response for the 

models that include the following variables: 

• Weight,

• AFQT score.

Both the HD and LD integration levels are significant and negatively correlated with the 

response for the models that include the following variables: 

• None. 
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The following variables are significant in their respective models and are positively 

correlated with the displacement from M2 firing position time: 

• Age of patch 3,

• CFT MTC of patches 1 and 2; 

• CFT MANUF time of patches 1 and 2. 

The following variables are significant in their respective models and are negatively 

correlated with the displacement from M2 firing position time: 

• Weight of patch 3,

• PFT crunches of patch 1.

The model for the following variable has no significant variables in the model:

• PFT 3-mile run.

Because the effects of the personnel variables do not have any patters and their effects 

are often negligible, our final model includes integration level only where HD has a 

statistically significant difference of 0.24 minutes when compared to a C group and a pvalue of <0.01. This difference is an increase from the 0.23-minute difference identified 

in the descriptive statistics, which is a 4.35% change. The LD integration level was not 

significant in the final model.
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Appendix to Annex C

0331 Supplemental Information

This appendix provides supplemental information for the 0331 portion of the GCEITF

experiment. It provides information regarding the GCEITF leadership subjective 

comments and additional descriptive and basic inferential statistics not described in 

Annex C.

Section 1: GCEITF Leadership Subjective Comments

The GCEITF leadership provided comments on their observations of the experiment 

throughout its execution. Table C A displays a summary of these comments broken 

down by task, integration level, gender, and type of comment.

Table C A – Summary of GCEITF Leadership Comments

Section 2. Additional Task Basic and Inferential Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. The experiment included a number of tasks and associated metrics 

conducted to enhance operational realism and maintain consistent application of the 

experimental process. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

Task and Metric 

Description Gender Total

C LD HD Total C LD HD Total C LD HD Total C LD HD Total C LD HD Total C LD HD Total C LD HD Total C LD HD Total

M 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 1 2 1 0 0 1 0 0 0 0 0 0 0 0 4

F 0 1 12 13 0 6 5 11 0 1 0 1 0 0 0 0 0 0 0 0 0 1 3 4 0 0 0 0 0 0 0 0 29

Unit 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 2 2 0 0 1 1 0 0 0 0 5

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

F 0 5 4 9 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 11

Unit 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2

M 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

F 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2

Unit 0 0 0 0 0 0 0 0 2 0 5 7 11 7 4 22 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 31

M 0 0 0 0 0 0 0 0 0 1 0 1 12 9 5 26 0 1 2 3 0 0 0 0 0 0 0 0 0 0 0 0 30

F 0 0 0 0 0 0 0 0 0 1 6 7 0 1 3 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11

Unit 0 0 0 0 0 0 0 0 0 0 1 1 0 1 4 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 2 0 2 0 1 0 1 0 0 0 0 0 0 0 0 6

F 0 7 7 14 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 15

Unit 0 0 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 3

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1

F 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

Unit 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 2

M 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

F 0 5 8 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

No category Falling behind/slowing 

movement

Requesting extra 

breaks

Requires extra 

assistance Needs no assistance Compensating for another Marine Gear pass off

M240B Engagement

Other

CASEVAC to CPP

7-km Hike

M240B Movement & 

Emplacement

Displace to LOA

M2 Displacment

1-km Hike

M2 Mount/Dismount
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AUGUST 2015 C-42

This section presents results for fifteen additional 0331 tasks. Annex C contains the 

descriptive statistics for the remainder of the 0331 tasks. The words “metric” and “task” 

are used interchangeably throughout this Appendix; they both refer to the experimental 

task. 

The two tables below display the results for fifteen additional 0331 metrics. Table C B

displays the metrics and integration levels with their respective sample sizes, means, 

standard deviations, and percent differences between integration levels. 

Table C C displays ANOVA and Tukey Test results, including metrics and integration 

levels, and p-values suggesting statistical significance. For each task, an ANOVA was 

conducted to compare the three groups and Tukey Tests were conducted to compare 

groups in pairs. If non-parametric tests were needed, Table C C displays these results 

instead of ANOVA and Tukey Test results. If p-values are less than the a-priori 

determined significance level of 0.10, we conclude that there is statistical evidence that 

the result was not found to be the same across all three groups. We present inferential 

statistics for eight additional tasks.

Table C B – 0331 Test Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD % Difference(LD-C)

% Difference

(HD-C)

% Difference

(HD-LD)

1-km Hike 

(minutes)

C 20 8.74 0.51

LD 18 10.28 0.69 17.62% 19.57% 1.65%

HD 20 10.45 0.59

7-km Hike; 

first km 

(minutes)

C 18 9.42 1.25

LD 15 11.91 1.04 23.62% 29.69% 2.67%

HD 16 12.22 1.33

7-km Hike; 

second km 

(minutes)

C 18 10.03 0.77

LD 15 13.49 1.96 34.50% 39.65% 3.83%

HD 16 14.01 2.13

7-km Hike; 

third km 

(minutes)

C 18 10.03 0.90

LD 16 13.07 2.96 30.25% 49.46% 14.75%

HD 17 15.00 3.35

7-km Hike; 

fourth km 

(minutes)

C 20 11.40 2.02

LD 17 16.13 3.39 41.56% 34.45% -5.02%

HD 18 15.32 2.81

7-km Hike; 

fifth km 

(minutes)

C 20 13.92 2.09

LD 17 18.30 2.96 31.46% 39.25% 5.92%

HD 19 19.39 4.68

7-km Hike; 

sixth km 

(minutes)

C 20 14.36 2.76

LD 17 18.41 5.44 28.22% 41.79% 10.59%

HD 20 20.36 4.30

7-km Hike; 

seventh km 

C 19 13.31 3.95 29.45% 25.23% -3.26% LD 17 17.23 3.45
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Metric Integration 

Level

Sample 

Size Mean SD % Difference(LD-C)

% Difference

(HD-C)

% Difference

(HD-LD)

(minutes) HD 20 16.67 2.64

M240B 

Movement 

(minutes)

C 20 1.64 0.21

LD 18 2.09 0.47 27.44% 33.11% 4.45%

HD 20 2.18 0.22

M240B 

Emplacement 

(minutes)

C 20 0.92 0.23

LD 18 0.82 0.27 -10.93% 24.20% 39.44%

HD 20 1.14 0.41

M240B 

Engagement 

Attack (hits on 

target)

C 20 108.15 64.65

LD 17 119.82 60.35 10.79% -17.20% -25.27%

HD 20 89.55 52.88

M240B 

Engagement 

C-Atk (hits on 

target)

C 18 92.61 43.88

LD 16 107.06 42.38 15.60% -20.46% -31.19%

HD 18 73.67 48.96

M2 Mount 

(minutes)

C 21 3.09 0.69

LD 18 3.18 0.63 2.93% 9.80% 6.68%

HD 21 3.40 0.77

M2 Dismount 

(minutes)

C 21 0.67 0.16

LD 18 0.65 0.14 -2.55% 14.80% 17.80%

HD 21 0.76 0.19

M2 hits on 

target

(% hits)

C 21 42.42% 21.46%

LD 17 53.97% 20.70% 27.24% 35.93% 6.83%

HD 19 57.66% 21.79%

Table C C – 0331 ANOVA and Tukey Test Results

Metric

F 

Statisti

c (df)

F Test 

PValue Comparison P-Value 80 % 

LCB**

80% 

UCB**

90% 

LCB**

90% 

UCB**

1-km Hike 

(minutes)

49.09 

(2, 55) < 0.01*

LD-C < 0.01* 1.20 1.88 1.13 1.95

HD-C < 0.01* 1.38 2.04 1.31 2.11

HD-LD 0.66 -0.17 0.51 -0.24 0.58

7-km Hike; first km 

(minutes)

27.27 

(2, 46) < 0.01*

LD-C < 0.01* 1.74 3.22 1.59 3.37

HD-C < 0.01* 2.07 3.53 1.92 3.68

HD-LD 0.75 -0.44 1.08 -0.60 1.24

7-km Hike; second 

km (minutes)

27.95 

(2, 46) < 0.01*

LD-C < 0.01* 2.43 4.49 2.21 4.71

HD-C < 0.01* 2.96 4.99 2.75 5.20

HD-LD 0.68 -0.55 1.58 -0.76 1.80

7-km Hike; third 

km (minutes)

16.25 

(2, 48) < 0.01*

LD-C < 0.01* 1.48 4.59 1.16 4.91

HD-C < 0.01* 3.43 6.50 3.11 6.81

HD-LD 0.09* 0.35 3.51 0.02 3.83

7-km Hike; fourth 

km (minutes)

15.97 

(2, 52) < 0.01* LD-C < 0.01* 3.15 6.32 2.83 6.65

HD-C < 0.01* 2.37 5.49 2.04 5.81
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Metric

F 

Statisti

c (df)

F Test 

PValue Comparison P-Value 80 % 

LCB**

80% 

UCB**

90% 

LCB**

90% 

UCB**

HD-LD 0.66 -2.43 0.81 -2.77 1.15

7-km Hike; fifth km 

(minutes)

13.99 

(2, 53) < 0.01*

LD-C < 0.01* 2.42 6.34 2.02 6.74

HD-C < 0.01* 3.56 7.37 3.17 7.76

HD-LD 0.61 -0.90 3.07 -1.31 3.47

7-km Hike; sixth 

km (minutes)

10.39 

(2, 54) < 0.01*

LD-C < 0.01* 1.62 6.48 1.12 6.98

HD-C < 0.01* 3.67 8.33 3.19 8.81

HD-LD 0.35 -0.48 4.38 -0.98 4.88

7-km Hike; 

seventh km 

(minutes)

7.35 (2, 

53) < 0.01*

LD-C < 0.01* 1.96 5.88 1.56 6.28

HD-C < 0.01* 1.48 5.24 1.09 5.63

HD-LD 0.87 -2.50 1.37 -2.90 1.77

M240B Movement

(minutes) 71.65‡ < 

0.01‡ 

LD-C < 0.01* 0.27 0.63 0.24 0.66

HD-C < 0.01* 0.37 0.72 0.33 0.75

HD-LD 0.64 -0.08 0.27 -0.12 0.31

M240B

Emplacement 

(minutes)

7.49‡ 0.02‡

LD-C 0.59 -0.28 0.08 -0.31 0.11

HD-C 0.08* 0.05 0.39 0.01 0.43

HD-LD 0.01* 0.14 0.50 0.11 0.54

M240B 

Engagement 

Attack (hits on 

target)

1.23 (2, 

54) 0.30

LD-C 0.82 -22.44 45.79 -29.44 52.79

HD-C 0.59 -51.30 14.10 -58.02 20.82

HD-LD 0.28 -64.39 3.84 -71.39 10.84

M240B 

Engagement CAtk (hits on target)

2.33 (2, 

49) 0.11

LD-C 0.62 -12.65 41.55 -18.24 47.14

HD-C 0.43 -45.24 7.35 -50.66 12.77

HD-LD 0.09* -60.50 -6.29 -66.08 -0.71

M2 Mount

(minutes)

1.03 (2, 

57) 0.36

LD-C 0.92 -0.30 0.48 -0.38 0.56

HD-C 0.35 -0.07 0.68 -0.15 0.76

HD-LD 0.62 -0.18 0.60 -0.26 0.69

M2 Dismount

(minutes)

2.78 (2, 

57) 0.07*

LD-C 0.09* -0.11 0.08 -0.13 0.10

HD-C 0.15 0.01 0.19 -0.01 0.21

HD-LD 0.09* 0.02 0.21 0.00 0.23

M2 hits on 

target

(% hits)

2.79 (2, 

54) 0.07*

LD-C 0.23 -0.01 0.24 -0.03 0.26

HD-C 0.07* 0.03 0.27 0.01 0.29

HD-LD 0.86 -0.09 0.16 -0.11 0.19

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA.

**Tukey intervals have familywise confidence of the indicated percentage, each interval is not of the given 

confidence level on its own. 

†Results presented are from a Mann-Whitney non-parametric test due to non-normality.

‡Indicates results presented are from Robust ANOVA due to unequal variances. The reported F-statistic 

is a Chi-square statistic from Robust ANOVA, and the F-test p-value is the Robust ANOVA p-value.
GCEITF EAR ANNEX C

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Additional Task Results:

7-km Hike by km. The general trend for the 7-km hike was that the difference between 

the LD and C groups, the HD and C groups, and the HD and LD groups increased over 

the course of the hike.

1-km Hike. The data are normally distributed, as evidenced by the Shapiro-Wilk Test 

that resulted in a p-value of 0.34 for the C group, 0.28 for the LD group, and 0.67 for the 

HD group.

The C group had a mean time of 8.74 minutes. This time is statistically significantly 

faster than the LD group mean time of 10.28 minutes and the HD group mean time of 

10.45 minutes. The LD group was 17.62% slower than the C group, and the HD group 

was 19.57% slower than the C group. The HD group was 1.65% slower, and this 

difference is not statistically significant. 

• Contextual Comments. The implications of this task contain relevance to both 

the training and combat environment, as it will take integrated squads more time 

to conduct foot marches. The infantry T&R Manual states that, “The approach 

march load will be such that the average infantry Marine will be able to conduct a 

20 mile hike in 8 hours with the reasonable expectation of maintaining 90% 

combat effectiveness.” This pace equated to 2.5 mph or 4.02 km/h and 1 km 

traveled every 14.92 minutes if conducted with no breaks or stopping. While 

both groups completed the first kilometer under the required pace, the 

statistically significant difference in the group’s pace is operationally relevant. To 

extrapolate this pace (not accounting for any further degradation of performance 

or breaks taken) over a 20-km movement, on average, it would take the C group 

2:54 and the HD group 3:48. 

• The operational impact of requiring additional time to move a given distance 

would be most operationally relevant during a movement to contact or patrolling

operations. During such operations, additional time spent moving towards an 

objective area or area of interest has the potential to decreases the unit’s 

element of surprise and increases the unit’s chances of being detected prior to 

reaching their objective. This difference in pace would likely increase as the 

machine-gun team enhanced their combat load-out by adding ammunition or a 

heavy machine-gun. 

M240B Movement. The data are normally distributed, as evidenced by the ShapiroWilk Test that resulted in a p-value of 0.36 for the C group, 0.08 for the LD group, and 

0.97 for the HD group.

The C group had a mean time of 1.64 minutes. This time is statistically significantly 

faster than the LD group mean time of 2.09 minutes and the HD group mean time of 

2.18 minutes. The LD group was 27.44% slower than the C group, and the HD group 
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was 33.11% slower than the C group. The HD group was 4.45% slower than the LD 

group, and the difference is not statistically significant.

• Contextual Comments. The loss in mission capability due to additional time 

required for movement from an ORP to an SBF depends on the maneuver 

element’s scheme of maneuver, as well as the fire support plan of the supported 

maneuver commander. The enemy situation at the time of deploying a 

machinegun team from their ORP also greatly affects the importance of quickly 

reaching the SBF. The infantry T&R Manual does not specify a time standard for 

the completion of this task. The friendly situation briefed during the conduct of 

this task was that the maneuver element was waiting for the machinegun team to 

begin suppression prior to their movement towards the objective. In this case, 

time is critical and increased time taken to accomplish this task equates to longer 

friendly element exposure times.

• Subjective Comments. Throughout the conduct of this event, degraded 

performance of female participants was the cause of 10 GCEITF leadership 

subjective comments, while no comments were made due to degraded male 

performance. Of these 10 comments, 9 were due to falling behind/ slowing 

movement and 1 was made due to the participant requesting extra breaks. 

M240B Emplacement. The data are normally distributed, as evidenced by the ShapiroWilk Test that resulted in a p-value of 0.95 for the C group, 0.24 for the LD group, and 

0.34 for the HD group.

The C group had a mean time of 0.92 minutes. This time is slower (but not statistically 

significantly) than the LD group mean time of 0.82 minutes and statistically significantly 

faster than the HD group mean time of 1.14 minutes. The LD group was 10.93% faster 

than the C group, and the HD group was 24.20% slower than the C group. The HD 

group was 39.44% slower than the LD group, and the difference is statistically 

significant. 

• Contextual Comments. The loss in mission capability due to additional time 

required for emplacement of a machinegun depends on the maneuver element’s 

scheme of maneuver, as well as the fire support plan of the supported maneuver 

commander. The enemy situation at the time of deploying a machinegun team 

also greatly affects the importance of quickly reaching the SBF. The infantry 

T&R Manual does not specify a time standard for the completion of this task. 

The friendly situation briefed during the conduct of this task was that the 

maneuver element was waiting for the machinegun team to begin suppression 

prior to their movement towards the objective. In this case, time is critical and 

increased time taken to accomplish this task equates to longer friendly element 

exposure times. 
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• Subjective Comments. No further comments. 

Engage Targets (Attack). The data are normally distributed, as evidenced by the 

Shapiro-Wilk Test that resulted in a p-value of 0.40 for the C group, 0.17 for the LD 

group, and 0.03 for the HD group.

The C group had a mean of 108.15 hits on target. This number is lower (but not 

statistically significantly) than the LD group mean of 119.82 hits and higher (but not 

statistically significantly) than the HD group mean of 89.55 hits. The LD group produced

10.79% more hits than the C group, and the HD group produced 17.20% fewer hits than 

the C group. The HD group produced 25.27% fewer hits than the LD group, and the 

difference is not statistically significant. 

Engage Targets (C-Attack). The data are normally distributed, as evidenced by the 

Shapiro-Wilk Test that resulted in a p-value of 0.22 for the C group, 0.59 for the LD 

group, and 0.16 for the HD group.

The C group had a mean of 92.61 hits on target. This number is lower (but not 

statistically significantly) than the LD group mean of 107.06 hits and higher (but not 

statistically significantly) than the HD group mean of 73.67 hits. The LD group produced

15.60% more hits than the C group, and the HD group produced 20.46% fewer hits than 

the C group. The HD group produced 31.19% fewer hits than the LD group, and the 

difference is statistically significant. 

Mount M2 on Vehicle. The data are normally distributed, as evidenced by the ShapiroWilk Test that resulted in a p-value of 0.54 for the C group, 0.53 for the LD group, and 

0.43 for the HD group.

The C group had a mean time of 3.09 minutes. This time is faster (but not statistically 

significantly) than the LD group mean time of 3.18 minutes and the HD group mean time 

of 3.40 minute. The LD group was 2.93% slower than the C group, and the HD group 

was 9.80% slower than the C group. The HD group was 6.68% slower than the LD 

group, and the difference is not statistically significant. 

Dismount M2 from Vehicle. The data are normally distributed, as evidenced by the 

Shapiro-Wilk Test that resulted in a p-value of 0.01 for the C group, 0.24 for the LD 

group, and 0.05 for the HD group.

The C group had a mean time of 0.67 minutes. This time is statistically significantly 

slower than the LD group mean time of 0.65 minutes; the HD group had a mean time of 

0.76 minutes. The LD group was 2.55% faster than the C group, and the HD group was 

14.80% slower than the C group. The HD group was 17.80% slower than the LD group, 

and the difference is statistically significant in a Tukey test. 
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M2 hits on target. The data are normally distributed, as evidenced by the Shapiro-Wilk 

Test that resulted in a p-value of 0.25 for the C group, 0.94 for the LD group, and 0.07 

for the HD group.

The C group had a mean percentage hit of 42.42%. This percent is lower (but not 

statistically significantly) than the LD group percentage hit of 53.97% and statistically 

significantly lower than the HD group mean of 57.60% percentage hit with a SD of 

21.79%. The LD group was 27.24% more accurate than the C group, and the HD group 

was 35.93% more accurate than the C group. The HD group was 6.83% more accurate 

than the LD group, and the difference is not statistically significant.
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Annex D. 

Infantry Mortarman (MOS 0341)

This annex details the Infantry Mortarman (MOS 0341) portion of the Ground Combat 

Element Integrated Task Force (GCEITF) experiment executed from 2 March – 26 April 

2015 at Range 107 and Range 110, at the Marine Corps Air Ground Combat Center

(MCAGCC), Twentynine Palms, California. The sections outline the Infantry Mortarman

Scheme of Maneuver (SOM), Limitations, Deviations, Data Set Description, Descriptive 

and Basic Inferential Statistics, and Modeling Results.

D.1 Scheme of Maneuver

D.1.1 Experimental Cycle Overview

The Infantry Mortarman (MOS 0341) assessment of the GCEITF took place in a field 

environment at MCAGCC, Twentynine Palms, California. The assessment consisted of 

21 trial cycles, each of which was a 2-day test cycle, conducted over the course of 55 

days. After every 4 days of trials, the Marines spent 1 recovery day at Camp Wilson. 

Every mortar team/squad consisted of four volunteers and a direct-assignment (nonvolunteer) squad leader. Each member of the team/squad was trained to fill each billet 

within the team: gunner, assistant gunner, ammunition man 1, and ammunition man 2. 

The assessment was executed under the supervision of MCOTEA functional test 

managers and a range Officer in Charge (OIC)/Range Safety Officer (RSO) from the 

GCEITF. 

D.1.2 Experimental Details

The 2-day 0341 assessment replicated offensive and defensive tasks. The 0341s 

began each cycle on the Day 1/Offensive task, followed by the Day 2/Defensive task on 

the subsequent day. Marine volunteers formed up as a 60-mm mortar team on the first 

(offensive) day and as an 81-mm mortar squad on the second (defensive) day; on both 

days, two four-Marine squads executed the tasks: a control (C) non-integrated 

team/squad and a high-density (HD) integrated team/squad with two females. 

Day 1 of the trial cycle was executed on Range 107 and consisted of one 60-mm mortar 

team with two 2-Marine units moving together and firing the 60-mm mortar in the 

handheld mode from two different Mortar Firing Positions (MFPs). After the 

engagement, the two 2-Marine units aggregated as a 4-Marine 60-mm mortar team to 

conduct a 100-meter casualty evacuation (CASEVAC) of a 220-lb dummy. 

Day 2 of the trial cycle was executed on Range 110. Marines started the day with a 

7-km forced march from Range 107 to Range 110 while wearing an approach load, 

carrying personal weapons, and the 81-mm mortar crew-served weapon system. After 
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arriving at Range 110, the 81-mm mortar squad engaged two targets from a MFP. After 

the engagement portion of the trial, which consisted of two 5-round fire missions, the 

mortar squad moved from their engagement position back to the Objective Rally Point 

(ORP). This concluded Day 2, and the Marines reorganized into new teams/squads for 

the next trial cycle. 

D.1.3 Additional Context

Throughout the assessment, Marines bivouacked at Range 107, sleeping in 2-man 

tents. During trial execution, Marines wore/carried prescribed loads for each task. 

Weighing packs each day prior to the 7-km forced march ensured consistency. After 

each trial day, Marines operated under Company leadership, performing minimal 

physically demanding tasks. Marines not part of an assessed squad conducted the 

same experimental subtasks after the assessed squads to ensure equity between 

individuals participating in a trial cycle and those not chosen for that particular cycle. 

These tasks are discussed in detail in the loading section below.

Fatigue surveys were designed to capture the volunteers’ cumulative fatigue level at the 

beginning and end of each day’s trials. The data collected provide additional insight into 

apparent aberrations in the performance level of a given volunteer on a specific day. It 

allows for outside fatigue-related factors (minor illness, lack of sleep the night before, 

etc.) to be accounted for in the analysis of the performance data. Workload surveys 

collected the volunteers’ perceived average and maximal level of exertion during the 

performance-specified tasks. Cohesion surveys provided a way to collect subjective 

data relating to each team/squad’s ability to work as a team and their overall 

perspective on the cohesiveness of the team/squad.

D.1.4 Experimental Tasks

D.1.4.1 1-km Movement 

Assaulting an enemy location never starts from a static position; first, a movement must 

be conducted to the assault position (AP). The distance from the line of departure to 

the AP depends on myriad factors. Based on time and space constraints, this distance 

was set at just under 1 km for the experimental event. Each mortar team moved this 

distance as quickly as possible while carrying an assault load in addition to two 60-mm 

mortar tubes, two M8 auxiliary baseplates, and six 60-mm mortar rounds divided among

the members. 

D.1.4.2 60-mm Mortar Engagement 

Indirect fire is used to suppress the enemy from farther than direct-fire weapon range 

and to prepare the battlefield to allow the rifle squad to complete its mission of locate, 

close-with, and destroy the enemy by fire and maneuver. During conduct of an attack, 

60-mm mortars are often employed in the handheld mode as an assault weapon and 
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can close distance with the enemy while still ensuring they can engage. Each twoMarine mortar team engaged one target from two different MFPs with three rounds per 

MFP. This task determined the mortar team’s accuracy while engaging from two 

different positions. 

D.1.4.3 Displace to the LOA

After providing indirect fire in support of an assault, mortar teams typically move with the 

0311 squad to a limit of advance (LOA) or displace to a position of advantage. During 

the assessment, each mortar team displaced from their second MFP approximately 

300 m to a LOA/CASEVAC position. This task determined the time for a mortar team to 

displace with all equipment. 

D.1.4.4 CASEVAC

Casualties are an inevitable part of conducting combat operations. Units train to 

become proficient in triaging, handling, and transporting a casualty. When a casualty is 

sustained, it is essential to move with a sense of urgency to get the injured Marine to 

the appropriate level of care. At the conclusion of the live-fire and counterattack, each 

mortar team moved a 220-lb dummy 100 m from a position of cover to a casualty 

collection point (CCP) while transporting their assault packs and crew-served weapon 

system (two 60-mm mortar tubes and M8 auxiliary baseplate). The mortar squads

could use a variety of techniques for transport but had to carry the dummy off the 

ground. This task determined the team’s proficiency in moving a simulated casualty to 

a CCP. After the CASEVAC, each Marine took a fatigue and workload survey to assess 

overall fatigue and workload of the entire offensive task. 

D.1.4.5 7-km Hike

Moving under a load is one of the most fundamental tasks of an infantry unit; it is both 

physically and mentally demanding. Infantry units must move through all sorts of terrain 

on foot. Units train by conducting a forced march with an approach load at a sustained 

rate of march. The Infantry Training and Readiness T&R Manual states, “the approach 

load will be such that the average infantry Marine will be able to conduct a 20-mile hike 

in 8 hours with the reasonable expectation of maintaining 90% combat effectiveness.” 

During the GCEITF assessment, each mortar squad moved a distance of 7.2 km from 

Range 107 to Range 110. This route was flat (minimal elevation change) and 

conducted on an unimproved surface with varying degrees of conditions (compact dirt 

and loose sand). Each mortar squad moved as fast as the slowest person while 

carrying an approach load and the 81-mm mortar system, which consisted of the 81-mm 

mortar tube, bipods, baseplate, and sight unit spread-loaded across all four members. 

This task determined the squad’s rate of movement over a 7.2-km route while carrying 

the approach load and crew-served weapons. Each Marine took a fatigue and workload 

survey after completion of the 7.2-km hike.
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D.1.4.6 81-mm Mortar Engagement

Indirect fire is used to suppress the enemy from farther than direct-fire weapon range 

and prepare the battlefield to allow the rifle squad to complete its mission of locate, 

close-with, and destroy the enemy by fire and maneuver. During the defensive day, the 

81-mm mortar squad conducted an emplacement of the crew-served weapon, engaged 

two different targets with five 81-mm rounds each, and conducted a displacement of the 

mortar system. The mortar squad engaged the targets using the direct-lay method and 

visually acquired and adjusted all rounds during each fire mission. This task determined 

the 81-mm mortar squad’s accuracy of engaging targets from a static position. At the 

conclusion of the 81-mm mortar engagement, the Marines took a fatigue and workload 

survey to assess their fatigue and workload for the mortar engagement task (see 

GCEITF EAP, Annex D). 

At the completion of the 2-day cycle, the Marines took a cohesion survey to record their 

cohesion during execution of the 2-day trial cycle (see GCEITF EAP, Annex M). 

D.1.5 Loading Plan

The loading plan ensured, to the greatest extent possible, equity of physical activity 

among all volunteers throughout the duration of the experimental assessment. Every 

trial and task was conducted in the same manner and sequence to ensure consistency. 

Due to the number of volunteers, a handful of Marines were not part of an assessed 

squad each 2-day cycle. Collaboration with Company leadership determined that the 

best method of loading non-assessed Marines was to form them into a quasiteam/squad and have them perform the same tasks as an assessed mortar team/squad

on the offense and defense test days, respectively. This allowed the Marines to 

experience the same conditions and physical strain. Minor modifications were permitted 

because of the reduced size of the squad, e.g., conducting a trial as the fifth Marine in a 

four-Marine element because not enough individuals were available to form another 

team.

D.1.6 Scheme of Maneuver Summary

The 0341 experiment consisted of a 2-day trial cycle comprising an offensive and 

defensive day. The offensive day involved three subtasks based around supporting a 

live-fire squad attack: 1-km movement, 60-mm mortar engagement, and CASEVAC. 

The defensive day involved two subtasks: a 7-km forced march and 81-mm mortar 

engagement. During the course of the experiment, the 0341 (60-mm mortar team and 

81-mm mortar squad) executed 2 pilot trial cycles and 21 record trial cycles. During trial 

execution, Marines rotated through every billet within the mortar elements and changed 

position on the crew-served weapon system. 
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D.2 Limitations 

D.2.1 0341 Limitations Overview

The GCEITF experiment was designed to allow operationally relevant tasks to occur as 

naturally as possible, while gathering unbiased measurements. Most tasks were 

performed in a similar manner to those in an operational environment. Under certain 

situations, artificial limitations or interruptions were introduced that changed or altered 

the way a task would normally be performed. Although these limitations represent a 

degree of artificiality, they do not detract significantly from our ability to generalize the 

conclusions of this experiment to the performance of Marines in a field environment. 

The following limitations were observed for the 0341 assessment. 

D.2.2 Relative Difficulty of Record Test 

The 0341 GCEITF assessment was designed to gather data associated with some of 

the most physically demanding tasks within the 0341 MOS. These tasks in isolation do 

not fully replicate life experienced by a Marine during a typical field exercise (FEX) or a 

combat environment and did not obtain the maximum cumulative load that could be 

placed on an Infantry Marine. With limited time available, only selected 0341 tasks 

were assessed. Other tasks/duties outside the assessment were minimized due to 

specific experimental constraints and human factors. During a typical FEX, it is 

common for Marines to conduct 24-hour operations that include day and nighttime 

operations/patrols, standing firewatch or a security post, and conducting continuing 

tactical actions. The offensive day SOM took squads approximately 1 hour to complete, 

and the defensive day SOM took approximately 3 hours to complete. Outside the 

assessed trials, there were minimal tasks required of the volunteers that demanded any 

degree of physical strain. 

Another concern in designing the 0341 assessment was making it achievable and 

sustainable for a 60-day period. The 7-km forced march distance was selected based 

on the training time available prior to the assessment. However, many of the loads 

carried were decreased; the crew-served load was lightened by dropping the mortar 

rounds. The Marines were authorized 1 day off after every 4 days of training. This 

artificial recovery period is not achievable when conducting training or combat 

operations. 

A final factor affecting the relative difficulty of the record test pertains to the intangible 

physiological impact of the volunteers’ ability to drop on request (DOR) at any point 

during a trial. Any time a volunteer dropped during a trial cycle, that squad/team 

performed the following subtasks with fewer personnel. This factor could have affected 

the cohesion of each squad and influenced its performance. 
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D.2.3 Geometries of Fire 

Outside of normal safety limitations, several artificialities were present during the 60-mm 

mortar live-fire portion of the assessment. Although it is doctrinal for mortarmen to 

employ the 60-mm mortar in the handheld mode while imbedded with a rifle squad, the 

assessed mortar squads were separated by approximately 500 meters and fired

different directions to prevent any interference between units. The loss of tactical 

realism in basing fires off a maneuver element resulted in this task being less 

challenging than in training or combat, in which the team leader and gunner must make 

intuitive decisions regarding selection of a mortar firing positon, rate of fire, and target 

precedence.

D.2.4 Number of Volunteer Participants

For the 0341 experiment, nine male and four female volunteers began the experiment; 

by the end, seven males and four females completed the assessment. The results 

presented in this annex are based on the performance of 11 to 13 Marines. 

D.2.5 Limitations Summary

The 0341 assessment was designed to replicate realistic training in a field environment. 

The end-state was to create an experiment in which the volunteers felt they were 

conducting realistic and operationally relevant tasks, but unavoidable limitations to the 

assessed tasks and non-assessed operating environment introduced a level of 

artificiality not normally present in a field training or combat environment. 

D.3 Deviations 

D.3.1 60-mm Mortar Employment

The EAP for the four-Marine 60-mm mortar team called for the employment of a single 

60-mm mortar tube. Because the employment of the 60-mm mortar is only a 2-Marine 

task, Company leadership recommended employing two 60-mm mortar tubes within 

each team. The entire assessment consisted of a 4-Marine 60-mm mortar team 

employing two tubes.

D.3.2 81-mm Mortar Ammunition

Ammunition allocation for the 81-mm mortar employment was C875 (practice rounds). 

These rounds were used from 2 March to 27 March 2015. The practice rounds had a 

much smaller signature upon impact than high-explosive (HE) rounds, and, on windy 

days, it proved difficult to mark the exact location of impact with a vector/dagger. A 

request for 81-mm HE rounds was submitted and approved. From 28 March to 25 April

2015, C868 (HE rounds) were used. An ammunition shortfall required using the C875 

practice rounds for the second fire mission for both mortar teams on 26 April 2015 to 

complete the assessment. 
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D.4 Data Set Description 

D.4.1 Data Set Overview

The 0341 portion of the experiment consisted of 2 pilot trial cycles and 21 record trial

cycles. The pilot trial cycle was conducted from 2 March to 6 March 2015. Pilot trial

data are not used in the analysis due to variations in the conduct of the experiment. We 

based all analysis on the 21 record trial cycles executed from 7 March to 26 April 2015.

D.4.2 Record Test Volunteers

At the beginning of the first record trial cycle, there were nine male 0341 volunteers and 

four female volunteers. There were two male Marines who voluntarily withdrew, or were 

involuntarily withdrawn, during the execution of the experiment. The final number of 

volunteers was seven males and four females. 

D.4.3 Planned, Executed, and Analyzed Trial Cycles

Table D-1 displays number of trial cycles planned, executed, and analyzed by task. The 

planned number of trial cycles for the 0341 MOS per Section 7.5.3 of GCEITF EAP was 

120, or 40 trial cycles per planned integration level (C, low-density, and HD). The 

original plan called for six teams/squads per day (two per integration level) over the 20 

trial cycles. However, due to the number of Marines who voluntarily withdrew or were 

involuntarily withdrawn from the experiment prior to the execution of the first record trial 

cycle, only one team/squad of each of the C and HD integration levels remained. We 

chose to keep the HD integration level to employ more Marines in the experiment. 

Although the number of male and female volunteers did not support the ability to 

execute another C group during a trial cycle, there were times when another HD group 

could execute additional whole or partial trials. A partial trial was a trial in which a twoMarine unit could execute the 60-mm mortar engagement on R107 as these tasks were 

collected at the two-Marine unit level. The planned number of trials in Table D-1 reflects 

21 planned trial cycles for each integration level and accounts for the extra trials the HD 

integration level completed.

There are several occurrences of missing data for the 7-km hike by individual kilometer. 

The individual kilometer times were derived from GPS data. Early in the experiment, 

the Garmin GPSs were set to record a volunteer’s position every second. Due to the 

storage space on the GPS and the length of the trial, when volunteers executed the 

7-km hike and then follow-on tasks, the GPS could not hold all the data. Therefore, it 

overwrote the hike data. Once the problem was found, the GPSs were corrected to 

record location every 2 seconds.
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Table D-1. 0341 Planned, Executed, and Analyzed Trial Cycles1

Task and Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

Trials 

Conducted 

Number of 

Trials Used 

in Analysis

Notes

7-km Hike C 21 21 21

HD 21 23 23

60-mm Mortar 

Engagement

C 21 21 18

Remove Mar 12 due to missing data. 

Remove Mar 14 due to TIR. Remove Mar 27 

high outlier.

HD 21 23 20 Remove Mar 12 and Mar 14 due to missing 

data. Remove Mar 9 run 2 due to TIR

Displace to LOA C 21 21 21

HD 21 23 23

CASEVAC C 21 21 20 High outlier: Mar 7

HD 21 23 23

81-mm Mortar 

Emplacement and 

Displacement

C 21 21 21

HD 21 23 23

1-km Hike C 21 21 21

HD 21 23 23

7-km Hike; 1km Time C 21 21 20 No data: Mar 18

HD 21 23 21 No data: run 2 Mar 10, Mar 18

7-km Hike; 2km Time C 21 21 20 No data: Mar 18

HD 21 23 21 No data: run 2 Mar 10, Mar 18

7-km Hike; 3km Time C 21 21 20 No data: Mar 18

HD 21 23 21 No data: run 2 Mar 10, Mar 18

7-km Hike; 4km Time C 21 21 20 No data: Mar 18

HD 21 23 22 No data: Mar 18

7-km Hike; 5km Time C 21 21 20 No data: Mar 18

HD 21 23 21 High outlier: Apr 7; No data: Mar 18

7-km Hike; 6km Time C 21 21 20 No data: Mar 18

HD 21 23 22 No data: Mar 18

7-km Hike; 7km Time C 21 21 20 No data: Mar 18

HD 21 23 22 No data: Mar 18

Fire & Movement to 

MFP; Movement to 

MFP #1

C 65 65 65

HD 21 32 32

Fire & Movement to 

MFP; First Three 

Rounds

C 21 21 19 Missing shots Mar 12. Remove Mar 14 due to 

TIR.

HD 21 23 20 Missing shots Mar 12, Mar 14. Remove Mar 

9 run 2 due to TIR. 

Fire & Movement to 

MFP; Movement to 

MFP #2

C 65 65 65

HD 21 32 32

Fire & Movement to 

MFP; Second Three 

Rounds

C 21 21 19 Remove Mar 14 due to TIR. Remove Mar 27 

high outlier.

HD 21 23 22 Remove Mar 9 run 2 due to TIR.

 

1 A TIR in this table refers to a Test Incident Report, which is a report the test team or direct assignment 

leaders completed when an incident occurred that affected the natural execution of a trial. If a data point 

is removed due to a TIR, it is because the TIR affected the data in such a way that it is not comparable to 

the rest of the data set.
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D.5 Descriptive and Basic Inferential Statistics 

D.5.1 Descriptive Statistics Overview

Performance metrics were measured during the conduct of common infantry tasks and 

are indicative of unit-level proficiency during either field exercises or combat operations. 

This section presents results for 6 out of 17 tasks. The Appendix to this Annex contains 

the descriptive statistics for the remainder of the 0341 tasks. The words “metric” and 

“task” are used interchangeably throughout this Annex; they both refer to the 

experimental task. 

Each team/squad consisted of four volunteer Marines and a direct assignment (nonvolunteer) squad leader. There were two integration levels for all tasks: a C group was 

non-gender integrated, and a HD group was gender integrated with two female Marines.

This section includes experimental results based on descriptive statistics, analysis of 

variance (ANOVA) (or non-parametric tests as necessary), and scatter plots. The 

subsequent sections cover each task in detail. Lastly, contextual comments, additional 

insights, and subjective comments (as applicable) tying to each experimental task are 

incorporated. 

Use caution when comparing similar tasks executed by different MOSs within the 

GCEITF experiment. Comparative analysis may be misleading due to differing factors 

between MOS tasks, such as distances, techniques, leadership, load carried, group 

size, and group composition.

D.5.2 0341 Selected Task Descriptive Statistics Results

The two tables below display the results for the six selected 0341 metrics. Table D-2

displays the metrics and integration levels with their respective sample sizes, means, 

and standard deviations. Table D-3 displays ANOVA results, including metrics and 

integration levels, p-values suggesting statistical significance, integration level elapsedtime differences, and percentage differences between integration levels. For each task, 

an ANOVA and t-test were conducted to compare the two groups. If non-parametric 

tests were needed, Table D-3 displays these results instead of ANOVA and t-test 

results. If p-values are less than the a-priori determined significance level of 0.10, we 

conclude that there is statistical evidence that the response for the HD group is different 

from that in the C group. 

Table D-2. 0341 Selected Task Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD

7-km Hike (minutes)* C 21 93.49 6.95

HD 23 112.46 10.17

60-mm Mortar Engagement 

(minutes)*

C 18 6.75 0.70

HD 20 7.24 0.72
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Metric Integration 

Level

Sample 

Size Mean SD

Displace to LOA (minutes)*

C 21 2.71 0.30

HD 23 3.19 0.40

CASEVAC (minutes) C 20 1.69 0.51

HD 23 1.77 0.44

81-mm Mortar Emplacement & 

Displacement (minutes)

C 21 2.56 0.91

HD 23 2.51 0.92

1-km Hike (minutes)* C 21 9.51 0.61

HD 23 10.89 0.63

*Indicates there is a statistically significant difference, in either a one-sided or 

two-sided hypothesis test, between integration levels according to ANOVA or a 

non-parametric equivalent test. 

Table D-3. 0341 Selected Task ANOVA and Welch's T-Test Results

Metric

F 

statistic 

(df) 

F Test

PvalueComparison Difference % 

Difference

2-

sided 

PValue

1-sided 

P-Value 

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

7-km Hike 

(minutes)*

51.20

(1, 42) < 0.01* HD-C 18.97 20.29% < 0.01* < 0.01* 15.57 22.37 14.58 23.36

60-mm Mortar 

Engagement 

(minutes)*

4.51

(1, 36) 0.04* HD-C 0.49 7.30% 0.04* 0.02* 0.19 0.79 0.10 0.88

Displace to LOA 

(minutes)*

20.37

(1, 42) < 0.01* HD-C 0.48 17.83% < 0.01* < 0.01* 0.35 0.62 0.31 0.66

CASEVAC 

(minutes)

0.31

(1, 41) 0.58 HD-C 0.08 4.75% 0.58 0.29 -0.11 0.27 -0.17 0.33

81-mm Mortar 

Emplacement & 

Displacement 

(minutes)

0.04

(1, 42) 0.85 HD-C -0.05 -2.10% 0.88† 0.44† -

0.33† 0.32† -0.38†

0.37

†

1-km Hike 

(minutes)*

54.21

(1, 42) < 0.01* HD-C 1.48 14.49% < 0.01* < 0.01* 1.14 1.62 1.06 1.69

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test. 

†Results presented are from a Mann-Whitney non-parametric test due to non-normality.

D.5.2.1 7-km Hike

D.5.2.1.1 7-km Hike Overview

This experimental task assessed a squad of four Marines moving 7.2 km while each 

Marine carried an approach load, an individual weapon (M-4), and a portion of the crewserve weapon load. The crew-serve load consisted of the 81-mm mortar tube, 

baseplate, bipod, and sight box, resulting in a cumulative load of 118-125 lb per Marine. 

The recorded time for this task started when the squad departed the Range 107 start 

point and stopped when the squad arrived at the Range 110 stop point. The squads 

moved as fast as the slowest person and could take as many breaks as necessary. 
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Figure D-1 displays all 0341 7-km hike time data. All data on the scatter plot are valid 

for analysis.

Figure D-1. 7-km Hike

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.63 for the C group and 0.93 for the HD group. 

The C group had a mean time of 93.49 minutes. This time is statistically significantly 

faster than the HD mean time of 112.46 minutes. This difference results in a 20.29%

(18.97-minute) degradation in hike time between the groups. The HD group had greater 

variability, as shown by the 3.22-minute increase in standard deviation (SD) (6.95 

minutes for the C group and 10.17 minutes for the HD group). See Table D-2 and Table 

D-3 for detailed analytical results.

D.5.2.1.2 7-km Hike Contextual Comments

D.5.2.1.2.1 USMC Hike Standards

The 7-km hike is a task that the following MOSs completed during the experiment: 

0311, 0331, 0341, 0351 and 0352, Provisional Infantry, Provisional Machine Gunners, 

and Combat Engineers. There are varying standards to which we can compare this 

result. The following sections define those standards, as well as the one we chose as a 

comparison.

The Infantry T&R Manual (30 Aug 2013) identifies minimum standards that Marines 

must be able to perform in combat, to include standards for tactical marches. In 
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Chapter 8 of the Infantry T&R Manual in the MOS 0300 Individual Events section, task 

“0300-COND-1001: March under an approach load” is applicable to all 03XX MOSs, 

ranks PVT – LtCol. The condition and standard established by this task is: “Given an 

assignment as a member of a squad, individual weapon, and an approach load, 

complete a 20 kilometer march in under 5 hours.” The march pace required by this 

standard is 4 kilometers per hour (km/h). In Chapter 9 of the Infantry T&R Manual in the 

MOS 0302/0369 Individual Events section, tasks “0302-OPS-2001: Lead an approach 

march” and “0369-OPS-2501: Lead an approach march” are applicable to MOS 0302 

and 0369, ranks SSgt – MGySgt and 2ndLt – LtCol. The condition and standard 

established by these tasks is: “Given a mission, time constraints, an approach march 

load, organic weapons, and a route, move 24.8 miles (40 km) in a time limit of 8 hours.” 

The march pace required by this standard is 5 km/h. Appendix E of the Infantry T&R 

Manual (Load Terms and Definitions) states: “The approach march load will be such 

that the average infantry Marine will be able to conduct a 20 mile hike in 8-hours with 

the reasonable expectation of maintaining 90% combat effectiveness.” The march pace 

required by this definition is 4.02 km/h.

Chapter 3 of Fleet Marine Force Reference Publication (FMFRP) 3-02A, Marine 

Physical Readiness Training for Combat (16 Jun 2004) states: “The normal pace is 30 

inches. A pace of 30 inches and a cadence of 106 steps per minute result in a speed of 

4.8 km/h or 3 mi/h and a rate of 4 km/h or 2.5 mi/h if a 10-minute rest halt per hour is 

taken.” Common Infantry practice today is to hike for 50 minutes and take a 10-minute 

break, while maintaining an overall pace of 4 km/h (resulting in a hiking pace of 4.8 

km/h). 

Driven by the need to pick an evaluative reference standard, this report follows the T&R 

Manual’s intent to establish minimum standards and uses the 4-km/h march pace for a 

20-km march established by task 0300-COND-1001 and supported by the definition of 

an approach load. Further, although an established reference standard is required to 

anchor observed performance to the T&R program, more important information is 

provided by performance differences observed between gender-integrated and nongender-integrated units.

D.5.2.1.2.2 0341 7-km Hike Pace

The difference in 7-km hike times between the C and HD group is relevant to both the 

training and combat environment as it will take integrated squads more time to conduct 

foot marches. Per the tactical march standards noted above, the Marine Corps 

standard of hiking is 4.0 km/h. The HD group failed to meet this standard. The C group 

average pace was 4.62 km/h, and the HD group average pace was 3.84 km/h, finishing 

19.0 minutes behind the C group. To extrapolate this pace over a 20-km movement (an 

optimistic assumption that does not account for any further degradation of 

performance), it would take the C group 4 hours and 20 minutes to complete the hike, 
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and it would take the HD group 5 hours and 13 minutes to complete the hike, finishing 

52.76 minutes behind the C group.

Furthermore, on any given day (under the same environmental conditions), the C group 

was faster than the HD group 90.5% of the time (19 of 21 trial cycles). Based on the 

standard deviations, the greater variability of the HD group leads to greater uncertainty 

and less confidence in their future performance from the mean.

D.5.2.1.3 7-km Hike Additional Insights

Based on the USMC standard of a 4-km/h pace over a 7.20-km route (which would 

result in a 108-minute hike completion time over the 7.20 km), the HD group was 4.46 

minutes slower than that standard. In a battlefield situation, in which speed is essential, 

this delay is advantageous for the enemy. An enemy maneuvering at 4 km/h would 

have the time to move 297 meters, shift indirect fires from preplanned targets, commit 

the employment of their least engaged unit, or conduct a spoiling attack.

Marine Corps Doctrinal Publications (MCDPs) consistently emphasize the importance of 

speed. MCDP 1-3 Tactics devotes an entire chapter to “Being Faster” and states, 

“Physical speed, moving more miles per hour, is a powerful weapon in itself.” MCDP-6 

Command and Control also speaks to speed relative to the enemy and states, “The 

speed differential does not necessarily have to be a large one: a small advantage 

exploited repeatedly can quickly lead to decisive results.” Further insights may be 

gleaned from the Appendix, which shows the difference in speed by kilometer. In 

general, the difference in performance increased as the movement got longer.

D.5.2.1.4 7km-Hike Subjective Comments

For subjective comments relating to this task, see the Appendix. 

D.5.2.2 60-mm Mortar Engagement

D.5.2.2.1 60-mm Mortar Engagement Overview

This experimental task assessed the time for a four-Marine 60-mm mortar team (two 

mortar tubes) to move a total distance of approximately 200 meters and engage from 

two different MFPs. Each tube moved simultaneously, employing the mortar in the 

handheld method. The team moved approximately 100 meters to MFP #1, where they 

fired three rounds, and then moved approximately 100 meters to MFP #2, where they 

fired three rounds. The recorded time started immediately upon completing the 1-km 

movement and stopped when the last (6th) round was fired at MFP #2.

Figure D-2 displays all 0341 60-mm mortar-engagement time data. The C group on 

trial-cycle 9 was a high outlier due to a weapons malfunction and removed for analysis. 

This data point is circled in black. With the exception of this data point, all data on the 

scatter plot are valid for analysis. 
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Figure D-2. 60-mm Mortar Engagement

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.33 for the C group and 0.21 for the HD group. 

The C group had a mean time of 6.75 minutes. This time is statistically significantly 

faster than the HD mean time of 7.24 minutes. This difference results in a7.30%, or 

0.49-minute, degradation in time between the groups. See Table D-2 and Table D-3 for 

detailed analytical results.

D.5.2.2.2 60-mm Mortar Engagement Contextual Comments

This result is relevant to the combat environment, as it will take integrated squads more 

time to move and deliver supporting fires. On average, it took the HD group 29.4 

seconds longer, a degradation of 7.30%, to conduct this movement and engagement. 

One factor slightly masking the results is the time of flight (TOF) for each mortar round. 

Because the TOF was a constant for every squad, the actual difference in performance 

occurred during a smaller time window when the Marines were actually performing 

work. Omitting the TOF further exaggerates the difference between the two groups. 

Consider, for instance, the average TOF from MFP #1 and MFP #2 was 27 seconds. 

Assuming each tube fired all six rounds simultaneously (a conservative assumption), 

the total amount of time the team would be waiting would be 1.67 minutes (waiting on 

the 1st, 2nd, 4th, and 5th rounds to impact prior to adjusting fire). The resultant 

engagement time for the C group is 5.08 minutes and for the HD group, 5.57 minutes. 

Based on this information, the HD group was closer to 9.65% slower than the C group.
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D.5.2.2.3 60-mm Mortar Engagement Additional Insights

A purely objective evaluation of a 29.4-second average delay is elusive but may 

possess some practical significance. Considering the 650 rounds-per-minute sustained 

rate of fire for the RPK-74 machinegun, a single enemy fighter would have the 

opportunity to fire 318 rounds against Marines conducting an assault in an integrated 

squad. The resultant trade in casualty exchange could be significant.

D.5.2.2.4 60-mm Mortar Engagement Subjective Comments 

For subjective comments relating to this task, see the Appendix. 

D.5.2.3 Displace to LOA

D.5.2.3.1 Displace to LOA Overview

This experimental task assessed the time for a 60-mm mortar team to displace 

approximately 300 meters from MFP #2 to an LOA immediately after conducting an 

assault. The recorded time started after the sixth round was fired by the team and 

stopped when the last member of the team arrived at the LOA.

Figure D-3 displays all 0341 displace to LOA time data. All data on the scatter plot are 

valid for analysis.

Figure D-3. Displace to LOA

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.64 for the C group and 0.43 for the HD group. 
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The C group had a mean time of 2.71 minutes. This time is statistically significantly 

faster than the HD mean time of 3.19 minutes. This difference results in a17.83%, or 

0.48-minute, degradation in hike time between the groups. The HD group had greater 

variability, as shown by the 0.10-minute increase in SD (0.30 minutes for the C group 

and 0.40 minutes for the HD group). See Table D-2 and Table D-3 for detailed 

analytical results.

D.5.2.3.2 Displace to LOA Contextual Comments

The ability to close with the objective after having provided indirect fires is crucial to 

maintaining the momentum during offensive operations. In this case, the integrated 

squads would have taken 23.4 seconds longer to begin providing additional indirect fire 

support from the LOA, a degradation of 17.83%. On any given day (under the same 

environmental conditions), the C group was faster than the HD group 76.2% of the time 

(16 of 21 trial cycles). 

D.5.2.3.3 Displace to LOA Additional Insights

A purely objective evaluation of 23.4 seconds is elusive but may possess some practical 

significance when considering a unit in contact. Consider an enemy 82-mm mortar 

system outside the range of friendly direct fire weapons (1800 m for .50 cal). In lieu of 

an 82-mm mortar firing table, an 81-mm mortar firing table reveals the maximum range 

on charge 1 is 1920 meters with a TOF of 20 seconds. Each enemy mortar tube would 

have the time to fire a round, make an adjustment, and fire another round by the time an 

integrated 60-mm mortar team is prepared to fire. The resultant trade in casualty 

exchange could be significant.

D.5.2.3.4 Displace to LOA Subjective Comments

For subjective comments relating to this task, see the Appendix. 

D.5.2.4 CASEVAC

D.5.2.4.1 CASEVAC Overview

This experimental task assessed the 60-mm mortar team’s ability to move a 220-lb 

dummy a distance of 100 meters to a CCP while wearing a fighting load, individual 

weapon, and two 60-mm mortar tubes. The team conducted this task at the conclusion 

of the 60-mm mortar engagement and movement to the LOA. Teams could use a 

variety of techniques, but they had to move all personnel and gear the entire distance 

and carry the dummy off the ground. Time started when Marines touched the dummy 

and stopped when the dummy and all members of the fireteam arrived at the CCP.

Figure D-4 displays all 0341 CASEVAC time data. The C group on trial cycle 1 was a 

high outlier and removed for analysis. This data point is circled in black. With the 

exception of this data point, all data on the scatter plot are valid for analysis.
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Figure D-4. CASEVAC

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.73 for the C group and 0.99 for the HD group. 

The C group had a mean time of 1.69 minutes. This time is faster (but not statistically 

significant) than the HD mean time of 1.77 minutes. This difference results in a 4.75%, 

or 0.08-minute, degradation in time between the groups. See Table D-2 and Table D-3

for detailed analytical results.

D.5.2.4.2 CASEVAC Contextual Comments

The implications of this task contain relevance to both the training and combat 

environment as a casualty must be moved expediently to a higher echelon of medical 

care. The data demonstrates that integrated squads took 4.8 seconds longer, a 

degradation of 4.75%.

D.5.2.4.3 CASEVAC Additional Insights

Although the “Golden Hour” is a common medical planning construct for C2 and 

logistical support, medical literature supports a “Platinum Ten” philosophy of first 

response. The U.S. National Library of Medicine references a French article that 

espouses, “on the battlefield, the majority of casualties die within 10 minutes of the 

trauma.” (Wounded in Action: The Platinum Ten Minutes and the Golden Hour, Daban) 

The fundamental principle is that a patient needs to be correctly triaged and moved to 

medical care as fast as possible. Any time degradation will reduce the probability of 

survival. 
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D.5.2.4.4 CASEVAC Subjective Comments

The GCEITF leadership subjective comment log sheds further light on the results as it 

indicates this task was primarily conducted by an individual Marine using the fireman

carry technique. Therefore, the results are highly indicative of the strength/performance 

of an individual rather than the effort of the team as a whole. A total of 36 comments 

indicated that an individual Marine carried the casualty for the entire event, 18 of which 

applied to the C group and 18 that applied to the HD group. 

In analyzing frequency of subjective comments of the HD trials, a single male carried 

the dummy for 16 trials and a single female carried the dummy for 2 trials. On both 

occasions, it was the same female Marine. This documentation indicates that female 

Marines were not carrying as much of the cumulative load as their male counterparts 

during the CASEVAC task. Furthermore, because the C group's average time of 1.69 

minutes is reasonably close to the HD group's mean time of 1.77 minutes, it can be 

assumed that male participation in both groups would have the same time when 

participating in a HD trial. It is also possible that the two trials in which a female carried 

the dummy was a large factor in the 4.75% reduction in performance.

For additional subjective comments relating to this task, see the Appendix. 

D.5.2.5 81-mm Mortar Emplacement & Displacement

D.5.2.5.1 81-mm Mortar Emplacement & Displacement Overview

This experimental task assessed the mortar squad’s ability to move an 81-mm mortar 

system and 10 mortar rounds approximately 100m from an ORP to a MFP, get the 

mortar system fire capable (FIRECAP), and conduct a displacement back to the ORP. 

Although it was not assessed for time, the squad engaged two targets with five rounds 

each after the mortar system was FIRECAP. The recorded time started when the 

squad departed the ORP and paused when the first round was fired. The time resumed 

when the last (10th) round was fired and stopped when the entire squad was back at 

the ORP.

Figure D-5 displays all 0341 displace to LOA time data. All data on the scatter plot are 

valid for analysis.
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Figure D-5. 81-mm Mortar Emplacement & Displacement

The data for the HD group are normally distributed as evidenced by the Shapiro-Wilk 

Test that resulted in a p-value of 0.26 but not normally distributed for the C group, which 

had a p-value of <0.01. We proceed with presenting ANOVA results because they are 

confirmed by a Mann-Whitney Test with a p-value of 0.87.

The C group had a mean time of 2.56 minutes. This time is slower (but not statistically 

significant) than the HD mean time of 2.51 minutes. This difference results in a 2.10%, 

or 0.05-minute, improvement in movement time between the groups. See Table D-2

and Table D-3 for detailed analytical results.

D.5.2.5.2 81-mm Mortar Emplacement & Displacement Contextual Comments

A mortar squad must be able to move and deliver supporting fires as rapidly as possible 

on the battlefield. On average, the HD groups were 3 seconds faster than the C group. 

However, because this difference is so small and did not meet the statistical 

significance threshold, it can be assumed the C and HD groups performed the same.

D.5.2.5.3 81-mm Mortar Emplacement & Displacement Additional Insights

One source of masking occurred during this task that was not anticipated during the 

design. The initial movement portion of this task (a physical-based capacity) was 

masked by the time it took to assemble the mortar and sight in on the target (a skillbased capacity). For instance, it was observed that, when slower members of the 

squad fell back during the initial movement, their delay was masked (not captured) by 

the fact that the rest of the team began emplacing the 81-mm mortar system 
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concurrently. By the time the weapon system was FIRECAP, all members had arrived 

at the MFP. Therefore, a squad that moved quickly versus a squad that got spread out 

was diffused by the time it took to sight in on the target. If the movement had been 

longer than 100m, then, based on the results of other similar movement tasks, one 

could conclude the results of this task would have been different.

D.5.2.5.4 81-mm Mortar Emplacement & Displacement Subjective Comments

For subjective comments relating to this task, see the Appendix. 

D.5.2.6 1-km Hike

D.5.2.6.1 1-km Hike Overview

This experimental task assessed a mortar team moving approximately 1 km to reinforce 

a notional friendly rifle squad pinned down by enemy fire. While conducting this 

movement, the team carried an assault load with 12 mortar rounds, individual weapons 

(M4), and two 60-mm mortar tubes. The time started when the squad departed the 

assembly area on Range107 and ended upon reaching a designated location in the 

down-range area.

Figure D-6 displays all 0341 1-km hike time data. All data on the scatter plot are valid 

for analysis.

Figure D-6. 1-km Hike
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The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.54 for the C group and 0.09 for the HD group.

The C group had a mean time of 9.51 minutes. This time is statistically significantly 

faster than the HD mean time of 10.89 minutes. This difference results in a14.49%, or

1.48-minute, degradation in time between the groups. See Table D-2 and Table D-3 for 

detailed analytical results.

D.5.2.6.2 1-km Hike Contextual Comments

The Infantry T&R Manual states, “the maximum assault load weight will be such that an 

average infantry Marine will be able to conduct combat operations indefinitely with 

minimal degradation in combat effectiveness.” While moving 1 km with the assault load, 

the HD group took 1.38 minutes longer, a degradation of 14.49%. On any given day 

(under the same environmental conditions), the C group was faster than the HD group 

90.5% of the time (19 of 21 trials).

D.5.2.6.3 1-km Hike Additional Insights

A purely objective evaluation of an 83-second delay is elusive but may possess some 

practical significance when considering a unit in contact. Consider an enemy 82-mm 

mortar system outside the range of friendly direct fire weapons (1800 m for .50 cal). In 

lieu of an 82-mm mortar firing table, an 81-mm mortar firing table reveals the maximum

range on charge 1 is 1920 meters with a TOF of 20 seconds. Each enemy mortar tube 

would have the time to fire 3-4 mortar rounds prior to the integrated group being fire 

capable. The resultant trade in casualty exchange could be significant.

D.5.2.6.4 1-km Hike Subjective Comments

For subjective comments relating to this task, see the Appendix. 

D.6 Statistical Modeling Results 

D.6.1 Statistical Modeling Overview

The previous section discussed results only as they pertain to differences due to 

integration level alone. The goal of statistical modeling, as applied here, is to estimate, 

simultaneously, the effect of gender-integration levels and other relevant variables on 

squad performance. Refer to the Methodology Annex for a broad overview of the 

analysis plan and the variables used in the models. 

For the same six selected tasks described in the previous section, this section presents 

an overview of the analysis and results and then presents the modeling results for each 

of the tasks.

For each task, we describe the significant variables in the model and whether these 

variables are either positively or negatively correlated with the result. A negative 
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correlation indicates an increase in that variable will result in a decrease in the response 

variable, which is a desired outcome for elapsed time. The results indicate where 

certain patch numbers are significant for a given variable.

The experiment tracked Marines within the squad by a patch number that associated 

their random position within the team/squad to a specific billet. Table D-4 displays the 

0341 patch numbers and billet titles. The billet titles for the mortar team/squad 

depended on the day of the trial cycle (day 1 offensive tasks versus day 2 defensive 

tasks). The 60-mm mortar team had two mortar tubes for the engagement. Therefore, 

Patch 1 and Patch 3 were the gunners for this task.

Table D-4. 0341 Patch Numbers and Billet Titles

Patch Number Billet Title Day 1 Billet Title Day 2

1 Gunner Gunner

2 Assistant Gunner Assistant Gunner

3 Gunner Ammunition Man 1

4 Assistant Gunner Ammunition Man 2

D.6.2 0341 Selected Tasks Method of Analysis

Due to the small number of trials, a mixed-effects model with all mortar team/squad

members and all types of personnel data does not work for the 0341 data set. Thus, we 

model each personnel variable with integration level separately with a random effect for

who filled each position within the mortar team/squad. For example, age for each 

member of the mortar team/squad (four variables), a random effect for who filled each 

billet, and integration level are modeled with the result (response time) as the response 

variable. Where maximum likelihood estimation converged, AIC was used for variable 

selection. Otherwise, we comment on the significance of individual variables in the full 

model. Variables reported as significant are concluded to be significant based on at 

least a one-sided test.

D.6.3 0341 Selected Tasks Overall Modeling Results

The displace to LOA task is the only task for which a personnel variable is significant for 

all members of the mortar team where height is statistically significant for all members 

of the mortar team and is negatively correlated with the response.

Integration level is significant for the 7-km hike, 60-mm mortar engagement time, and 

the 1-km hike. For each of these tasks, modeling the random effects for the individuals 

participating in the task results in changes from the initial results in the descriptive 

statistics. Each respective task paragraph describes these changes.
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The CASEVAC and 81-mm mortar emplacement and displacement tasks did not have a 

final model with any significant variables. Refer to Section D.5.2.4 and Section D.5.2.5, 

respectively, for these tasks’ ANOVA results.

D.6.3.1 7-km Hike

We model elapsed time for the 7-km hike as a function of each personnel variable and 

integration level in a separate mixed model. The covariates in each model are the 

values of each personnel variable for each patch number, integration level, and a 

random effect of who filled each position in the squad. For each model, we report 

statistically significant positive and negative correlations and whether we observe any 

patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• All. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the 7-km hike time:

• CFT MTC of patch 4 

• PFT 3-mile run of patch 4.

The following personnel variables are significant in their respective models and are 

negatively correlated with the 7-km hike time:

• Height of patches 1, 2, and 3

• Weight of patches 1, 2, and 3

• AFQT score of patches 2 and 4

• GT score of patch 2 

• PFT crunches of patch 3 

• Rifle score of patch 4. 
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The following personnel variables have no significant variables in their respective 

models:

• None.

Because the effects of the personnel variables do not have any patters and their effects 

are often negligible, the final model includes integration level only where HD has a 

difference of 16.42 minutes when compared to a C group and a p-value of <0.01. This 

difference is a decrease from the 18.97-minute difference identified in the descriptive 

statistics, which is a 13.44% change.

D.6.3.2 60-mm Mortar Engagement

We model elapsed time for the 60-mm mortar engagement as a function of each 

personnel variable and integration level in a separate mixed model. The covariates in 

each model are the values of each personnel variable for each patch number, 

integration level, and a random effect of who filled each position in the team. For each 

model, we report statistically significant positive and negative correlations and whether 

we observe any patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Squad leader

• Age

• AFQT score

• GT score

• CFT MTC

• PFT crunches

• PFT 3-mile run

• Rifle score. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the 60-mm mortar engagement time:

• CFT MTC for patches 2 and 4. 
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The following personnel variables are significant in their respective models and are 

negatively correlated with the 60-mm mortar engagement time:

• Height of patches 1 and 3

• Weight of patches 1, 3, and 4. 

The following personnel variables have no significant variables in their respective 

models:

• None.

Because the effects of the personnel variables do not have any patterns and the effects 

are often negligible, the final model includes integration level only where HD has a 

difference of 0.45 minutes when compared to a C group and a p-value of <0.01. This 

difference is a decrease from the 0.49-minute difference identified in the descriptive 

statistics, which is an 8.16% change

D.6.3.3 Displace to LOA

We model elapsed time for the displacement to LOA as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and 

a random effect of who filled each position in the team. For each model, we report 

statistically significant positive and negative correlations and whether we observe any 

patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Squad leader

• Age

• AFQT score

• GT score

• CFT MTC

• CFT MANUF

• PFT crunches

• PFT 3-mile run

• Rifle score. 
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The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the displacement to LOA time:

• PFT 3-mile run of patch 3. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the displace to LOA time:

• Height of patches 1, 2, 3, and 4

• Weight of patches 2, 3, and 4

• GT score of patch 3 

• PFT crunches of patch 3. 

The following personnel variables have no significant variables in their respective 

models:

• None.

The final model includes the height of the mortar team. AIC does not select integration 

level in this model. Each of the variables is statistically significant and negatively 

correlated with the displacement to the LOA time. There are no strong correlations 

between the integration level and height for the mortar participants (less than 0.33). 

Table D-5 displays the variables and their respective estimates and standard errors. 

This result implies that, as a Marine’s height increases, the displacement to the LOA 

time will decrease.

Table D-5. Coefficients and Standard Errors for the Final Displace to LOA Model

Effect Estimate Std. Error

Height patch 1 -0.04 0.02

Height patch 2 -0.05 0.02

Height patch 3 -0.04 0.02

Height patch 4 -0.04 0.01

D.6.3.4 CASEVAC

We model elapsed time for the CASEVAC as a function of each personnel variable and 

integration level in a separate mixed model. The covariates in each model are the 

values of each personnel variable for each patch number, integration level, and a 

random effect of who filled each position in the team. For each model, we report 

statistically significant positive and negative correlations and whether we observe any 

patterns.
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The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Squad leader. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the CASEVAC time:

• None.

The following personnel variables are significant in their respective models and are 

negatively correlated with the CASEVAC time:

• Age of patch 3 

• Height of patch 1 

• Weight of patch 1 

• GT score of patches 3 and 4

• PFT crunches of patch 3. 

The following personnel variables have no significant variables in their respective 

models:

• AFQT score

• CFT MTC

• CFT MANUF

• PFT 3-mile run

• Rifle score. 

Because integration level is not significant in the final model and there are no variables 

that are significant for the whole team, there is no final mixed-effects model for this task. 

Refer to the Section D.5.2.4 to see the ANOVA results for this task. 

D.6.3.5 81-mm Mortar Emplacement and Displacement

We model elapsed time for the 81-mm mortar emplacement and displacement as a 

function of each personnel variable and integration level in a separate mixed model. 
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The covariates in each model are the values of each personnel variable for each patch 

number, integration level, and a random effect of who filled each position in the squad. 

For each model, we report statistically significant positive and negative correlations and 

whether we observe any patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• None.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the 81-mm mortar emplacement and displacement time:

• Squad leader

• CFT MTC of patch 2 

• CFT MANUF time of patch 2. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the 81-mm mortar emplacement and displacement time:

• Height of patch 2

• AFQT score of patch 2 

• GT score of patch 2 

• PFT crunches of patch 3 

• Rifle score of patch 2. 

The following personnel variables have no significant variables in their respective 

models:

• Age

• Weight

• PFT 3-mile run. 

Because integration level is not significant in the final model and there are no variables 

that are significant for the whole squad, there is no final mixed-effects model for this 

task. Refer to Section D.5.2.5 to see the ANOVA results for this task. 
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D.6.3.6 1-km Hike

We model elapsed time for the 1-km hike as a function of each personnel variable and 

integration level in a separate mixed model. The covariates in each model are the 

values of each personnel variable for each patch number, integration level, and a 

random effect of who filled each position on the team. For each model, we report 

statistically significant positive and negative correlations and whether we observe any 

patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• All. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the 1-km hike time:

• CFT MTC of patch 2 

• PFT crunches of patch 1 

• PFT 3-mile run of patch 4. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the 1-km hike time:

• Height of patches 1, 2, and 3

• Weight of patch 3 

• PFT crunches of patch 3. 

The following personnel variables have no significant variables in their respective 

models:

• None.

Because the effects of the personnel variables do not have any patters and their effects 

are often negligible, the final model includes integration level only where HD has a 

difference of 1.19 minutes when compared to a C group and a p-value of <0.01. This 

difference is a decrease from the 1.48-minute difference identified in the descriptive 

statistics, which is a 19.59% change.
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Appendix to Annex D 

0341 Supplemental Information

This appendix provides supplemental information for the 0341 portion of the GCEITF

experiment. It provides information regarding the GCEITF leadership subjective 

comments and additional descriptive and basic inferential statistics not described in 

Annex D. 

Section 1. GCEITF Leadership Subjective Comments

The GCEITF leadership provided comments on their observations of the experiment 

throughout it execution. Table D A displays a summary of these comments broken 

down by task, integration level, gender, and type of comment.
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Table D A – Summary of GCEITF Leadership Comments

Section 2. Additional Task Basic and Inferential Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. The experiment included a number of tasks and associated metrics 

conducted to enhance operational realism and maintain consistent application of the 

experimental process. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

This section presents results for 11 additional 0341 tasks. Annex D contains the 

Task and Metric 

Description Gender Total

C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total

M 21 4 25 5 0 5 2 0 2 0 1 1 0 1 1 0 0 0 0 0 0 0 0 0 34

F 0 41 41 0 13 13 0 0 0 0 0 0 0 0 0 0 6 6 0 0 0 0 1 1 61

Unit 3 0 3 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 1 1 7

M 4 3 7 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8

F 0 33 33 0 0 0 0 2 2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 36

Unit 1 0 1 0 0 0 1 1 2 1 1 2 0 0 0 0 0 0 0 0 0 0 0 0 5

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 1 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2

F 0 2 2 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 6

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 1 1 0 0 0 0 0 0 17 16 33 0 0 0 0 0 0 0 0 0 1 0 1 35

F 0 9 9 0 2 2 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 13

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 2 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

F 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Unit 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

M 1 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2

F 0 9 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 10

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

60-mm Mortar Engagement

Falling 

behind/slowing 

movement

Requesting extra 

breaks

Requires extra 

assistance Other No category

7-km Hike

Needs no 

assistance

Compensating 

for another 

Marine

Gear pass off

1-km Hike

Fire & Movement to MFP; 

Movement to MFP #1

Fire & Movement to MFP; 

First Three Rounds

Fire & Movement to MFP; 

Movement to MFP #2

Fire & Movement to MFP; 

Second Three Rounds

Displace to LOA

CASEVAC to CCP

81-mm Mortar Emplacement 

& Displacement
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descriptive statistics for the remainder of the 0341 tasks. The words “metric” and “task” 

are used interchangeably throughout this Appendix; they both refer to the experimental 

task. 

The two tables below display the results for 11 additional 0341 metrics. Table D B

displays the metrics and integration levels with their respective sample sizes, means, 

standard deviations, and percent differences between integration levels.

Table D C displays ANOVA results, including metrics and integration levels, and pvalues suggesting statistical significance. For each task, an ANOVA and t-test were 

conducted to compare the two groups. If p-values are less than the a-priori determined 

significance level of 0.10, we conclude that there is statistical evidence that the 

response for the HD group is different from that in the C group. We present basic 

inferential statistics for four tasks. 

Table D B – 0341 Test Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD % Difference 

(HD-C)

7-km Hike; first km 

(minutes)*

C 20 10.66 0.59 7.40% HD 21 11.44 0.66

7-km Hike; second 

km (minutes)*

C 20 11.05 0.62 10.94%

HD 21 12.26 0.95

7-km Hike; third km 

(minutes)*

C 20 11.20 1.61 32.43% HD 21 14.83 3.13

7-km Hike; fourth 

km (minutes)*

C 20 12.52 2.33 18.54%

HD 22 14.84 2.86

7-km Hike; fifth km 

(minutes)*

C 20 13.88 2.75 32.56% HD 21 18.40 2.86

7-km Hike; sixth km 

(minutes)*

C 20 14.14 1.29 21.44% HD 22 17.17 2.58

7-km Hike; seventh 

km (minutes)*

C 20 15.28 2.11

19.51%

HD 22 18.27 3.56

60-mm Mortar 

Engagement; 

Movement to MFP 

#1 (seconds)*

C 65 49.66 10.76

35.92%

HD 32 67.50 19.22

60-mm Mortar 

Engagement; First 

Three Rounds 

(seconds)

C 19 36.91 5.09

-0.12%

HD 20 36.86 4.83

60-mm Mortar 

Engagement; 

Movement to MFP 

#2 (minutes)*

C 65 1.24 0.28

27.34%

HD 32 1.58 0.39

60-mm Mortar 

Engagement; 

Second Three 

C 19 32.50 4.65

15.77% HD 22 37.62 5.80
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Metric Integration 

Level

Sample 

Size Mean SD % Difference 

(HD-C)

Rounds (seconds)*

Table D C – 0341 ANOVA Results and Welch’s T-Test Results

Metric

F 

statistic 

(df) 

F Test

PvalueComparison 2-sided 

P-Value 

1-sided 

P-Value 

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

60-mm Mortar 

Engagement; 

Movement to 

MFP #1 

(seconds)*

34.38

(1, 95) < 0.01* HD-C < 0.01† < 0.01† 0.25† 0.42† 0.22† 0.43†

60-mm Mortar 

Engagement; 

First Three 

Rounds 

(seconds)

0.00

(1, 37) 0.98 HD-C 0.98 0.49 -2.12 2.03 -2.73 2.64

60-mm Mortar 

Engagement; 

Movement to 

MFP #2 

(minutes)*

24.21

(1, 95) < 0.01* HD-C < 0.01† < 0.01† 0.28† 0.45† 0.25† 0.48†

60-mm Mortar 

Engagement; 

Second Three 

Rounds 

(seconds)*

9.54

(1, 39) < 0.01* HD-C < 0.01* < 0.01* 3.00 7.25 2.37 7.88

*Indicates there is a statistically significant difference, in either a one-sided or two-sided 

hypothesis test, between integration levels according to ANOVA.

†Results presented are from a Mann-Whitney non-parametric test due to non-normality.

Additional Task Results: 

7-km Hike by km. The general trend for the 7-km hike was that the difference between 

the HD and C groups increased over the course of the hike.

60-mm Mortar Engagement; Movement to MFP #1. The data for the HD group are 

normally distributed, as evidenced by the Shapiro-Wilk Test that resulted in a p-value of 

0.03 but not normally distributed for the C group, which had a p-value of <0.01. We 

proceed with presenting ANOVA results because they were confirmed by a MannWhitney Test with a two-sided p-value of <0.01.

The C group had a mean of 49.66 seconds. This time is statistically significantly faster 

than the HD mean of 67.50 seconds. The HD group was 35.92% slower than the C 

group.

• Contextual Comments. For references regarding the importance of speed, see 

Annex D. The C group squads were able to get in position to bring their weapon 

system into action 18 seconds faster than the HD squads, on average. This

difference could be a significant advantage in a combat engagement.
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60-mm Mortar Engagement; First Three Rounds. The data are normally distributed, 

as evidenced by the Shapiro-Wilk Test that resulted in a p-value of 0.21 for the C group 

and 0.90 for the HD group.

The C group had a mean of 36.91 seconds. This time is slower (but not statistically 

significant) than the HD group mean of 36.86 seconds. The HD group was 0.12% faster

than the C group. 

• Contextual Comments. This event did not elicit a particular difference in the 

squad types. However, this is not a particularly physically demanding event by 

itself.

60-mm Mortar Engagement; Movement to MFP #2. The data for the HD group are 

normally distributed, as evidenced by the Shapiro-Wilk Test that resulted in a p-value of 

0.55 but not normally distributed for the C group, which had a p-value of <0.01. We 

proceed with presenting ANOVA results because they were confirmed by a MannWhitney Test with a two-sided p-value of <0.01.

The C group had a mean of 1.24 minutes. This time is statistically significantly faster 

than the HD group mean of 1.58 minutes. The HD group was 27.34% slower than the C 

group. 

• Contextual Comments. The importance of speed has been iterated several 

times before. The C group squads were able to get in position to bring their 

weapon system into action 20 seconds faster than the HD squads, on average. 

When considered in combination with the 18-second advantage already gained 

in the movement to MFP #1 event, the advantage for a combat engagement is 

even more significant.

60-mm Mortar Engagement; Second Three Rounds. The data are normally 

distributed, as evidenced by the Shapiro-Wilk Test that resulted in a p-value of 0.65 for 

the C group and 0.88 for the HD group.

The C group had a mean of 32.50 seconds. This time is statistically significantly faster 

than the HD group mean of 37.62 seconds. The HD group was 15.77% slower than the 

C group.

• Contextual Comments. This is essentially the same event as the “First Three 

Rounds” portion of the test already described. With that in mind, it is not clear 

why there is a significant difference between the squad types for this event when 

such a difference is absent in the first one. The HD groups were, on average, 

slightly slower than the first event (just under a second), while the C groups were 

over four seconds faster on average. The observer’s comments do not show any 

particular reason this difference occurred. Without amplifying information as to a 

cause for this difference, it can still be reiterated that faster is better.
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Annex E. 

Infantry Assaultman (MOS 0351) and Infantry Anti-tank Missileman (MOS 0352) 

This annex details the Infantry Assaultman (MOS 0351) and Infantry Anti-tank 

Missileman (MOS 0352) combined portion of the Ground Combat Element Integrated 

Task Force (GCEITF) experiment executed from 2 March to 26 April 2015 at Range 107 

and Range 110, aboard the Marine Corps Air Ground Combat Center (MCAGCC), 

Twentynine Palms, CA. The combined 0351 and 0352 assessment is referred to in this 

annex as the 035X assessment. The sections outline the Infantry 035X scheme of 

maneuver (SOM), limitations, deviations, data set description, descriptive and basic 

inferential statistics, and modeling results. 

E.1 Scheme of Maneuver

E.1.1 Experimental Cycle Overview

The Infantry Assaultman (0351) and Anti-tank Missileman (0352), or MOS 035X, 

assessment of the GCEITF took place in a field environment aboard MCAGCC, 

Twentynine Palms, CA. The assessment consisted of 21 trial cycles, each of which was 

a 2-day test cycle, conducted over the course of 55 days. After every 4 days of trials, 

the Marines spent 1 recovery day at Camp Wilson. The 0351 and 0352 MOSs were 

combined for the assessment to maximize the participation of every Marine and 

generate a larger sample. The experimental unit was composed of a pair of two-person 

Assault Teams making an assault squad or an anti-armor squad. Each squad consisted 

of four volunteers and one direct-assignment (non-volunteer) squad leader. Each 

member was trained to fill each billet within the team/squad: gunner and assistant 

gunner. The assessment was executed under the supervision of MCOTEA functional 

test managers and a range Officer in Charge (OIC)/Range Safety Officer (RSO) from 

the GCEITF. 

E.1.2 Experimental Details

The 2-day 035X assessment replicated offensive and defensive tasks. The 035X MOS 

began each cycle on Day 1/Offensive tasks and concluded with Day 2/Defensive tasks. 

Two 035X squads executed each trial cycle: a control (C) nonintegrated squad and a 

high-density (HD) integrated squad with two, three, or four females. 

Day 1 of the trial cycle was executed on Range 107 and consisted of supporting a 

squad attack as an assault squad employing the shoulder-launched, multipurpose 

assault weapon (SMAW). Each assault squad moved approximately 1 km to an assault 

position (AP) wearing an assault load and carrying a personal weapon (M-4), two 

SMAW launchers, and four rockets. The squad moved all personnel and gear over an 8-
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ft obstacle/wall. After negotiating the obstacle, the squad staged its assault packs and 

followed-in-trace of a rifle squad conducting a live-fire assault. During the counterattack, 

the assault squad moved from a cold position to a hot position and engaged two enemy 

armored vehicles with the SMAW. Then, the assault squad conducted a 100-m casualty 

evacuation (CASEVAC) of a 220-lb dummy.

Day 2 of the trial cycle was executed on Range 110 and consisted of defensive actions. 

The squad started the day with a 7-km forced march from Range 107 to Range 110 

wearing an approach load and carrying a personal weapon, two SMAW launchers, and 

four rockets. After arriving at Range 110, the squad then had to mount and dismount the 

M-41 Saber system to a High-Mobility Multipurpose Wheeled Vehicle (HMMWV). Each 

squad then carried four tube-launched, optically tracked, wire-guided (TOW) missiles to 

a firing line where two Saber systems were already assembled and calibrated. Finally, 

the two gunners engaged two designated targets as varying distances. At the 

conclusion of Day 2, the Marines were reorganized into new squads for the next 

experimental cycle.

E.1.3 Additional Context

Throughout the assessment, Marines bivouacked at Range 107, sleeping in two-man 

tents. During trial execution, Marines wore/carried prescribed loads for each task. 

Weighing packs each day prior to the 7-km forced march ensured consistency. After 

each trial day, the Marines operated under company leadership, performing minimal 

physically demanding tasks. The Marines who were not part of an assessed squad 

conducted the same experimental subtasks after the assessed squads to ensure equity 

between individuals participating in a trial cycle and those not chosen for that particular 

cycle. These tasks will be discussed in detail in the loading section that follows. 

Fatigue surveys were designed to capture the volunteers’ cumulative fatigue level at the 

beginning and end of each day’s trials. The data collected provide additional insight into 

apparent aberrations in the performance level of a given volunteer on a specific day. It 

allows outside fatigue-related factors (minor illness, lack of sleep the night before, etc.) 

to be accounted for in the analysis of the performance data. Workload surveys collected 

the volunteers’ perceived average and maximal levels of exertion during the 

performance specified tasks. Cohesion surveys provided a method of collecting 

subjective data relating to each squad’s ability to work as a team and its overall 

perspective on the cohesiveness of the squad.

E.1.4 Experimental Tasks

E.1.4.1 1-km Movement 

Assaulting an enemy position never starts from a static position; first, a movement must 

be conducted to the AP. The distance from the line of departure to the AP depends on 

myriad factors. Based on time and space constraints, this distance was set at just under 
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1 km for the experimental event. Each 035X squad moved this distance as quickly as 

possible while carrying an assault load in addition to two SMAW launchers and four 

rockets divided among the four members. 

E.1.4.2 Negotiate an Obstacle

The conduct of an attack often involves reducing or negotiating an obstacle. It is 

common in an urban environment to make entry through a window or over a wall 

(obstacle). One of the more difficult tasks is climbing over a wall with a fighting load. 

Each squad negotiated an 8-ft wall by getting all four Marines and their equipment over 

as quickly as possible. 

E.1.4.3 SMAW Engagement 

An assault squad often accompanies a rifle squad into an attack. The assault squad 

provides anti-armor fires to destroy fortifications or other designated targets. When 

employing the SMAW, the squad generally prepares its rockets from a position of cover, 

commonly referred to as a cold position. Then it moves to an exposed position with a 

good line of sight to the enemy, commonly referred to as a hot position. During the 

experiment, the SMAW squad followed-in-trace of the rifle squad to a cold position 

where the gunners prepared a rocket for employment. The Marines then moved 

approximately 50 m to a hot position where they engaged an armored vehicle, 

conducted a rapid reload, engaged a second armored vehicle, and displaced back to 

the cold position. This task required Marines to move rapidly under a load and 

accurately engage targets while fatigued. This task determined the time and accuracy of 

employment. 

E.1.4.4 CASEVAC

Casualties are an inevitable part of conducting combat operations. Units train to 

become proficient in triaging, handling, and transporting casualties. When a casualty is 

sustained, it is essential to move with a sense of urgency to get the injured Marine to 

the appropriate level of care. Each 035X squad moved a 220-lb dummy 100 m from a 

position of cover to a casualty collection point (CCP) while also transporting their 

assault packs and two SMAW launchers. The 035X squads could use a variety of 

techniques for transport but had to carry the dummy off the ground. This task 

determined the squad’s proficiency in moving a simulated casualty to a CCP. After the 

CASEVAC, each Marine took a fatigue and workload survey to assess overall fatigue 

and workload of the entire offensive task (see GCEITF Experimental Assessment Plan 

[EAP], Annex D).

E.1.4.5 7-km Hike

Infantry units must move through all sorts of terrain on foot. Units train by conducting a 

forced march with an approach load at a sustained rate of march. For the assessment, 
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each 035X squad moved a distance of 7.20 km as quickly as possible while carrying an 

approach load, two SMAW launchers, and four rockets spread-loaded across all four

members. This route was flat (minimal elevation change) and featured an unimproved 

surface with varying degrees of conditions (compact dirt and loose sand). The squads 

moved as fast as the slowest person. This task determined the squad’s rate of 

movement over a 7.20-km route carrying the approach load and the crew-served 

weapon. Each Marine took a fatigue and workload survey after completion of the 7.20-

km hike (see GCEITF EAP, Annex D).

E.1.4.6 Mount/Dismount Drill

The TOW missile is generally employed from a mounted platform, such as a HMMWV. 

Members of an anti-armor squad must mount and dismount the Saber system to a 

HMMWV. During the assessment, the anti-armor squad mounted a Saber system onto 

a HMMWV. A squad leader verified that Marines had properly mounted the Saber 

system, and then the squad dismounted the system. Marines did not conduct the 

calibration process due to its technical and timely procedures. This task was selected 

for the physical strength required to lift, curl, and press the Saber components up and 

lower them down by members of the squad. This task determined the time it took to 

mount and dismount the Saber system. 

E.1.4.7 TOW Engagement

The TOW missile is a heavy anti-armor weapon that may be employed from a tripod to 

provide defensive fires. During the assessment, a precalibrated Saber system was 

mounted on a tripod at a designated firing position. Each anti-armor squad moved four 

TOW missiles to the firing line and engaged two designated targets, firing each missile 

in sequence. This task was chosen for the strength required to move each missile and 

the ability to employ the TOW while fatigued. This task determined the time to move the 

TOW missile to the firing line and gunner accuracy. At the conclusion of the TOW 

engagement, each Marine took a fatigue and workload survey to assess his or her 

fatigue and workload during the execution of the mount/dismount drill and engagement 

task (see GCEITF EAP, Annex D). 

At the completion of the 2-day cycle, Marines took a cohesion survey to record their 

cohesion during the execution of the 2-day trial cycle (see GCEITF EAP, Annex M). 

E.1.5 Loading Plan

The loading plan ensured, to the greatest extent possible, equity of physical activity 

among all volunteers throughout the duration of the experimental assessment. Every 

trial and task was conducted in the same manner and sequence to ensure consistency. 

Due to the number of volunteers, a handful of Marines were not part of an assessed 

squad for each 2-day cycle. Collaboration with company leadership determined that the 

best method of loading nonassessed Marines was to form them into a separate squad 
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and have them perform the same tasks as an assessed squad to experience the same 

conditions and physical strain. Minor modifications were permitted due to the reduced 

size of the squad. 

E.1.6 Scheme of Maneuver Summary

The 035X experiment consisted of a 2-day trial cycle composed of an offensive and 

defensive day. The offensive day involved four subtasks based on supporting a squad 

attack: 1-km movement, negotiating an obstacle, SMAW engagement, and CASEVAC. 

The defensive day involved three subtasks: a 7.20-km forced march, mount/dismount 

drill, and TOW engagement. During the course of the experiment, the 0351 and 0352 

squads executed 2 pilot trial cycles and 21 record trial cycles. During trial execution, 

Marines rotated through every billet within the assault/anti-armor squad, carrying 

components of the crew-served load.

E.2 Limitations 

E.2.1 Limitations Overview

The GCEITF experiment was designed to allow operationally relevant tasks to occur as 

naturally as possible, while gathering unbiased measurements. Most tasks were 

performed in a manner similar to those in an operational environment. Under certain 

situations, artificial limitations or interruptions were introduced that changed or altered 

the way a task would normally be performed. While these limitations represent a degree 

of artificiality, they do not detract significantly from our abilities to generalize the 

conclusions of this experiment to the performance of Marines in a field environment. 

The following limitations were observed for 035X assessment. 

E.2.2 Relative Difficulty of Record Test

The 035X GCEITF assessment was designed to gather data associated with some of 

the most physically demanding tasks within the 035X MOSs. These tasks in isolation do 

not fully replicate life experienced by a Marine during a typical field exercise (FEX) or a

combat environment and did not obtain the maximum cumulative load that could be 

placed on an Infantry Marine. With limited time available, only selected 035X tasks were 

assessed. Other tasks/duties outside the assessment were minimized due to specific 

experimental constraints and human factors. During a typical FEX, it is common for 

Marines to conduct 24-hour operations that include daytime and nighttime 

operations/patrols, standing firewatch or a security post, and conducting continuing 

tactical actions. The offensive day SOM took squads approximately 1 hour to complete, 

and the defensive day SOM took approximately 3 hours to complete. Outside the 

assessed trials, there were minimal tasks required of the volunteers that demanded any 

degree of physical strain. 

Another primary concern in designing the 035X assessment was to ensure that it was 

achievable and sustainable for a 60-day period. The 7-km forced march distance was 
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selected based on the amount of training time available prior to the assessment. 

However, many of the loads carried were decreased. For instance, the crew-served 

load was altered from the Javelin Missile Simulator Rounds and Command Launch Unit 

for the Day 2 (defensive SOM) to the SMAW and dummy rockets. Additionally, the 

Marines were authorized 1 day off after every 4 days of training. This artificial recovery 

period is not achievable when conducting training or combat operations.

A final factor affecting the relative difficulty of the record test pertains to the intangible 

physiological impact of the volunteers’ ability to drop on request (DOR) at any point

during a trial. Any time a volunteer dropped during a trial cycle, that squad/team 

performed the following subtasks with fewer personnel. This factor could have affected 

the cohesion of each squad and could have influenced its performance. 

E.2.3 Artificial Emplacement 

Artificialities were introduced for a 60-day period. On Day 2 of the 035X experiment, the 

assault/anti-armor Marines engaged targets with the TOW system. Once the 7-km 

forced march was completed with the SMAW crew-served weapon system, the Marines 

arrived at a range with a TOW system already emplaced in a static firing position. The 

Marines engaged two targets per weapon system for each weapon system. Once 

Marines fired the four missiles, the trial was complete, and the TOW system remained

on the firing line.

E.2.4 Number of Volunteer Participants

For the 035X experiment, 6 male and 6 female volunteers began the experiment, but 

only 5 males and 4 females completed the assessment. The results presented in this 

annex are based on the performance of 9 to 12 Marines. 

E.2.5 Limitations Summary

The 035X assessment was designed to replicate realistic training in a field environment. 

The end state was to create an experiment in which the volunteers felt they were 

conducting realistic and operationally relevant tasks. Certain unavoidable limitations to 

the assessed tasks and non-assessed operating environment introduced a level of 

artificiality that would not normally have been present in a field training or combat 

environment. 

E.3 Deviations 

E.3.1 Integration Level of the Squad

The EAP stated that the 035X MOS would have three levels of integration: C, lowdensity (LD) (one female), and HD (two females). Prior to the beginning of the first 

record trial cycle, the population could no longer support an LD group. Initially, there 

were two females in the HD squad. Due to the number of DORs, however, the number 

of females in the squad changed based on the availability of male and female Marines. 
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For the majority of trial cycles, there was an all-male squad and an all-female squad. 

However, due to injuries, there were some occasions when an HD squad consisted of 

three female Marines.

E.4 Data Set Description 

E.4.1 Data Set Overview

The 035X portion of the experiment consisted of 2 pilot trial cycles and 21 record trial

cycles. The pilot trial cycles were conducted from 2 to 6 March 2015. Pilot trial cycle

data are not used in analysis due to variations in the conduct of the experiment. We 

based all analysis on the 21 record trial cycles executed from 7 March to 26 April 2015.

E.4.2 Record Test Volunteer Participants

At the beginning of the first record trial cycle, there were six male 035X volunteers and 

six female volunteers. Several Marines voluntarily withdrew, or were involuntarily 

withdrawn, during the execution of the experiment. The final number of volunteers was 

five males and four females.

E.4.3 Planned, Executed, and Analyzed Trial Cycles

Table E-1 displays number of trial cycles planned, executed, and analyzed by task. The 

planned number of trial cycles for the 035X MOS per Section 7.5.3 of GCEITF EAP is 

120 trial cycles, or 40 trial cycles per planned integration level (C, LD, and HD). The 

original plan called for six squads per day (two per integration level) over the 20 trial 

cycles. However, due to the number of Marines who voluntarily withdrew or were 

involuntarily withdrawn from the experiment prior to the execution of the first record trial 

cycle, only one squad of the C and HD integration levels remained. We chose to keep 

the HD integration level to employ more Marines in the experiment.

While the number of male and female volunteers did not support the ability to execute 

another C group during a trial cycle, there were times when another HD group could 

execute additional whole or partial trials. A partial trial was a trial in which a two-Marine 

unit could execute the tasks where data were collected at the two-Marine unit level. The 

planned number of trials in Table E-1 reflects 21 planned trial cycles for each integration 

level and accounts for the extra trials the HD integration level completed.

There are several occurrences of missing data for the 7-km hike by individual kilometer. 

The individual kilometer times were derived from GPS data. Early in the experiment, the 

Garmin GPSs were set to record a volunteer’s position every second. Due to the 

storage space on the GPS and length of the trial, when volunteers executed the 7-km 

hike and then their follow-on tasks, the GPS could not hold all the data. Therefore, it 

overwrote the hike data. Once the problem was found, the GPSs were corrected to 

record location every 2 seconds. 
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Table E-1. 035X Planned, Executed, and Analyzed Trial Cycles1

Task and 

Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

Trials 

Conducted 

Number of 

Trials Used in 

Analysis

Notes

7-km Hike

C 21 21 21

HD 21 22 21 Run 1 on Mar 8 disregarded due to 

TIR

SMAW 

Engagement by 

Time

C 21 21 20 Remove Apr 6 due to TIR

HD 21 24 24

SMAW 

Engagement 

Accuracy

C 21 21 20 Remove Apr 6 due to TIR

HD 21 24 24

Negotiate 

Obstacle

C 21 21 21

HD 21 22 22

CASEVAC C 21 21 21

HD 21 22 20 Remove Mar 7 and Mar 17 due to TIR

Mount/Dismount 

Saber

C 21 21 19 Remove Apr 2 and Apr 12 due to TIR

HD 21 22 20 Remove Apr 2 and Apr 12 due to TIR

TOW 

Engagement

C 21 21 19 Remove Mar 18 and Apr 4 due to 

hangfire

HD 21 24 23 Remove Mar 20 due to hangfire

1-km Hike C 21 21 21

HD 21 22 22

7-km Hike; 

1-km Time

C 21 21 19 No data: Mar 8, Mar 18.

HD 21 22 16 No data: run1 Mar 8, run 2 Mar 8, Mar 

10, Mar 13, Mar 15, Mar 18.

7-km Hike; 

2-km Time

C 21 21 19 No data: Mar 8, Mar 18.

HD 21 22 16 No data: run1 Mar 8, run 2 Mar 8, Mar 

10, Mar 13, Mar 15, Mar 18.

7-km Hike; 

3-km Time

C 21 21 16 No data: Mar 8, Mar 18. High outlier 

(GPS error): Mar 30, Apr 7, Apr 9

HD 21 22 18 No data: run1 Mar 8, run 2 Mar 8, Mar 

15, Mar 18.

7-km Hike; 

4-km Time

C 21 21 16

No data: Mar 8, Mar 18. Negative 

result: Mar 30, Apr 7. Low outlier Apr 

9.

HD 21 22 19 No data: run1 Mar 8, run 2 Mar 8, Mar 

18.

7-km Hike; 

5-km Time

C 21 21 19 No data: Mar 18. High outlier (GPS 

error): Mar 30.

HD 21 22 19 No data: run 2 Mar 8, Mar 18. 

Remove Mar 8 run 1 due to TIR.

7-km Hike; 

6-km Time

C 21 21 17 No data: Mar 18. Low outlier (GPS 

error) Mar 30, Apr 24 and 26.

HD 21 22 20 No data: Mar 18. Remove Mar 8 run 1 

due to TIR.

7-km Hike; 

7-km Time

C 21 21 19 No data: Mar 18. Low outlier (GPS 

error) Mar 30.

HD 21 22 20 No data: Mar 18. Remove Mar 8 run 1 

due to TIR.

Mount Saber C 21 21 19 Remove Apr 2 and Apr 12 due to TIR

 

1 A TIR in this table refers to a Test Incident Report, which is a report the test team or direct assignment 

leaders completed when an incident occurred that affected the natural execution of a trial. If a data point

is removed due to a TIR, it is because the TIR affected the data in such a way that it is not comparable to 

the rest of the data set.
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Task and 

Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

Trials 

Conducted 

Number of 

Trials Used in 

Analysis

Notes

onto Vehicle HD 21 22 20 Remove Apr 2 and Apr 12 due to TIR

Dismount Saber 

from Vehicle

C 21 21 20 Remove Apr 2 due to TIR

HD 21 22 21 Remove Apr 2 due to TIR

TOW 

Engagement 

Accuracy

C 21 21 21

HD 21 24 24

E.5 Descriptive and Basic Inferential Statistics 

E.5.1 Descriptive Statistics Overview

Performance metrics were measured during the conduct of common infantry tasks and 

are indicative of unit-level proficiency during either field exercises or combat operations. 

This section presents results for 7 out of 18 tasks. The Appendix to this Annex contains 

the descriptive statistics for the remainder of the 035X tasks. The words “metric” and 

“task” are used interchangeably throughout this annex. They both refer to the 

experimental task. 

Each squad consisted of four volunteer Marines and a direct assignment squad leader. 

There were two integration levels for all tasks: a C group was not gender integrated, 

and an HD group was gender integrated with two, three, or four female Marines.

This section includes experimental results based on descriptive statistics, analysis of 

variance (ANOVA) (or nonparametric tests as necessary), and scatter plots. The 

subsequent sections will cover each task in detail. Lastly, contextual comments, 

additional insights, and subjective comments (as applicable) tying back to each 

experimental task are incorporated. 

Use caution when comparing similar tasks executed by different MOSs within the 

GCEITF experiment. Comparative analysis may be misleading because of differing 

factors between MOS tasks, such as distances, techniques, leadership, load carried, 

group size, and group composition.

E.5.2 035X Selected Task Descriptive Statistic Results

The two tables that follow display the results for the seven selected 035X metrics. Table 

E-2 displays the metrics and integration levels with their respective sample sizes, 

means, and standard deviations (SDs). Table E-3 displays ANOVA results, including 

metrics and integration levels, p-values suggesting statistical significance, integration 

level elapsed-time differences, and percentage differences between integration levels. 

For each task, an ANOVA and t-test were conducted to compare the two groups. If 

nonparametric tests were needed, Table E-3 displays these results instead of ANOVA 

and t-test results. If p-values are less than the a priori determined significance level of 

0.10, we conclude that there is statistical evidence that the response for the HD group is 

different from that in the C group.
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Table E-2. 035X Selected Task Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD 

7-km Hike (minutes)* C 21 97.18 5.99

HD 21 123.57 12.68

SMAW Engagement by Time 

(minutes)*

C 20 1.30 0.16

HD 24 2.06 0.52

SMAW Engagement Accuracy 

(% hits)*

C 20 0.79 0.19

HD 24 0.49 0.25

Negotiate Obstacle (minutes)* C 21 1.53 0.22

HD 22 3.28 1.24

Negotiate Obstacle [excluding 

potential influential point]

(minutes)*

C 21 1.53 0.22

HD 21 3.04 0.53

CASEVAC (minutes)* C 21 0.91 0.21

HD 20 2.35 0.90

Mount/Dismount Saber 

(minutes)*

C 19 4.26 0.40

HD 20 6.80 0.97

Engage Target (TOW 

Engagement (minutes)*

C 19 3.76 1.78

HD 23 5.58 2.01

*Indicates that there is a statistically significant difference, in either a one-sided 

or two-sided hypothesis test, between integration levels according to ANOVA 

or a nonparametric equivalent test. 

Table E-3. 035X Selected Task ANOVA and Welch's T-test Results

Metric

FStatistic 

(df)

F-Test

P-Value

ComparisonDifference

% 

Difference

2-sided 

P-Value

1-sided 

P-Value

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

7-km Hike 

(minutes)†† 72.09 <0.01* HD-C 26.39 27.15% < 0.01* < 0.01* 22.37 30.40 21.18 31.59

SMAW 

Engagement by

Time (minutes)††

57.76 < 0.01* HD-C 0.76 57.99% < 0.01* < 0.01* 0.61 0.91 0.56 0.95

SMAW 

Engagement 

Accuracy (% hits)*

19.42

(1, 42) < 0.01* HD-C 0.30 -37.83% < 0.01† < 0.01† -0.50† -0.25† -0.50† -0.25† 

Negotiate Obstacle 

(minutes)* 134.86‡ < 0.01‡ HD-C 1.75 114.75% < 0.01† < 0.01† 1.37† 1.68† 1.32† 1.73† 

Negotiate Obstacle 

[excluding 

potential 

influential point]

(minutes)††

145.18 < 0.01* HD-C 1.51 99.12% < 0.01* < 0.01* 1.35 1.68 1.30 1.73

CASEVAC 

(minutes)†† 52.69 < 0.01* HD-C 1.44 159.25% < 0.01* < 0.01* 1.17 1.72 1.09 1.80

Mount/Dismount 

Saber (minutes) †† 128.25 < 0.01* HD-C 2.54 59.82% < 0.01* < 0.01* 2.23 2.86 2.14 2.95

TOW Engagement 

(minutes)*

9.40

(1, 40) < 0.01* HD-C 1.82 48.36% < 0.01† < 0.01† 1.23† 2.10† 1.18† 2.15† 
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*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a nonparametric equivalent test.

†Results presented are from a Mann-Whitney nonparametric test due to non-normality. 

††Indicates that results presented are from Robust ANOVA and Welch’s t-tests with p-values compared 

to 0.05 for Bonferroni adjustment due to unequal variances. The reported F-statistic is a Chi-square 

statistic from Robust ANOVA, and the F-test p-value is the Robust ANOVA p-value. The p-values in 

columns labeled “2-sided P-value” and “1-sided P-value” are p-values from Welch’s t-tests, and the 

confidence intervals are from Welch’s t-tests.

‡Indicates that results presented are from Robust ANOVA due to unequal variances. The reported Fstatistic is a Chi-square statistic from Robust ANOVA, and the F-test p-value is the Robust ANOVA pvalue.

E.5.2.1 7-km Hike

E.5.2.1.1 7-km Hike Overview

This experimental task assessed a squad of four Marines moving 7.20 km while each 

Marine carried an approach load, an individual weapon (M-4), and a portion of the crewserved weapon load. The crew-served load consisted of two SMAW launchers and four 

SMAW rockets, resulting in a cumulative load of 116-132 lb per Marine. The recorded 

time for this task started when the squad departed the Range 107 start point and 

stopped when the squad arrived at the Range 110 stop point. The squads moved as 

fast as the slowest person and could take as many breaks as necessary.

Figure E-1 displays all 035X 7-km hike time data. All data on the scatter plot are valid 

for analysis.

Figure E-1. 7-km Hike
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The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.78 for the C group and 0.19 for the HD group. 

The C group had a mean time of 97.18 minutes. This time is statistically significantly 

faster than the HD mean time of 123.57 minutes. This difference results in a 27.15%, or 

26.39-minute, degradation in hike time between the groups. The HD group had greater 

variability, as shown by the 6.69-minute increase in SD (5.99 minutes for the C group 

and 12.68 minutes for the HD group). See Table E-2 and Table E-3 for detailed 

analytical results.

E.5.2.1.2 7-km Hike Contextual Comments

E.5.2.1.2.1 USMC Hike Standards

The 7-km hike is a task that the following MOSs completed during the experiment: 

0311, 0331, 0341, 0351, and 0352, Provisional Infantry, Provisional Machine Gunners, 

and Combat Engineers. There are varying standards to which we can compare this 

result. The following sections define those standards, as well as the one we chose as a 

comparison.

The Infantry T&R Manual (30 August 2013) identifies minimum standards that Marines 

must be able to perform in combat, including standards for tactical marches. In Chapter 

8 of the Infantry T&R Manual in the MOS 0300 Individual Events section, task “0300-

COND-1001: March under an approach load” is applicable to all 03XX MOSs, ranks 

PVT – LtCol. The condition and standard established by this task is: “Given an 

assignment as a member of a squad, individual weapon, and an approach load, 

complete a 20 kilometer march in under 5 hours.” The march pace required by this 

standard is 4 kilometers per hour (km/h). In Chapter 9 of the Infantry T&R Manual in the 

MOS 0302/0369 Individual Events section, tasks “0302-OPS-2001: Lead an approach 

march” and “0369-OPS-2501: Lead an approach march” are applicable to MOS 0302 

and 0369, ranks SSgt – MGySgt and 2ndLt – LtCol. The condition and standard 

established by these tasks is: “Given a mission, time constraints, an approach march 

load, organic weapons, and a route, move 24.8 miles (40 km) in a time limit of 8 hours.” 

The march pace required by this standard is 5 km/h. Appendix E of the Infantry T&R 

Manual (Load Terms and Definitions) states: “The approach march load will be such 

that the average infantry Marine will be able to conduct a 20 mile hike in 8-hours with 

the reasonable expectation of maintaining 90% combat effectiveness.” The march pace 

required by this definition is 4.02 km/h.

Chapter 3 of Fleet Marine Force Reference Publication (FMFRP) 3-02A, Marine 

Physical Readiness Training for Combat (16 June 2004) states: “The normal pace is 30 

inches. A pace of 30 inches and a cadence of 106 steps per minute result in a speed of 

4.8 km/h or 3 mi/h and a rate of 4 km/h or 2.5 mi/h if a 10-minute rest halt per hour is 

taken.” Common Infantry practice today is to hike for 50 minutes and take a 10-minute 
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break, while maintaining an overall pace of 4 km/h (resulting in a hiking pace of 4.8 

km/h). 

Driven by the need to pick an evaluative reference standard, this report follows the T&R 

Manual’s intent to establish minimum standards and uses the 4-km/h march pace for a 

20-km march established by task 0300-COND-1001 and supported by the definition of 

an approach load. Further, while an established reference standard is required to 

anchor observed performance to the T&R program, more important information is 

provided by performance differences observed between units that are gender integrated 

and those that are not. 

E.5.2.1.2.2 035X Hike Pace

This result is relevant to both the training and combat environment, as it will take 

integrated squads more time to conduct foot movements. Per the tactical march 

standards noted earlier, the Marine Corps standard of hiking is 4.0 km/h. The HD group 

failed to meet this standard. The C group average pace was 4.45 km/h, while the HD 

group average pace was 3.50 km/h, finishing 26.4 minutes behind the C group. To 

extrapolate this pace over a 20-km movement (an optimistic assumption that does not 

account for any further degradation of performance), it would take the C group 4 hours 

and 30 minutes and the HD group 5 hours and 43 minutes to complete the hike, 

finishing 73 minutes behind the C group. With the exception of one instance, the 

slowest C group was faster than the fastest HD group throughout the duration of the 

experiment. Furthermore, on any given day (under the same environmental conditions), 

the C group was faster than the HD group 100% of the time (21 of 21 trial cycles). 

Based on the SDs, the variation in performance of the HD group is greater than twice as 

much as the variation in performance of the C group. This inconsistency in the 

performance of the HD group leads to greater uncertainty and less confidence in their 

future performance from the mean.

E.5.2.1.3 7-km Hike Additional Insights

A variety of factors potentially explains the high degree of variability within the HD 

group: the weather, Day 2 versus Day 4 hike execution, or most notably the crewserved load that varied from 116 to 132 lb. 

Based on the USMC standard of a 4-km/h pace over a 7.20-km route (which would 

result in a 108-minute hike completion time over the 7.20 km), the HD group was 15.57 

minutes slower than that standard. In a battlefield situation, in which speed is essential, 

this delay is advantageous for the enemy. An enemy maneuvering at 4 km/h would 

have the time to move 1.04 km, shift indirect fires from preplanned targets, commit the 

employment of their least engaged unit, or conduct a spoiling attack. 

Marine Corps Doctrinal Publications (MCDPs) consistently emphasize the importance of 

speed. MCDP 1-3 Tactics devotes an entire chapter to “Being Faster” and states, 
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“Physical speed, moving more miles per hour, is a powerful weapon in itself.” MCDP-6 

Command and Control also speaks to speed relative to the enemy and states, “The 

speed differential does not necessarily have to be a large one: a small advantage 

exploited repeatedly can quickly lead to decisive results.” Further insights may be 

gleaned from the Appendix, which shows the difference in speed by kilometer. In 

general, the difference in performance increased as the movement got longer.

E.5.2.1.4 7-km Hike Subjective Comments

For subjective comments relating to this task, see the Appendix.

E.5.2.2 SMAW Engagement by Time

E.5.2.2.1 SMAW Engagement by Time Overview

This experimental task assessed the time for an assault squad (composed of a pair of 

two-Marine SMAW teams) to move approximately 50 meters from a cold position to a 

hot position and engage two targets with four rockets. One rocket reload per team was 

conducted between the first and second shots. The recorded time for this task started 

when the squad departed the cold position and stopped when the last (fourth) rocket 

was fired. Two SMAW teams conducted this engagement in sequence.

Figure E-2 displays all 035X SMAW engagement time data. All data on the scatter plot 

are valid for analysis.

Figure E-2. SMAW Engagement by Time
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The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.24 for the C group and 0.17 for the HD group. 

The C group had a mean time of 1.30 minutes. This time is statistically significantly 

faster than the HD mean time of 2.06 minutes. This difference results in a 57.99%, or 

0.76-minute, degradation in engagement time between the groups. The HD group had 

greater variability, as shown by the 0.36-minute increase in SD (0.16 minute for the C 

group and 0.52 minute for the HD group). See Table E-2 and Table E-3 for detailed 

analytical results.

E.5.2.2.2 SMAW Engagement by Time Contextual Comments

The ability to maneuver the SMAW rockets into an advantageous firing position is 

critically important to the forward progress and tempo of an assaulting unit. The faster 

this weapon system is brought to bear against an enemy target, the less time for friendly 

elements to be exposed to a threat. MCDP 1 states, “Speed is rapidity of action. It 

applies to both time and space. Both forms are genuine sources of combat power. In 

other words, speed is a weapon.” The experimental results show that an HD group 

takes on average 46 seconds longer, a 58% degradation in performance, to accomplish 

the same task. Furthermore, on any given day (under the same environmental 

conditions), the C group was faster than the HD group 95.2% of the time (20 of 21 trial 

cycles). Based on the SDs, the variation in performance of the HD group is greater than 

three times the variation in performance of the C group. This inconsistency in the 

performance of the HD group leads to greater uncertainty and less confidence in its 

future performance from the mean.

E.5.2.2.3 SMAW Engagement by Time Additional Insights

A purely objective evaluation of 46 seconds is elusive but may possess some practical 

significance on the battlefield that would reduce the survivability of an integrated squad. 

Considering the 650-rounds-per-minute sustained rate of fire from an RPK-74 machinegun bunker, a single enemy machine-gun team would have the time/opportunity fire 498 

rounds against an integrated squad still exposed to enemy fire. The resultant trade in 

casualty exchange could be significant. The difference in this movement and 

engagement time is even more noteworthy when one considers the accuracy for each 

SMAW engagement. See the results for the SMAW accuracy, Section E.5.2.3, to 

compare accuracy versus engagement time. On average, the HD groups were 38% less 

accurate than the C group.

E.5.2.2.4 SMAW Engagement by Time Subjective Comments

For subjective comments relating to this task, see the Appendix.
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E.5.2.3 SMAW Engagement Accuracy

E.5.2.3.1 SMAW Engagement Accuracy Overview

This experimental task assessed the accuracy of an assault squad engaging two targets 

with four rockets. Two two-Marine teams, each firing two SMAW rockets, conducted the 

engagement. The first target was at a distance of 150 m and the second target was at a 

distance of 250 m. This task was conducted after walking 1 km, bounding 500 m, and 

sprinting 50 m to arrive at an advantageous firing position. Accuracy was assessed as a 

hit or miss on a vehicle-sized target.

Figure E-3 displays all 035X SMAW engagement accuracy data. All data on the scatter 

plot are valid for analysis.

Figure E-3. SMAW Engagement Accuracy

The HD group data are normally distributed as evidenced by the Shapiro-Wilk Test that 

resulted in a p-value of 0.04, but data are not normally distributed for the C group, which 

had a p-value of <0.01. We proceed with presenting ANOVA results because they were 

confirmed by a Mann-Whitney Test with a p-value of <0.01.

The C group had a mean proportion of hit of 0.79. This proportion is statistically 

significantly higher than the HD proportion of 0.49. This difference results in a 37.88%, 

or 0.30-percentage-point, degradation in accuracy between the groups. The HD group 

had greater variability, as shown by the 0.06-percentage point increase in SD (0.19

minute for the C group and 0.25 minute for the HD group). See Table E-2 and Table E-3

for detailed analytical results.
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E.5.2.3.2 SMAW Engagement Accuracy Contextual Comments

Accuracy is the measure of military effectiveness with a given weapon system under 

operational conditions. In combat operations, accuracy is highly desirable in destroying 

an enemy target. Ammunition, especially rockets, must be employed with precision 

since they are limited on the battlefield. To extrapolate the probability of hit to a 

battlefield situation in which there are 10 known targets, a C group would need to 

carry/fire 13 rockets, while an HD group would need to carry/fire 21 rockets to have the 

same military effect. Furthermore, on any given day (under the same environmental 

conditions), the C group was more accurate than the HD group 90% of the time (18 of 

20 trial cycles).

E.5.2.3.3 SMAW Engagement Accuracy Additional Insights

This accuracy data are even more noteworthy when one considers the amount of time it 

took for each SMAW engagement. See the results for the SMAW engagement times, 

Section E.5.2.2, to compare accuracy versus engagement time. On average, the HD 

groups took 46 seconds longer to conduct each trial. 

E.5.2.3.4 SMAW Engagement Subjective Comments

For subjective comments relating to this task, see the Appendix.

E.5.2.4 Negotiate Obstacle

E.5.2.4.1 Negotiate Obstacle Overview

This experimental task involved a squad of four Marines getting all Marines and 

equipment over an 8-foot ISO Container (wall obstacle) as quickly as possible. The 

squad began this task as soon as it finished the 1-km movement. The time started when 

the first Marine touched the obstacle and stopped when the last Marine touched both 

feet down on the other side.

Figure E-4 displays all negotiate obstacle data. There was one potential influential point: 

the HD on trial cycle 1. Because the impact of this point is unknown, we perform all 

analysis with and without this point. All data on the scatter plot are valid for analysis.
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Figure E-4. Negotiate Obstacle with Potential Influential Point Circled

The inclusion of the potential influential point does not change the statistical significance 

between groups. It does, however, change the SD and percentage differences between 

the integration levels. Once we remove the potential influential point, the percentage

difference between the C group and HD group decreases. The SD for the HD group

decreases without the potential influential point. Additionally, the removal of the 

potential influential point results in the data for HD group being normally distributed. The 

following sections discuss results with and without the potential influential point.

E.5.2.4.1.1 Negotiate Obstacle Descriptive Statistics with Potential Influential Point

The data for C group are normally distributed as evidenced by the Shapiro-Wilk Test 

that resulted in a p-value of 0.77 but not normally distributed for the HD group, which 

had a p-value of <0.01. We proceed with presenting ANOVA results because they were 

confirmed by a Mann-Whitney Test with a p-value of <0.01.

The C group had a mean time of 1.53 minutes. This time is statistically significantly 

faster than the HD mean time of 3.28 minutes. This difference results in a 114.75%, or 

1.75-minute, degradation in time between the groups. The HD group had greater 

variability, as shown by the 1.02-minute increase in SD (0.22 minutes for the C group 

and 1.24 minutes for the HD group). See Table E-2 and Table E-3 for detailed analytical 

results. 
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E.5.2.4.1.2 Negotiate Obstacle Descriptive Statistics without Potential Influential Point

The data are normally distributed, as evidenced by the Shapiro-Wilk Test that resulted 

in a p-value of 0.77 for the C group and 0.45 for the HD group. 

The C group had a mean time of 1.53 minutes. This time is statistically significantly 

faster than the HD mean time of 3.04 minutes. This difference results in a 99.12%, or 

1.51-minute, degradation in time between the groups. The HD group had greater 

variability, as shown by the 0.31-minute increase in SD (0.22 minute for the C group 

and 0.53 minute for the HD group). See Table E-2 and Table E-3 for detailed analytical 

results. 

E.5.2.4.2 Negotiate Obstacle Contextual Comments

Sun Tzu stated, “Speed is the essence of war. Take advantage of the enemy’s 

unpreparedness; travel by unexpected routes and strike him where he has taken no 

precautions” (MCDP-1, p. 69). Speed and surprise are crucial to success. Furthermore, 

the enemy is reliably expected to cover obstacles with fires. When possible, obstacles 

are to be avoided. When not possible, they must be negotiated quickly. While no purely 

objective standard can be set for the negotiation of the obstacle presented in this task, 

any decrement in speed translates into increased exposure to enemy fires and greater 

risk for friendly casualties.

Throughout the assessment, within a given MOS and task, the C and HD groups used 

the same techniques to accomplish each task. However, this was not the case for this 

task. The influential point on Trial Cycle 1 represents the only occurrence in which the 

HD group performed this task using the same technique as the C group as a fully 

integrated squad (four females). During every other trial, the HD group utilized a 

mechanical advantage by attaching three web belts and using it as a ladder to aid in 

getting the last Marine over the obstacle. The HD group constructed this improvised 

ladder in advance of each trial for the duration of the experiment.

On average, the HD groups were 1.51 minutes slower than the C groups in performing 

the same task, a 99.12% degradation in performance. Through the course of the 

experiment, the slowest C group was faster than the fastest HD group. Furthermore, on 

any given day (under the same environmental conditions), the C group was faster than 

the HD group 100% of the time (21 of 21 trial cycles). Based on the SDs, the variation in 

performance of the HD group is greater than twice as much as the variation in 

performance of the C group. This inconsistency in the performance of the HD group 

leads to greater uncertainty and less confidence in its future performance from the 

mean.

E.5.2.4.3 Negotiate Obstacle Additional Insights

During nine HD trials, a partially integrated squad of two or three females was 

assessed. The mechanical device was not utilized whenever a male was part of the 
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squad. Four of these nine trials represent the four fastest HD times: 7 March 2015, 16 

April 2015, 18 April 2015, and 25 April 2015 (Trial Cycles 1, 17, 18, and 21, 

respectively). 

E.5.2.4.4 Negotiate Obstacle Subjective Comments

The subjective leadership log adds greater fidelity by stating that, for the HD group’s 

four fastest trails (Trial Cycles 1, 17, 18, and 21), a male Marine “pulled all other 

Marines in team over the obstacle; performing majority of the work.”

For additional subjective comments relating to this task, see the Appendix.

E.5.2.5 CASEVAC

E.5.2.5.1 CASEVAC Overview

This experimental task assessed the squad’s ability to move a 220-lb dummy a distance 

of 100 meters to a CCP while wearing a fighting load, individual weapon, and two 

SMAW launchers. Marines conducted this task at the conclusion of the SMAW 

engagement. Squads could use a variety of techniques, but they had to move all 

personnel and gear the entire distance, as well as carry the dummy off the ground. The 

recorded time started when Marines touched the dummy and it stopped when the 

dummy and all members of the squad arrived at the CCP.

Figure E-5 displays all CASEVAC data. All data on the scatter plot are valid for analysis.

Figure E-5. CASEVAC
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The data are normally distributed, as evidenced by the Shapiro-Wilk Test that resulted 

in a p-value of 0.18 for the C group and 0.06 for the HD group. 

The C group had a mean time of 0.91 minute. This time is statistically significantly faster 

than the HD mean time of 2.35 minutes. This difference results in a 159.25%, or 1.44-

minute, degradation in time between the groups. The HD group had greater variability, 

as shown by the 0.69-minute increase in SD (0.21 minute for the C group and 0.90 

minute for the HD group). See Table E-2 and Table E-3 for detailed analytical results.

E.5.2.5.2 CASEVAC Contextual Comments

The implications of this task contain relevance to both the training and combat 

environment because a casualty must be moved expediently to a higher echelon of 

medical care. The data demonstrate that integrated squads took 1.44 minutes longer, a

159.25% degradation in performance, to accomplish the same 100-meter casualty 

movement. With the exception of 3 of 21 trials, the slowest C group was faster than the 

fastest HD group. During these three exceptions (Trial Cycles 17, 20, and 21), the HD 

group was partially integrated with three females, vice fully integrated. Furthermore, on 

any given day (under the same environmental conditions), the C group was faster than 

the HD group 100% of the time (21 of 21 trial cycles). Based on the SDs, the variation in 

performance of the HD group is greater than four times the variation in performance of 

the C group. This inconsistency in the performance of the HD group leads to greater 

uncertainty and less confidence in their future performance from the mean.

E.5.2.5.3 CASEVAC Additional Insights

While the “Golden Hour” is a common medical planning construct for C2 and logistical 

support, medical literature supports a “Platinum Ten” philosophy of first response. The 

U.S. National Library of Medicine references a French article that states that “on the 

battlefield, the majority of casualties die within ten minutes of the trauma” (Wounded in 

Action: The Platinum Ten Minutes and the Golden Hour, Daban). The fundamental 

principle is that patient need to be correctly triaged and moved to medical care as fast 

as possible. Any time degradation reduces the probability of survival.

E.5.2.5.4 CASEVAC Subjective Comments

Seven instances in the leadership subjective logs indicated that an HD group required 

extra breaks in order to stop and put the dummy down, compared with zero comments 

for the C group. The implication is that a C group could have maintained its CASEVAC 

pace for a longer distance, while the HD group could not have maintained its CASEVAC 

pace over a longer distance. Therefore, the longer the CASEVAC distance, the greater 

the difference in time will be due to integration.

For additional subjective comments relating to this task, see the Appendix.
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E.5.2.6 Mount/Dismount Saber

E.5.2.6.1 Mount/Dismount Saber Overview

This experimental task assessed the squad’s ability to mount a Saber system onto a 

tactical vehicle (HMMWV) and then dismount it. A brief, non-assessed administrative 

pause was conducted between the mounting and dismounting subtasks. This task was 

conducted approximately 10 minutes after the conclusion of the 7-km hike. The 

recorded time started when Marines touched a component of the Saber, and it stopped 

when the last component of the Saber was back on the ground.

Figure E-6 displays all 035X mount/dismount Saber data. All data on the scatter plot are 

valid for analysis.

Figure E-6. Mount/Dismount Saber

The data are normally distributed, as evidenced by the Shapiro-Wilk Test that resulted 

in a p-value of 0.22 for the C group and 0.77 for the HD group. 

The C group had a mean time of 4.26 minutes. This time is statistically significantly 

faster than the HD mean time of 6.80 minutes. This difference results in a 59.82%, or 

2.54-minute, degradation in time between the groups. The HD group had greater 

variability, as shown by the 0.57-minute increase in SD (0.40 minute for the C group 

and 0.97 minute for the HD group). See Table E-2 and Table E-3 for detailed analytical 

results. 
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E.5.2.6.2 Mount/Dismount Saber Contextual Comments

The challenging aspect of mounting and dismounting the Saber system is the weight of 

the components. On average, it took the HD groups 2.54 minutes longer, a 59.82% 

degradation in performance. With the exception of one trial cycle, the fastest HD group 

was slower than the slowest C group throughout the duration of the experiment. 

Furthermore, on any given day (under the same environmental conditions), the C group 

was faster than the HD group 100% of the time (19 of 19 trial cycles). Based on the 

SDs, the variation in performance of the HD group is greater than twice the variation in 

performance of the C group. This inconsistency in the performance of the HD group 

leads to greater uncertainty because there is less confidence in its future performance 

from the mean.

E.5.2.6.3 Mount/Dismount Saber Additional Insights

This task began with all components of the Saber system prestaged on the deck within 

2 meters of the HMMWV. The Marines were not required to move the Saber system 

to/from the actual firing position. For an indication of the performance when moving 

heavy objects, see results for the TOW engagement (Section E.5.2.7), which involved 

moving a 50-lb TOW missile a distance of 100 meters.

E.5.2.6.4 Mount/Dismount Saber Subjective Comments

For subjective comments relating to this task, see the Appendix.

E.5.2.7 TOW Engagement

E.5.2.7.1 TOW Engagement Overview

This experimental task assessed the squad’s time to move four TOW missiles (each 

weighing 50 lb) approximately 100 m to a firing line and engage four targets. Due to 

experimental efficiencies, the Saber system was pre-established on a firing line. One 

missile reload per team was conducted between the first and second shots. The 

recorded time started when the squad departed the ORP, and it stopped when the last 

TOW missile was fired.

Figure E-7 displays all 035X TOW engagement data. All data on the scatter plot are 

valid for analysis.
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Figure E-7. TOW Engagement

The data are not normally distributed, as evidenced by the Shapiro-Wilk Test that 

resulted in a p-value of <0.01 for the C and HD groups. We proceed with presenting 

ANOVA results because they were confirmed by a Mann-Whitney Test with a p-value of 

<0.01.

The C group had a mean time of 3.76 minutes. This time is statistically significantly 

faster than the HD mean time of 5.58 minutes. This difference results in a 48.36%, or 

1.82-minute, degradation in time between the groups. The HD group had greater 

variability, as shown by the 0.23-minute increase in SD (1.78 minutes for the C group 

and 2.01 minutes for the HD group). See Table E-2 and Table E-3 for detailed analytical 

results. 

E.5.2.7.2 TOW Engagement Contextual Comments

Each TOW missile weighs over 50 lb. The ability to quickly move a TOW missile to a 

Saber system and effectively engage targets is important to eliminating enemy targets 

on the battlefield while minimizing exposure. On average, it took the HD group 1.82 

minutes longer than the C group, a 48.36% degradation in performance, to accomplish 

the same movement and engagement. This provides the enemy that much more time 

to engage friendly positions. Furthermore, on any given day (under the same 

environmental conditions), the C group was faster than the HD group 89.5% of the time 

(17 of 19 trial cycles).

E.5.2.7.3 TOW Engagement Additional Insights

None.
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E.5.2.7.4 TOW Engagement Subjective Comments

For subjective comments relating to this task, see the Appendix.

E.6 Statistical Modeling Results 

E.6.1 Statistical Modeling Overview

The previous section discussed results only as they pertain to differences due to 

integration level alone. The goal of statistical modeling, as applied here, is to estimate, 

simultaneously, the effect of gender integration levels and other relevant variables on 

squad performance. Refer to the Methodology Annex for a broad overview of the 

analysis plan and the variables used in the models. 

For the same seven selected tasks described in the previous section, this section 

presents an overview of the analysis and results and then presents the modeling results 

for each of the tasks.

For each task, we describe the significant variables in the model and determine whether 

they are positively or negatively correlated with the result. A negative correlation 

indicates that an increase in that variable will result in a decrease in the response 

variable, which is a desired outcome for elapsed time. The results indicate where 

certain patch numbers are significant for a given variable. The experiment tracked 

Marines within the squad by a patch number that associated their random position 

within the squad to a specific billet. Table E-4 displays the 035X patch numbers and 

billet titles.

Table E-4. 035X Patch Numbers and Billet Titles

Patch Number Billet Title

1 Gunner

2 Assistant Gunner

3 Gunner

4 Assistant Gunner

E.6.2 035X Selected Task Method of Analysis

Because there are two different types of responses for the 035X selected tasks, we 

used two different methodologies. For all of the elapsed time response variables, we 

used a mixed effects model. For the SMAW hits, we used a multinomial logit model. The 

following sections describe each of these methodologies in more detail.

E.6.2.1 Mixed Effects Models

Due to the small number of trials, a mixed effects model with all 035X squad members 

and all types of personnel data does not work for the 035X data set. Thus, we model 
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each personnel variable with integration level separately with a random effect for who 

filled each position within the 035X squad. For example, age for each member of the 

035X squad (four variables), a random effect for who filled each billet, and integration 

level are modeled with the result (response time) as the response variable. Where 

maximum likelihood estimation converged, AIC was used for variable selection. 

Otherwise, we comment on the significance of individual variables in the full model. 

Variables reported as significant are concluded to be significant based on at least a 

one-sided test.

E.6.2.2 Multinomial Logit Model

We modeled the SMAW hits using a multinomial logit model where the number of 

impacts is the response variable and is modeled as a categorical variable. The levels for 

this variable are 0, 1, 2, 3, and 4, which correspond to the potential number of hits. Each 

personnel variable was modeled separately due to the small number of trials. For each 

model, we used the AIC to choose which variables to include in the model.

E.6.3 035X Selected Task Overall Modeling Results

Integration level is significant for all of the selected tasks modeled. For each of these 

tasks, modeling the random effects for the individuals participating in the task results in 

changes from the initial results in the descriptive statistics. Each respective task 

paragraph describes these changes.

The negotiate obstacle task had a potential influential point, and we model this task with 

and without this point. The HD integration level is significant for all variables in each of 

these analyses. Not all of the same variables remain significant when modeled with and 

without influential points. However, analysis with and without the potential influential 

point for the negotiate obstacle task does not change the overall result of the effect of 

the integration levels.

E.6.3.1 7-km Hike

We model elapsed time for the 7-km hike as a function of each personnel variable and 

integration level in a separate mixed model. The covariates in each model are the 

values of each personnel variable for each patch number, integration level, and a 

random effect of who filled each position in the squad. For each model, we report 

statistically significant positive and negative correlations and whether we observe any 

patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:
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• Squad leader

• Age 

• Armed Forces Qualification Test (AFQT) score 

• General Classification Test (GT) score 

• Physical Fitness Test (PFT) crunches 

• PFT 3-mile run

• Rifle score. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• Height. 

The following personnel variables are significant in their respective models and are 

positively correlated with the 7-km hike time:

• AFQT score of patch 4

• CFT Movement to Contact of patches 1, 2, and 4

• CFT Maneuver Under Fire time of patches 2, 3, and 4. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the 7-km hike time:

• Height of patches 1, 2, 3, and 4 

• Weight of patches 1, 2, and 4.

The following personnel variables have no significant variables in their respective

models:

• None.

Height of all Marines was significant and negatively correlated for all Marines. This 

model also included integration level, which was negatively correlated with the 7-km 

hike time where the coefficient for integration level is -15.98. This is the only model for 

which integration level is significant and negatively correlated with the 7-km hike time. In 

the final model with only integration level, the coefficient for integration level is 23.00. 

Due to this large change in both magnitude and direction, it is highly likely there is a 

problematic multicollinearity between height and integration level in this model. This 

result is only reported for completeness as it is impractical and unsubstantial due to the 

negative correlation.

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, the final model includes integration level only where HD has 
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a difference of 23.00 minutes when compared with a C group and a p-value of <0.01. 

This difference is a decrease from the 26.39-minute difference identified in the 

descriptive statistics, which is a 12.85% change.

E.6.3.2 SMAW Engagement by Time

We model elapsed time for the SMAW engage targets as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and 

a random effect of who filled each position in the squad. For each model, we report 

statistically significant positive and negative correlations and whether we observe any 

patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• Squad leader 

• Age 

• Height 

• Weight 

• AFQT score 

• GT score

• CFT Movement to Contact 

• PFT crunches 

• PFT 3-mile run 

• Rifle score. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the SMAW engage targets time:

• Age of patches 3 and 4

• Height of patch 4

• AFQT score of patch 3
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• GT score of patch 3

• CFT Movement to Contact of patches 1 and 2

• CFT Maneuver Under Fire of patches 1, 2 and 3

• PFT 3-mile run of patch 2. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the SMAW engage targets time:

• Height of patches 1 and 2

• Weight of patch 2

• CFT Movement to Contact of patch 4

• CFT Maneuver Under Fire of patch 4

• PFT crunches of patch 2

• PFT 3-mile run of patch 3. 

The following personnel variables have no significant variables in their respective 

models:

• None.

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, the final model includes integration level only where HD has 

a difference of 0.61 minute when compared with a C group and a p-value of <0.01. This 

difference is a decrease from the 0.76-minute difference identified in the descriptive 

statistics, which is a 19.74% change.

E.6.3.3 SMAW Engagement Accuracy

We model SMAW engagement accuracy as a function of each personnel variable and 

integration level in a separate multinomial logit model. The covariates in each model are 

the values of each personnel variable for each patch number and integration level. For 

each model, we report the variables chosen using AIC to remain in the model and if 

those variables have a positive, negative, or nonlinear correlation with the response. 

Using AIC for variable selection, the HD integration level remained in the model in the 

following variable’s respective models:

• Squad leader

• Age

• Weight

• AFQT score
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• GT score

• PFT crunches

• PFT 3-mile run

• CFT Movement to Contact

• CFT Maneuver Under Fire

• Rifle score.

Model selection using AIC resulted in the following personnel variables in the final 

model, and they had a positive correlation with the SMAW engagement accuracy:

• Height of patch 1. 

Model selection using AIC resulted in the following personnel variables in the final 

model, and they had a negative correlation with the SMAW engagement accuracy:

• Height of patches 2 and 4

• CFT Movement to Contact for patch 1. 

Model selection using AIC resulted in the following personnel variables in the final 

model, and they had a nonlinear correlation with the SMAW engagement accuracy:

• PFT 3-mile run for patch 1

• Rifle score for patch 1.

The final model includes integration level only. Integration level is negatively correlated 

with the SMAW accuracy, meaning changing integration level from C to HD results in a 

lower probability of hit. Table E-5 shows the probabilities of obtaining a specific number 

of hits on target by integration level based on the model results.

Table E-5. Probability of SMAW Hit by Integration Level

Number of Hits C HD

0 0.00% 8.33%

1 5.00% 20.83%

2 5.00% 41.67%

3 60.00% 25.00%

4 30.00% 4.17%

E.6.3.4 Negotiate Obstacle Overview

We model elapsed time for the negotiate obstacle as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and 

a random effect of who filled each position in the squad. For each model, we report 
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statistically significant positive and negative correlations and whether we observe any 

patterns.

There was one potential influential point (HD group on trial cycle 1), and we model the 

negotiate obstacle time with and without this point. 

E.6.3.4.1 Negotiate Obstacle with Potential Influential Point

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• All. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the negotiate obstacle time:

• Age of patch 2

• CFT Maneuver Under Fire of patch 1

• PFT crunches of patch 2

• Rifle score of patch 2. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the negotiate obstacle time:

• Weight of patches 2 and 3

• CFT Movement to Contact of patch 2

• PFT crunches of patch 4. 

The following personnel variables have no significant variables in their respective 

models:

• None.

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, the final model includes integration level only where HD has 

a difference of 1.91 minutes when compared with a C group and a p-value of <0.01. 

This difference is an increase from the 1.75-minute difference identified in the 

descriptive statistics, which is an 8.38% change.
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E.6.3.4.2 Negotiate Obstacle without Potential Influential Point

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• All.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the negotiate obstacle time:

• Age of patch 3

• CFT Movement to Contact of patch 1

• CFT Maneuver Under Fire of patch 1

• Rifle score of patch 2. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the negotiate obstacle time:

• Squad leader 

• Height of patch 1

• Weight of patch 1. 

The following personnel variables have no significant variables in their respective 

models:

• None.

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, the final model includes integration level only where HD has 

a difference of 1.55 minutes when compared with a C group and a p-value of <0.01. 

This difference is an increase from the 1.51-minute difference identified in the 

descriptive statistics, which is a 2.65% change.

E.6.3.5 CASEVAC

We model elapsed time for the CASEVAC as a function of each personnel variable and 

integration level in a separate mixed model. The covariates in each model are the 

values of each personnel variable for each patch number, integration level, and a 
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random effect of who filled each position in the squad. For each model, we report 

statistically significant positive and negative correlations and whether we observe any 

patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• All.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the CASEVAC time:

• Age of patch 3

• AFQT score of patch 3

• GT score of patch 3

• CFT Movement to Contact of patch 1

• CFT Maneuver Under Fire of patch 1, 2, and 3

• PFT 3-mile run of patch 2. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the CASEVAC time:

• Age of patch 2

• Height of patches 1 and 2

• Weight of patch 1

• AFQT score of patch 2

• PFT crunches of patches 2

• Rifle score of patch 1. 

The following personnel variables have no significant variables in their respective 

models:

• None.
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Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, the final model includes integration level only where HD has 

a difference of 1.45 minutes when compared to a C group and a p-value of <0.01. This 

difference is an increase from the 1.44-minute difference identified in the descriptive 

statistics, which is a 0.69% change.

E.6.3.6 Mount/Dismount Saber

We model elapsed time for the mount/dismount Saber as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and

a random effect of who filled each position in the squad. For each model, we report 

statistically significant positive and negative correlations and whether we observe any 

patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• All.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the mount/dismount Saber time:

• AFQT score of patch 4

• GT score of patch 4

• CFT Maneuver Under Fire of patch 3

• PFT 3-mile run of patch 2. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the mount/dismount Saber time:

• Height of patch 3

• CFT Maneuver Under Fire time of patch 2

• PFT crunches of patch 1

• PFT 3-mile run of patch 4. 
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The following personnel variables have no significant variables in their respective 

models:

• None.

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, the final model includes integration level only where HD has 

a difference of 2.25 minutes when compared with a C group and a p-value of <0.01. 

This difference is a decrease from the 2.54-minute difference identified in the 

descriptive statistics, which is an 11.42% change.

E.6.3.7 TOW Engagement

We model elapsed time for the TOW engagement as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and 

a random effect of who filled each position in the squad. For each model, we report 

statistically significant positive and negative correlations and whether we observe any 

patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• All.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables: 

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the TOW engagement time:

• AFQT score of patch 1

• PFT 3-mile run of patch 2. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the TOW engagement time:

• Age of patch 1

• AFQT score of patch 2

• PFT crunches of patch 2. 
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The following personnel variables have no significant variables in their respective 

models:

• None.

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, the final model includes integration level only where HD has 

a difference of 2.22 minutes when compared with a C group and a p-value of 0.02. This 

difference is an increase from the 1.82-minute difference identified in the descriptive 

statistics, which is a 21.98% change.
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Appendix to Annex E 

035X Supplemental Information

This appendix provides supplemental information for the 035X portion of the GCEITF

experiment. It provides information regarding the GCEITF leadership subjective 

comments and additional descriptive and basic inferential statistics not described in 

Annex E. 

Section 1. GCEITF Leadership Subjective Comments

The GCEITF leadership provided comments on their observations of the experiment 

throughout it execution. Table E A displays a summary of these comments broken 

down by task, integration level, gender, and type of comment.

Table E A – Summary of GCEITF Leadership Comments

Task and Metric 

Description Gender Total

C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total

M 13 0 13 1 0 1 0 0 0 0 3 3 0 0 0 0 0 0 2 0 2 0 0 0 19

F 0 20 20 0 1 1 0 1 1 0 4 4 0 0 0 0 6 6 0 0 0 0 0 0 32

Unit 0 3 3 0 4 4 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 9

M 1 3 4 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5

F 0 16 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16

Unit 0 2 2 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 3

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1

F 0 0 0 0 0 0 0 4 4 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 5

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1

M 0 0 0 0 0 0 0 0 0 0 0 0 0 5 5 0 0 0 1 0 1 0 0 0 6

F 0 0 0 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

Unit 0 0 0 0 0 0 0 1 1 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 3

M 0 0 0 0 0 0 0 0 0 2 2 4 0 0 0 0 0 0 0 0 0 0 0 0 4

F 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2

Unit 0 1 1 0 2 2 0 3 3 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 9

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Unit 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 2

M 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 2

F 0 0 0 0 0 0 0 5 5 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 6

Unit 0 1 1 0 0 0 1 2 3 0 0 0 0 0 0 0 0 0 2 2 4 0 0 0 8

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 4 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4

Unit 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1

Mount/Dismount TOW; by 

Squad

CASEVAC to CCP

Other No category

Falling 

behind/slowing 

movement

Requesting extra 

breaks

Requires extra 

assistance

Needs no 

assistance

Compensating 

for another 

Marine

Gear pass off

1-km Hike

7-km Hike

Negotiate Obstacle

SMAW Engagement by 

Time

Engage Target (TOW)

SMAW Engagement 

Accuracy
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Section 2. Additional Task Basic and Inferential Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. The experiment included a number of tasks and associated metrics 

conducted to enhance operational realism and maintain consistent application of the 

experimental process. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

This section presents results for 11 additional 035X tasks. Annex E contains the 

descriptive statistics for the remainder of the 035X tasks. The words “metric” and “task” 

are used interchangeably throughout this Appendix. They both refer to the experimental 

task. 

The two tables below display the results for 11 additional 035X metrics. Table E B

displays the metrics and integration levels with their respective sample sizes, means, 

standard deviations, and percent differences between integration levels.

Table E C displays ANOVA results, including metrics and integration levels, and pvalues suggesting statistical significance. For each task, an ANOVA and t-test were 

conducted to compare the two groups. If p-values are less than the a-priori determined 

significance level of 0.10, we conclude that there is statistical evidence that the 

response for the HD group is different from that in the C group. We present basic 

inferential statistics for four tasks.

Table E B – 035X Test Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD % Difference 

(HD-C)

7--km Hike; first 

km

C 19 10.85 0.49

11.25% HD 16 12.07 0.61

7-km Hike; 

second km

C 19 11.21 0.55 21.54% HD 16 13.63 1.76

7-km Hike; third 

km

C 16 11.52 1.62 21.58% HD 18 14.01 2.82

7-km Hike; 

fourth km

C 16 12.94 3.02 32.40% HD 19 17.13 3.10

7-km Hike; fifth 

km

C 19 17.60 3.39 13.99% HD 19 20.06 4.58

7-km Hike; sixth 

km

C 17 13.88 2.37

34.05% HD 20 18.61 2.78

7-km Hike; 

seventh km

C 19 15.38 2.26 33.21% HD 20 20.49 3.68

1-km Hike

C 21 8.82 0.62 17.33% HD 22 10.34 0.45

Mount Saber 

C 19 2.36 0.32

73.77% HD 20 4.10 0.76

Dismount Saber C 20 1.92 0.23 41.18%
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Metric Integration 

Level

Sample 

Size Mean SD % Difference 

(HD-C)

HD 21 2.71 0.62

TOW accuracy 

(% hit)

C 21 0.94 0.16 -4.78% HD 24 0.90 0.19

Table E C – 035X ANOVA Results and Welch’s T-Test Results

Metric

F 

statistic 

(df) 

F Test

PvalueComparison 2-sided 

P-Value 

1-sided 

P-Value 80% LCB 80% UCB 90% LCB 90% UCB

1-km 

Hike*

86.58

(1, 41) < 0.01* HD-C < 0.01* < 0.01* 1.31 1.74 1.25 1.81

Mount 

Saber* 85.60‡ < 0.01‡ HD-C < 0.01* < 0.01* 1.50 1.98 1.42 2.05

Dismount 

Saber* 30.23‡ < 0.01‡ HD-C < 0.01* < 0.01* 0.60 0.98 0.55 1.04

TOW 

Accuracy 

(% hit)

0.76

(1, 43) 0.39 HD-C 0.35† 0.18† -3.25e-5† 4.83e-5† -1.69e-5† 3.65e-5†

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test. 

†Results presented are from a Mann-Whitney non-parametric test due to non-normality.

‡Indicates results presented are from Robust ANOVA due to unequal variances. The reported F-statistic 

is a Chi-square statistic from Robust ANOVA, and the F-test p-value is the Robust ANOVA p-value.

Additional Task Results: 

7-km Hike by km. The general trend for the 7-km hike was that the difference between 

the HD and C groups increased over the course of the hike.

1-km Hike. The data are normally distributed, as evidenced by the Shapiro-Wilk Test 

that resulted in a p-value of 0.97 for the C group and 0.01 for the HD group.

The C group had a mean time of 8.82 minutes. This time is statistically significantly 

slower than the HD group mean time of 10.34 minutes. The HD group was 17.33% 

slower than the C group.

Mount Saber. The data are normally distributed, as evidenced by the Shapiro-Wilk 

Test that resulted in a p-value of 0.26 for the C group and 0.72 for the HD group.

The C group had a mean of 2.36 minutes. This time is statistically significantly slower 

than the HD group mean of 4.10 minutes. The HD group was 73.77% slower than the C 

group.

• Contextual Comments. One challenging aspect of mounting the Saber system 

is the weight of the sub-components and missile. This task affects combat 

capability during the preparation phase of a combat operation. Based on the 

standard deviations, the variation in performance of the HD group is twice as 

great as the variation in performance of the C group. This inconsistency in the 

performance of the HD group leads to greater uncertainty, as there is less 

confidence in their future performance from the mean. 
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Dismount Saber. The data are normally distributed, as evidenced by the Shapiro-Wilk 

Test that resulted in a p-value of 0.23 for the C group and 0.04 for the HD group.

The C group had a mean of 1.92 minutes. This time is statistically significantly slower 

than the HD group mean of 2.71 minutes. The HD group was 41.18% slower than the C 

group. 

• Contextual Comments. One challenging aspect of dismounting the Saber 

system is the weight of the sub-components. This task affects combat capability 

during the preparation and conduct phases of an operation. Increased time to 

complete this task during mission conduct reduces time available for the target 

engagement process and increases exposure time. Based on the standard 

deviations, the variation in performance of the HD group is twice as great as the 

variation in performance of the C group. This inconsistency in the performance 

of the HD group leads to greater uncertainty, as there is less confidence in their 

future performance from the mean.

• Lift limitations identified when lifting the sub-components of this weapon system 

pose additional anti-tank missilemen capability concerns, as it is not uncommon 

for Marines to be required to conduct a combat reload of a TOW missile from 

inside or outside a tactical vehicle. The timely execution of these transitional 

tasks is critical to the lethality of all mounted combat units, from vehicle team to 

Combined Anti-armor Team. If an inability to quickly dismount subcomponents of 

this system is related to time required to load and unload the TOW missile, 

additional combat capability may be affected.

TOW Accuracy (% hit). The data are not normally distributed, as evidenced by the 

Shapiro-Wilk Test that resulted in a p-value of <0.01 for the C and HD groups. 

The C group had a mean percent hit of 94%. This percentage is higher (but not 

statistically significantly) than the HD group mean of 90%. The HD group was 4.78% 

less accurate than the C group. 
FOR OFFICIAL USE ONLY 

Annex F. 

Provisional Infantry Rifleman (PI) 

This annex details the Provisional Infantry (PI) portion of the Ground Combat Element 

Integrated Task Force (GCEITF) experiment executed 2 March – 26 April 2015 at 

Range 107 and Range 110, aboard the Marine Corps Air Ground Combat Center

(MCAGCC), Twentynine Palms, CA. The sections outline the PI Scheme of Maneuver

(SOM), Limitations, Deviations, Data Set Description, Descriptive and Basic Inferential 

Statistics, Subjective Comments, and Modeling Results. 

F.1 Scheme of Maneuver

F.1.1 Experimental Cycle Overview

The PI assessment of the GCEITF took place in a field environment aboard MCAGCC, 

Twentynine Palms, CA. The assessment consisted of 21 trial cycles, each of which was 

a 2-day test cycle, conducted over the course of 55 days. After every 4 days of trials, 

the Marines received 1 recovery day spent at Camp Wilson. Each squad consisted of 

12 volunteers and a direct assignment (non-volunteer) squad leader. Each member of 

the squad was trained to fill each billet within the fireteam: fireteam leader, grenadier, 

automatic rifleman, and rifleman. The rifle squad contained three fireteams. The 

assessment was executed under the supervision of MCOTEA functional test managers 

and a range officer in charge (OIC)/range safety officer (RSO) from the GCEITF. 

F.1.2 Experimental Details

The 2-day PI assessment was modeled to replicate defensive and offensive tasks. The 

PI conducted defensive tasks on Day 1 and offensive tasks on Day 2. Three PI squads 

executed each trial cycle: a control (C) non-integrated squad, a low-density (LD) 

gender-integrated squad with two females, and a high-density (HD) gender-integrated 

squad with four or five females. 

Day 1 of the PI trial cycle was executed on Range 110 and consisted of defensive 

actions. The day started with a 7-km forced march from Range 107 to Range 110, for

which Marines were wearing an approach load and carrying personal weapons. After a 

10-minute operational pause, each fireteam spent 2 hours digging two-man fighting 

positions wearing a fighting load. Two Marines from each fireteam provided security 

while the other two dug, rotating every 15 minutes. 

Day 2 of the PI trial cycle was executed on Range 107 and consisted of a squadreinforced attack. Each squad moved approximately 1 km to an assault position 

wearing an assault load and carrying personal weapons. As a squad, they moved all 

personnel and gear over an 8-ft obstacle/wall. After negotiating the obstacle, the squad 
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staged its assault packs, deployed on-line, and conducted a 425-m live-fire assault to a 

limit of advance wearing the fighting load. They immediately repelled an enemy 

counterattack by fire for 90 seconds. Finally, each fireteam conducted a 100-m casualty 

evacuation (CASEVAC) of a 220-lb. At the conclusion of Day 2, the composition of the 

squad was dissolved and a new sample of males and females were randomly assigned 

for the following cycle. 

F.1.3 Additional Context

Throughout the duration of the assessment, Marines bivouacked at Range 107, 

sleeping in two-man tents. Prior to the Day 2 trial, each Marine zeroed his or her 

weapon system to maximize accuracy. During trial execution, Marines wore/carried 

prescribed loads for each task. Packs were weighed each day prior to the 7-km forced 

march to ensure consistency. After each trial day, the Marines operated under the 

guidance of their Company leadership, performing minimal physically demanding tasks. 

Not all Marines were selected for each trial cycle. Those Marines who were not part of 

an assessed squad conducted the same experimental subtasks to ensure equity in 

physical loading between individuals participating in a trial cycle and those not chosen 

via random selection for that particular cycle. A detailed discussion of these tasks is in 

the Loading Plan section below.

Fatigue surveys were designed to capture the volunteers’ cumulative fatigue level at the 

beginning and end of each day’s trials. The data collected provide additional insight into 

apparent aberrations in the performance level of a given volunteer on a specific day. 

Outside fatigue-related factors (minor illness, lack of sleep the night before, etc.) are

accounted for in the analysis of the performance data. Workload surveys collected the 

volunteers’ perceived average and maximal level of exertion during the performance of 

specified tasks. Cohesion surveys provided a method of collecting subjective data 

relating to each squad’s ability to work as a team and their overall perspective on the 

cohesiveness of the squad.

F.1.4 Experimental Tasks

F.1.4.1 7-km Hike

Moving under a load is one of the most fundamental tasks of an infantry unit; it is both 

physically and mentally demanding. Units train by conducting tactical marches with an 

approach load at increasing distances. The Infantry Training and Readiness (T&R) 

Manual states that “the approach march load will be such that the average infantry 

Marine will be able to conduct a 20 mile hike in 8-hours with the reasonable expectation 

of maintaining 90% combat effectiveness.” During the GCEITF assessment, each PI

squad moved a distance of 7.20 km, from Range 107 to Range 110. This route was flat 

(minimal elevation change) and conducted on an unimproved surface with varying 

degrees of conditions (compact dirt and loose sand). The squads moved as fast as the 
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slowest person, carrying an approach load and an individual weapon. The individual 

weapons included the M-4, the M-16A4 with M203 attachment, and the M27, resulting in 

a cumulative load of 96 – 101 lb per Marine. The primary purpose of this task was to 

determine the squad’s pace over a 7.20-km route while carrying the approach load. 

Each Marine took a fatigue and workload survey after completion of the 7.20-km hike 

(see GCEITF Experimental Assessment Plan [EAP], Annex D). 

F.1.4.2 Digging Fighting Holes

Protection is vital to infantry units, especially in a defensive posture. Infantry units 

commonly construct fighting positions to conceal positions and minimize exposure to 

enemy fire. The most physically demanding aspect of constructing a doctrinal fighting 

position is digging out the fighting hole. The terrain at Twentynine Palms consisted of 

hard, compact sand and rocks. Each fireteam dug 2 two-man fighting holes in a time 

limit of 2 hours, maintaining 50% security, meaning that two Marines dug while two 

provided security in the prone position. The Marines swapped positions every 15 

minutes. The purpose of this task was to determine the fireteam’s rate of work while 

digging fighting positions. After 2 hours, each Marine took a fatigue and workload 

survey (see GCEITF EAP, Annex D). 

F.1.4.3 1-km Movement 

Assaulting an enemy position never starts from a static position; first, a movement must 

be conducted to the assault position (AP). The distance from the line of departure to 

the AP is dependent upon myriad factors. Based on time and space constraints during 

the GCEITF assessment, this distance was a little less than 1 km. Each PI squad 

moved this distance as quickly as possible while carrying an assault load and individual 

weapon. The Infantry T&R Manual states that “the assault load is the load that is 

needed during the actual conduct of the assault.” This task caused moderate fatigue for 

the Marines prior to commencing the attack. 

F.1.4.4 Negotiate an Obstacle

The conduct of an attack often involves reducing or negotiating an obstacle. It is 

common in an urban environment to enter through a window or over a wall (obstacle). 

One of the more difficult tasks is climbing over a wall with a fighting load. Each squad 

negotiated an 8-ft wall by getting all Marines and equipment over as quickly as possible. 

Although the technique was not dictated, the PI squads used three launch-points (one 

per fireteam) from which to lift Marines up onto the wall. 

F.1.4.5 Squad Attack

The mission of the rifle squad is “to locate, close-with, and destroy the enemy by fire 

and maneuver, and repel the enemy’s assault by fire and close combat.” Conducting a 

live fire-and-movement task is fundamental to the infantry community and operationally
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relevant. Having moved to an AP, each PI squad deployed into an on-line formation to 

maximize firepower in the direction of the enemy and then began movement-to-contact 

with weapons at the ready. Upon contact with the enemy (targets being presented), the 

Marines laid down a heavy volume of fire to gain fire superiority. They then began 

buddy rushes to close with the enemy objective. Each squad conducted approximately 

300 m of buddy rushes, engaging a total of twelve GCEITF Targeting Systems (GTSs) 

with direct-fire weapons and three machinegun bunkers with the M16A4 with M203 

grenade launcher. After all targets were destroyed (no targets remaining), the squad 

moved another 125 m to a limit of advance (LOA) and prepared for an enemy 

counterattack. This task is physically demanding and involves a combination of 

accuracy, tempo, and squad cohesion. 

F.1.4.6 Repel Counterattack

At the conclusion of every assault, the attacking unit must be prepared for the enemy to 

regroup and organize a counterattack. Upon consolidation at the LOA, the PI squad

oriented its weapons in the direction of the enemy’s retreat. Upon target presentation, 

the counterattack commenced. It continued for 90 seconds. Six GTSs were used during 

the course of the counterattack. The primary purpose of this task was to determine the 

PI squad’s accuracy engaging targets approximately 300 m away after conducting an 

offensive squad attack. 

F.1.4.7 CASEVAC

Casualties are an inevitable part of conducting combat operations. Units train to 

become proficient in triaging, handling, and transporting a casualty. After a Marine is 

injured, it is essential to move the casualty to the appropriate level of care as quickly as 

possible. During the GCEITF assessment, each PI fireteam was assigned a casualty at 

the conclusion of the live-fire attack and counterattack. Each fireteam had to move a 

220-lb casualty (dummy and equipment) a distance of 100 meters to a casualty 

collection point (CCP). The team could use a variety of techniques for transport, but 

had to carry the dummy off the ground (not drag any part). The primary purpose of this 

task was to determine the fireteam’s proficiency at moving a simulated casualty to a 

CCP. After the CASEVAC, each Marine took a fatigue and workload survey to assess 

overall fatigue and workload of the entire offensive task (see GCEITF EAP, Annex D). 

At the completion of the 2-day cycle, Marines also took a cohesion survey to record 

cohesion during the execution of the 2-day trial cycle (See GCEITF EAP, Annex M). 

F.1.5 Loading Plan 

Due to the number of volunteers, a handful of Marines were not part of an assessed 

squad for each 2-day cycle. The primary purpose of the loading plan was to ensure, to 

the greatest extent possible, equity of physical activity among all volunteers throughout 
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the duration of the experimental assessment. Every trial and task was conducted in the 

same manner and sequence to ensure consistency. Collaboration with the Company 

leadership determined that the best method of loading non-assessed Marines was to 

have them perform the same tasks as an assessed PI squad so that they would 

experience the same conditions and physical strain. Every trial and task was conducted 

in the same manner and sequence to ensure consistency. 

F.1.5.1 Variations

A variety of factors, including safety and the number of loading Marines, introduced 

variations to the loading plan. 

• In some instances, the loading Marines formed a quasi-squad and conducted the 

trial after all assessed PI squads were done for the day. At other times, the 

quasi-squad was too small, so the loading Marines were attached to an assessed 

squad, in which case they operated on the flanks and were not given 

ammunition. At no point in time did a loading Marine aid or interfere with an 

assessed PI Marine/squad. 

• The loading Marines did not always dig for 2 hours. To gain efficiencies, the 

loading Marines would rotate between digging, assisting in weighing buckets of 

sand, and refilling the holes of the assessed squads. Any such variation was 

carefully calculated to ensure that loading Marines were doing an amount of work 

equivalent to that of the assessed Marines. 

F.1.6 Scheme of Maneuver Summary

The PI experiment consisted of a 2-day trial cycle comprising a defensive and an 

offensive day. The defensive day involved two subtasks: 7-km forced march and 

digging a fighting position. The offensive day involved five subtasks based around a 

squad live-fire attack: 1-km movement, negotiating an obstacle, fire and movement, 

counterattack, and CASEVAC. During the course of the experiment, the PI squad 

executed 2 pilot trial cycles and 21 record trial cycles. During trial execution, Marines 

rotated through every billet within the rifle squad, carrying the respective weapon 

system. 

F.2 Limitations 

F.2.1 Limitations Overview

The GCEITF experiment was designed to allow operationally relevant tasks to occur as 

naturally as possible, while gathering unbiased measurements. Most tasks were 

performed in a similar manner to those in an operational environment. However, under 

certain situations, artificial limitations or interruptions were introduced that changed or 

altered the way a task would normally be performed. While these limitations represent 
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a degree of artificiality, they do not detract significantly from our abilities to generalize 

the conclusions of this experiment to the performance of Marines in a field environment. 

The following limitations were observed for the PI assessment. 

F.2.2 Relative Difficulty of Record Test

The PI GCEITF assessment was designed to gather data associated with some of the 

most physically demanding tasks that an open MOS Marine could perform when 

assigned to an Infantry unit with collateral responsibilities as a rifleman. However, these 

tasks in isolation did not fully replicate life experienced by a Marine during a typical field 

exercise (FEX) or in a combat environment and did not obtain the maximum cumulative 

load that could be placed on a Marine assigned to a ground combat element. With

limited time available, only selected PI tasks were assessed. Other tasks/duties outside 

of the assessment were minimized due to specific experimental constraints and human 

factors. During a typical FEX, it is common for Marines to conduct 24-hour operations 

that include performing daytime and nighttime operations/patrols, standing firewatch or 

a security post, and conducting continuing tactical actions. It took PI squads 

approximately 4 hours to complete the defensive day and approximately 1 hour to 

complete the offensive day. Outside the assessed trials, there were minimal tasks 

required of the volunteers that demanded any degree of physical strain. 

Another concern in designing the PI assessment was to ensure that it was achievable 

and sustainable for a 60-day period. The 7-km forced march distance was selected 

based on the training time available prior to the assessment. However, many of the 

loads carried were decreased. Once they were over the wall/obstacle, the provisional 

infantrymen staged their assault packs without security rather than wearing them during 

the fire-and-movement. The provisional infantrymen also did not carry ammunition, 

radios, batteries, or other equipment often required when operating in a tactical 

environment. The Marines were authorized 1 day off after every 4 days of training; this 

artificial recovery period is not achievable when conducting training or combat 

operations. 

A final factor affecting the relative difficulty of the record test pertains to the intangible 

physiological impact of the volunteers’ ability to drop on request (DOR) at any point 

during a trial. Any time a volunteer dropped during a trial cycle, that PI squad

performed the following subtasks with fewer personnel. This factor affected the 

cohesion of each squad and influenced its performance. 

F.2.3 Digging a Fighting Position

Several artificialities were present as the volunteers dug their fighting holes. Preparing 

a defensive fighting position involves many continuing actions by those not actually 

digging the hole, such as clearing fields of fire and creating sectors of fire. However, no 

continuing defensive actions were conducted other than lying in the prone position and 
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providing notional security. The Marines digging did not have to fill up a 5-gallon bucket 

for measurement; they either filled sandbags or built up a parapet. These artificialities 

may have influenced their performance and morale.

F.2.4 Number of Volunteer Participants

A total of 33 male and 8 female volunteers began the experiment; of those, 29 males 

and 6 females completed the assessment. The results presented in this annex are 

based on the performance of 35 – 41 Marines. For population analysis (by gender and 

MOS), which examines the volunteer population and the overall Marine Corps 

population, see Population Analysis Annex Q. 

F.2.5 Limitations Summary

The PI assessment was designed to replicate realistic training in a field environment. 

The end-state was to create an experiment in which the volunteers felt they were 

conducting realistic and operationally relevant tasks, but unavoidable limitations to the 

assessed tasks and non-assessed operating environment introduced a level of 

artificiality not normally present in a field training or combat environment. 

F.3 Deviations 

F.3.1 Concentration for the Provisional Rifle Squad

Marines participated in this experiment voluntarily and could leave the experiment at 

any time, for any reason, making the total number of human subjects available highly 

volatile. Trials were not executed if there were not enough participants to carry out the 

assigned mission, and attrition affected the integration levels for the PI experiment. The 

EAP stated that the PI Rifle Squad would have three levels of integration: a C group, an 

LD group, and an HD group, with zero females, two females, and four females, 

respectively. Due to the low number of male volunteers, the MCOTEA research team 

had to add a female to the high-density group for some trials, resulting in the final highdensity integration level being either four or five females.

F.4 Data Set Description 

F.4.1 Data Set Overview

The PI portion of the experiment consisted of 2 pilot trial cycles and 21 record trial

cycles. The pilot trial cycles were conducted 2 March – 6 March 2015. Pilot trial cycle

data are not used in analysis, due to variations in the conduct of the test. We based all 

analysis on the 21 record trial cycles executed 7 March – 26 April 2015.
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F.4.2 Record Test Volunteer Participants

At the beginning of the first record trial cycle, there were 33 male PI volunteers and 8 

female volunteers. Several of those voluntarily withdrew, or were involuntarily 

withdrawn, during the execution of the experiment. The final number of volunteers was 

29 males and 6 females.

F.4.3 Planned, Executed and Analyzed Trial Cycles

Table F-1 displays the number of trial cycles planned, executed, and analyzed by task. 

The planned number of trial cycles for the PI MOS per Section 7.5.3 of GCEITF EAP 

was 78 trials, or 26 trials per planned integration level (C, LD, and HD). Due to the 

change in trial execution, only 21 trial cycles could be executed. The planned number 

of trial cycles in Table F-1 reflects the 21 planned trial cycles for each integration level. 

Of note, there are several occurrences of missing data for the 7-km hike by individual 

kilometer. The individual kilometer times were derived from GPS data. Early in the 

experiment, the Garmin GPSs were set to record a volunteer’s position every second. 

Due to the storage space on the GPS and length of the trial when volunteers executed 

the 7-km hike and then 2 hours of preparing a fighting position, the GPS could not hold 

all of the data. Therefore, it overwrote the hike data. Once the problem was found, the 

GPSs were corrected to record location every 2 seconds. 

Table F-1. PI Planned, Executed, and Analyzed Trial Cycles

Task and 

Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

Trials 

Conducted

Number of 

Trials Used in 

Analysis

Notes

7-km Hike

C 21 21 21

LD 21 18 18

HD 21 18 18

Movement to 

LOA

C 21 21 19 Missing TRACR 12 Apr (data problem); 18 

Mar controller

LD 21 18 16 Missing TRACR 12 Apr (data problem); 18 

Mar controller

HD 21 18 16 Missing TRACR 12 Apr (data problem); 18 

Mar controller

Attack & CAtk Percent 

Hits

C 21 21 19 Missing TRACR 12 Apr (data problem), 24 

Apr

LD 21 18 17 Missing TRACR 12 Apr (data problem)

HD 21 18 16 Missing TRACR 13 Mar, TRACR 12 Apr (data 

problem)

CASEVAC by 

FT

C 105 96 96

LD 42 41 41 Partial trial 20 Mar

HD 42 36 34 No 15 Mar (2 HD FTs)

Prepare 

Fighting 

Positions by 

FT

C 105 96 95 27 Mar missing data

LD 42 43 43

HD 42 36 34 No 14 Mar (2 HD FTs)

1-km Hike

C 21 21 21

LD 21 18 18

HD 21 18 18

Negotiate C 21 21 20 2 Apr high outlier
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Task and 

Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

Trials 

Conducted

Number of 

Trials Used in 

Analysis

Notes

Obstacle LD 21 18 18

HD 21 18 17 12 Apr high outlier

7-km Hike; 

1km Time

C 21 21 17 No data: 7 Mar, 9 Mar, 12 Mar, 14 Mar

LD 21 18 15 No data: 7 Mar, 9 Mar, 12 Mar

HD 21 18 16 No data: 7 Mar, 12 Mar

7-km Hike; 

2km Time

C 21 21 17 No data: 7 Mar, 9 Mar, 12 Mar, 14 Mar

LD 21 18 15 No data: 7 Mar, 9 Mar, 12 Mar

HD 21 18 16 No data: 7 Mar, 12 Mar

7-km Hike; 

3km Time

C 21 21 17 No data: 7 Mar, 9 Mar, 12 Mar, 14 Mar

LD 21 18 15 No data: 7 Mar, 9 Mar, 12 Mar

HD 21 18 16 No data: 7 Mar, 12 Mar

7-km Hike; 

4km Time

C 21 21 17 No data: 7 Mar, 9 Mar, 12 Mar, 14 Mar

LD 21 18 15 No data: 7 Mar, 9 Mar, 12 Mar

HD 21 18 16 No data: 7 Mar, 12 Mar

7-km Hike; 

5km Time

C 21 21 17 No data: 7 Mar, 9 Mar, 12 Mar, 14 Mar

LD 21 18 14 No data: 7 Mar, 9 Mar, 12 Mar; 8 Apr high 

outlier

HD 21 18 16 No data: 7 Mar, 12 Mar

7-km Hike; 

6km Time

C 21 21 17 No data: 7 Mar, 9 Mar, 12 Mar, 14 Mar

LD 21 18 15 No data: 7 Mar, 9 Mar, 12 Mar

HD 21 18 15 No data: 7 Mar, 12 Mar; 23 Apr high outlier

7-km Hike; 

7km Time

C 21 21 18 No data: 7 Mar, 12 Mar, 14 Mar

LD 21 18 15 No data: 7 Mar, 9 Mar, 12 Mar

HD 21 18 16 No data: 7 Mar, 12 Mar

F.5 Descriptive and Basic Inferential Statistics 

F.5.1 Descriptive Statistics Overview

Performance metrics were measured during the conduct of common infantry tasks and 

are indicative of unit-level proficiency during either field exercises or combat operations. 

This section presents results for 7 out of 16 tasks. The PI Appendix contains the 

descriptive statistics for the remainder of the PI tasks. The words “metric” and “task” 

are used interchangeably throughout this Annex. They both refer to the experimental 

task. 

Each fireteam consisted of four volunteer Marines: the fireteam leader, automatic 

rifleman, grenadier, and rifleman. Each squad consisted of 12 volunteer Marines (three 

fireteams) with a direct assignment (non-volunteer) squad leader. There were three

integration levels for all tasks. For squad-level tasks, a C group was non gender

integrated, an LD was gender integrated with two female Marines, and an HD group 

was gender integrated with four or five female Marines. For fireteam-level tasks, a C 

group was non gender integrated, an LD group was gender integrated with one female 

Marine, and an HD group contained at least two, but not more than three, females.

This section includes experimental results based on descriptive statistics, analysis of 

variance (ANOVA), Tukey Tests (or non-parametric tests as necessary), and scatter 

plots. The subsequent sections will cover each task in detail. Lastly, contextual 
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comments, additional insights, and subjective comments (as applicable) tying back to 

each experimental task are incorporated.

Caution must be used when comparing similar tasks executed by different MOSs within 

the GCEITF experiment. Comparative analysis may be misleading due to differing 

factors between MOS tasks, such as distances, techniques, leadership, load carried, 

group size, and group composition.

F.5.2 PI Selected Task Descriptive Statistics Results

The two tables below display the results for the seven selected PI metrics. Table F-2

displays the metrics and integration levels with their respective sample sizes, means, 

and standard deviations. Table F-3 displays ANOVA and Tukey Test results, including 

metrics and integration levels, p-values suggesting statistical significance, elapsed-time 

differences between the integration levels, and percentage differences between 

integration levels. For each task, an ANOVA was conducted to compare the three 

groups and Tukey Tests were conducted to compare each pair of two groups. In cases 

where non-parametric tests were needed, Table F-3 displays these results instead of 

ANOVA and Tukey Test results. If p-values are less than the a-priori determined 

significance level of 0.10, we conclude that there is statistical evidence that the result

was not found to be the same across all three groups.

Table F-2. PI Selected Task Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD

7-km Hike (minutes)*

C 21 82.75 4.75

LD 18 90.76 6.71

HD 18 91.05 3.85

Movement to LOA (minutes)† 

C 19 3.01 0.44

LD 16 3.22 0.36

HD 16 3.37 0.43

Attack & C-Atk Percent Hits (%)

C 19 0.39 0.05

LD 17 0.37 0.04

HD 16 0.36 0.07

CASEVAC by FT (minutes)* 

C 96 1.31 0.34

LD 41 1.57 0.34

HD 34 1.63 0.42

Prepare Fighting Positions by 

FT (lbs.)

C 95 5146.13 963.27

LD 43 5257.46 1078.25

HD 34 5184.84 1097.58

1-km Hike (minutes)*

C 21 8.87 0.58

LD 18 9.55 0.56

HD 18 9.37 0.44

Negotiate Obstacle (minutes)* C 20 1.75 0.19
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Metric Integration 

Level

Sample 

Size Mean SD

LD 18 1.78 0.24

HD 17 2.13 0.34

*Indicates that there is a statistically significant difference in a two-sided 

hypothesis test between integration levels according to ANOVA and those 

according to a non-parametric equivalent test.

†Indicates that there are contradicting statistical significance results between 

ANOVA and a non-parametric equivalent test.

Table F-3. PI Selected Task ANOVA and Tukey Test Results

Metric

F 

statistic 

(df) 

F Test

PvalueComparison Difference % 

Difference

2-

sided 

PValue

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

7-km Hike 

(minutes)* 

16.23

(2, 54) < 0.01*

LD-C 8.01 9.68% < 0.01* 5.10 10.92 4.50 11.52

HD-C 8.30 10.03% < 0.01* 5.39 11.22 4.79 11.82

HD-LD 0.29 0.32% 0.98 -2.73 3.32 -3.35 3.94

Movement to 

LOA 

(minutes)* 

3.39

(2, 48) 0.76†

LD-C 0.22 7.15% 0.04† 0.15† 0.37† 0.08† 0.40†

HD-C 0.36 12.00% 0.01† 0.23† 0.55† 0.02† 0.60†

HD-LD 0.15 4.52% 0.16† 0.00† 0.28† -0.02† 0.37†

Attack & C-Atk 

Percent Hits 

(%) 

2.25

(2, 49) 0.12

LD-C -0.03 -6.62% 0.33 -0.06 0.01 -0.06 0.01

HD-C -0.04 -9.63% 0.11 -0.07 -0.01 -0.08 0.00

HD-LD -0.01 -3.23% 0.81 -0.05 0.02 -0.05 0.03

CASEVAC by 

FT (minutes)*

14.56

(2, 168) < 0.01*

LD-C 0.26 20.12% < 0.01* 0.15 0.38 0.13 0.40

HD-C 0.33 24.88% < 0.01* 0.20 0.45 0.18 0.47

HD-LD 0.06 3.97% 0.73 -0.08 0.20 -0.11 0.23

Prepare 

Fighting 

Positions

(lbs.) 

0.18

(2, 169) 0.84

LD-C 111.33 2.16% 0.82 -211.46 434.13 -276.03 498.70

HD-C 38.71 0.75% 0.98 -312.26 389.68 -382.47 459.89

HD-LD -72.62 -1.38% 0.95 -475.67 330.42 -556.29 411.04

1-km Hike 

(minutes)* 

8.634

(2, 54) 0.58†

LD-C 0.68 7.65% < 0.01† 0.38† 0.78† 0.35† 0.85†

HD-C 0.50 5.66% <0.01† 0.32† 0.67† 0.27† 0.73†

HD-LD -0.18 -1.85% 0.73† -0.25† 0.12† -0.30† 0.17†

Negotiate 

Obstacle 

(minutes)*

11.51

(2, 52) < 0.01*

LD-C 0.03 1.88% 0.92 -0.12 0.18 -0.15 0.21

HD-C 0.38 21.80% < 0.01* 0.23 0.53 0.20 0.56

HD-LD 0.35 19.55% < 0.01* 0.19 0.50 0.16 0.53

*Indicates that there is a statistically significant difference in a two-sided hypothesis test between 

integration levels according to ANOVA and those according to a non-parametric equivalent test. 

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given 

confidence level on its own. 

†Results presented are from a Kruskal-Wallis and Mann-Whitney non-parametric tests due to nonnormality.
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F.5.2.1 7-km Hike 

F.5.2.1.1 7-km Hike Overview

This experimental task assessed a squad of 12 Marines moving 7.20 km while each 

Marine carried an approach load and an individual weapon. The individual weapons 

included the M-4, the M-16A4 with M203 attachment, and the M27, resulting in a 

cumulative load of 96 – 101 lb per Marine. The recorded time for this task started when 

the squad departed the Range 107 start point and stopped when the squad arrived at 

the Range 110 stop point. Each squad moved as fast as the slowest person and could 

take as many breaks as necessary. 

Figure F-1 displays all PI 7-km hike data. All data on the scatter plot are valid for 

analysis.

Figure F-1. 7-km Hike

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

p-values of 0.06 for the C group, 0.24 for the LD group, and 0.28 for the HD group.

The C group had a mean time of 82.75 minutes. This is statistically significantly faster 

than the LD mean time of 90.76 minutes and the HD mean time of 91.05 minutes. 

These differences result in 9.68% (8.01-minute) and 10.03% (8.30-minute) degradations 

in time for the LD and HD groups, respectively. Additionally, the LD group had greater 

variability as shown by the 1.96-minute increase in standard deviation (SD), and the HD 

had less variability as shown by the 0.90-minute decrease in SD (4.75 minutes for the C 

group, 6.71 minutes for the LD group, and 3.85 minutes for the HD group). The LD 

group was faster than the HD group. There was a 0.32% (0.29-minute) degradation in 

hike time from the LD to HD group, but this difference is not statistically significant. See 

Table F-2 and Table F-3 for detailed analytical results.
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F.5.2.1.2 7-km Hike Contextual Comments

F.5.2.1.2.1 USMC Hike Standards

The 7-km hike is a task that the following MOSs completed during the experiment: 

0311, 0331, 0341, 0351 and 0352, PI, Provisional Machine Gunners, and Combat 

Engineers. There are varying standards to which we can compare this result. The 

following sections define those standards, as well as the one we chose as a 

comparison.

The Infantry T&R Manual (30 Aug 2013) identifies minimum standards that Marines 

must be able to perform in combat, to include standards for tactical marches. In 

Chapter 8 of the Infantry T&R Manual in the MOS 0300 Individual Events section, task 

“0300-COND-1001: March under an approach load” is applicable to all 03XX MOSs, 

ranks Pvt – LtCol. The condition and standard established by this task is: “Given an 

assignment as a member of a squad, individual weapon, and an approach load, 

complete a 20 kilometer march in under 5 hours.” The march pace required by this 

standard is 4 kilometers per hour (km/h). In Chapter 9 of the Infantry T&R Manual in the 

MOS 0302/0369 Individual Events section, tasks “0302-OPS-2001: Lead an approach 

march” and “0369-OPS-2501: Lead an approach march” are applicable to MOS 0302 

and 0369, ranks SSgt – MGySgt and 2ndLt – LtCol. The condition and standard 

established by these tasks is: “Given a mission, time constraints, an approach march 

load, organic weapons, and a route, move 24.8 miles (40 km) in a time limit of 8 hours.” 

The march pace required by this standard is 5 km/h. Appendix E of the Infantry T&R 

Manual (Load Terms and Definitions) states: “The approach march load will be such 

that the average infantry Marine will be able to conduct a 20 mile hike in 8-hours with 

the reasonable expectation of maintaining 90% combat effectiveness.” The march pace 

required by this definition is 4.02 km/h.

Chapter 3 of Fleet Marine Force Reference Publication (FMFRP) 3-02A, Marine 

Physical Readiness Training for Combat (16 Jun 2004), states: “The normal pace is 30 

inches. A pace of 30 inches and a cadence of 106 steps per minute result in a speed of 

4.8 km/h or 3 mi/h and a rate of 4 km/h or 2.5 mi/h if a 10-minute rest halt per hour is 

taken.” Common Infantry practice today is to hike for 50 minutes and take a 10-minute 

break, while maintaining an overall pace of 4 km/h (resulting in a hiking pace of 4.8 

km/h). 

Driven by the need to pick an evaluative reference standard, this report follows the T&R 

Manual’s intent to establish minimum standards and uses the 4-km/h march pace for a 

20-km march established by task 0300-COND-1001 and supported by the definition of 

an approach load. Further, while an established reference standard is required to 

anchor observed performance to the T&R program, more important information is 

provided by performance differences observed between gender-integrated and nongender-integrated units.
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F.5.2.1.2.2 PI 7-km Hike Pace

This result is relevant to both the training and combat environments as it will take 

integrated squads more time to conduct foot marches. Per the tactical march standards 

referenced above, the Marine Corps standard of hiking is 4.0 km/h. All integration 

levels surpassed this standard. The C group’s average pace was 5.22 km/h, while the 

LD and HD groups’ average paces were 4.76 km/h and 4.74 km/h, respectively. 

Assuming that these paces could be maintained for a 20-km task (an optimistic 

assumption that does not account for any further degradation of performance), the HD 

and LD groups would be approximately 23 minutes behind the C group at the finish. 

Finally, on any given day (under the same environmental conditions), the C group was 

faster than the HD group 94.4% of the time (17 of 18 trial cycles). The C group was 

faster than the LD group 88.9% of the time (16 of 18 trial cycles). The HD group was 

faster than the LD group 60% of the time (9 of 15 trial cycles).

F.5.2.1.3 7-km Hike Additional Insights

The difference in the 7-km hike time and speed was statistically significant, and the size 

of the difference has some intuitive significance. Common Infantry practice today is to 

hike for 50 minutes and take a 10-minute break, while maintaining an overall pace of 4 

km/h (resulting in a hiking pace of 4.8 km/h). Given a 4.8 km/h rate of march, the LD 

and HD failed to maintain that pace. 

A purely objective evaluation of 0.45 – 0.46 km/h decrease in pace is elusive, but 

Marine Corps Doctrinal Publications (MCDPs) consistently emphasize the importance of 

speed. MCDP 1-3 Tactics devotes an entire chapter to “Being Faster” and states, 

“Physical speed, moving more miles per hour, is a powerful weapon in itself.” MCDP-6 

Command and Control also speaks to speed relative to the enemy and states, “The 

speed differential does not necessarily have to be a large one: a small advantage 

exploited repeatedly can quickly lead to decisive results.” The difference observed 

between the C and HD or LD groups was over 8 minutes. For an indication of 

performance when the load is increased, see the 0331, 0341, and 035X 7-km hike data 

and contextual comments.

F.5.2.1.4 7-km Hike Subjective Comments

The subjective leadership comments reveal that the majority of the Marines responsible 

for falling behind and slowing the movement within integrated groups were female 

Marines. There were 32 comments about males slowing the movement within C 

groups. For slowing movement within the LD group, 13 comments related to females 

and 8 comments related to males. For slowing movement within the HD groups, 27 

comments related to females, while only 2 comments related to males. It was observed 

that as the integration level increased, the more frequently female Marines were 

responsible for a degradation in performance.
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For additional subjective comments relating to this task, see the Appendix. 

F.5.2.2 Movement to LOA

F.5.2.2.1 Movement to LOA Overview

This experimental task assessed a squad moving approximately 125 meters to an LOA 

immediately after conducting a fire-and-movement assault. The recorded time started 

when the last target went down after the assault and stopped when the last member of 

the squad was prone at the LOA.

Figure F-2 displays all PI Movement to LOA time data. On trial cycle 5, data for the C, 

LD, and HD groups were removed from the analysis due to data collection errors; data 

omitted from the analysis are circled in black. With the exception of the trial cycle 5 

data points, all data on the scatter plot are valid for analysis.

Figure F-2. Movement to LOA

The data for the C and HD groups are normally distributed as evidenced by the ShapiroWilk Test that resulted in p-values of 0.06 and 0.51, respectively, but they are not 

normally distributed for the LD group, which had a p-value of < 0.01.

The C group had a mean of 3.01 minutes; the LD, 3.22 minutes; and the HD, 3.37

minutes. These differences result in 7.15% (0.22-minute) and 12.00% (0.36-minute) 

degradations in time for the LD and HD groups, respectively. The LD group was faster 

than the HD group. There was a 4.52% (0.15-minute) degradation in movement time 

from the LD to HD group. 

The difference in movement to LOA time was not statistically significant between the LD 

and HD groups in a two-sided Mann-Whitney Test but was statistically significant in a 

one-sided Mann-Whitney Test. The difference in movement to LOA time was 
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statistically significant between the LD and C groups as well as the HD and C groups in 

a Mann-Whitney Test. The difference in movement to LOA time was not statistically 

significant for the LD and C groups in a Tukey Test. Because of a lack of normality, we 

recommend using the Mann-Whitney test results (reported in Table F-3). 

The near significance (between the LD and HD groups) of the non-parametric results 

suggests that further study of this task is warranted. See Table F-2 and Table F-3 for 

detailed analytical results.

F.5.2.2.2 Movement to LOA Contextual Comments 

The ability to close with the objective after having conducted a live-fire attack is a crucial 

aspect of maintaining the momentum during offensive operations. In this case, the LD 

squads were exposed to the enemy 13.20 seconds (7.15%) longer and HD squads 

were exposed to the enemy 21.60 seconds (12.00%) longer than the C group squads. 

This longer exposure means that these squads have that much less time to prepare for 

a counterattack or conduct follow-on actions. On any given day (under the same 

environmental conditions), the C group was faster than the LD group 58.8% of the time 

(10 out of 17 trial cycles) and faster than the HD group 76.5% of the time (13 out of 17

trial cycles). On any given day, the LD group was faster than the HD group 69.2% of 

the time (9 out of 13 trial cycles), while they finished in the same amount of time for one 

trial.

F.5.2.2.3 Movement to LOA Additional Insights

A purely objective evaluation of 13.20 or 21.60 seconds is elusive, while the previous 

citations emphasizing the importance of speed still apply (see Section F.5.2.1.3). 

However, the performance decrement in this task is approximately 7% or 12% 

(depending on type of integrated squad) and may possess some practical significance 

on the battlefield that would reduce the survivability of an integrated squad. 

Considering the 12 – 15 rounds-per-minute sustained rate of fire for both the M4 and 

AK-47 rifles, a single enemy fighter would have the opportunity of two to three more 

well-aimed shots on Marines in an integrated squad moving to the limit of advance. 

Similarly, the delay degrades our own pursuit of the enemy by fire, denying our slowest 

Marines two to three well-aimed engagements on the enemy from a fixed position at the 

LOA. The resultant trade in casualty exchange could be significant. 

F.5.2.2.4 Movement to LOA Subjective Comments

The subjective leadership comments reveal that the majority of the Marines displaying 

fatigue within integrated groups were female Marines. There were 54 comments about 

males slowing the movement within C groups. Of the 62 comments related to Marines 

showing fatigue within the LD group, 35 related to females and 27 related to males. Of 

the 61 comments related to Marines showing fatigue within the HD group, 44 related to 
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females, while only 17 related to males. We observe that as the integration level 

increased, female Marines were increasingly responsible for degradation in 

performance.

For additional subjective comments relating to this task, see the Appendix.

F.5.2.3 Attack & Counterattack (C-Atk) Percent Hit 

F.5.2.3.1 Attack & C-Atk Overview 

This experimental task assessed the accuracy of a rifle squad engaging 12 GTSs during 

a 300-meter fire-and-movement assault. Each GTS captured the precise location of a 

round that impacted a target silhouette using a location of hit and miss (LOMAH) 

sensor. The GTSs were equally spread out over the downrange area at varying 

distances and were exposed according to pre-determined parameters that were 

consistent for every squad attack. The accuracy was determined by dividing the 

number of hits on each target by the total amount of ammunition expended by each 

squad. 

Figure F-3 displays all Attack & C-Atk Percent Hit data. All data on the scatter plot are 

valid for analysis.

Figure F-3. Attack & C-Atk Percent Hits

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.65 for the C group, 0.20 for the LD group, and 0.36 for the HD group. 

The C group had an average percent hit of 39%. This difference is higher (but not 

statistically significantly) for both the LD 37% and the HD 36%. These differences result 

in degradations of 6.62% (3 percentage points) and 9.63% (4 percentage points) in 

accuracy for the LD and HD groups, respectively. The HD group was 3.23% (1 
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percentage point) less accurate (but not statistically significantly) than the LD group. 

See Table F-2 and Table F-3 for detailed analytical results.

F.5.2.3.2 Attack & C-Atk Contextual Comments

F.5.2.3.2.1 Attack & C-Atk Contextual Comments Overview

In combat operations, accuracy is highly desirable in destroying or effectively 

suppressing an enemy position. In the execution of this task, the LD group sustained 

an average of 6.62% decrement in the percentage of hits for the number of shots taken, 

and the HD group sustained an average of 9.63% decrement in the percentage of hits 

for the number of shots taken. Operationally, this equates to a degradation of accuracy 

and/or an increase in ammunition expenditure. On any given day (under the same 

environmental conditions), the C group was more accurate than the LD group 70.6% of 

the time (12 out of 17 trial cycles) and more accurate than the HD group 66.7% of the 

time (10 out of 15 trial cycles). On any given day, the HD group was more accurate 

than the LD group 58.3% of the time (7 out of 12 trial cycles).

F.5.2.3.2.2 Analysis by Weapon System and Gender

The use of a Weapons Player Pack (WPP) on each weapon system allowed data to be 

captured on each shot taken by a Marine during the conduct of the attack and c-atk. 

When synchronized with the data obtained from the GTS, a shooter-to-shot correlation 

was possible. For the analysis of shot accuracy, accuracy percentages by gender and 

weapon were analyzed that measured percent hits and percent hits and near misses

where a hit indicates that a round hit the target silhouette and a near miss indicates that 

the LOMAH sensor detected a round within a 1.5-meter detection arc.

Since the accuracy results by gender were collected, a t-test was used for this analysis. 

Table F-4 displays the shot accuracy results by gender and weapon system. 

Table F-4. Shot Accuracy by Gender and Weapon System1

Probability of Hit Probability of Hit & Near Miss

Weapon F M % 

Difference

2-sided 

p-value F M % Difference

2-sided 

p-value

M4 0311* .28 .42 33% <0.01 .73 .75 3% 0.32

M27 0311** .25 .43 42% <0.01 .58 .69 16% .014

M16A4/M203 0311** .15 .28 46% <0.01 .50 .67 25% <0.01

M4 PI** .37 .44 16% .02 .73 .79 8% 0.03

M27 PI .37 .38 3% .7571 .66 .69 4% .37

M16A4/M203 PI** .15 .26 42% <0.01 .59 .70 16% 0.05

*Indicates that there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between the percent hits values for the gender.

 

1 The M16A4/M203 shot accuracy data are only for 5.56mm ammunition shot from the weapon and do not 

include the 40mm practice round accuracy.
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**Indicates that there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between the percent hits and the percent hits and near miss values for the gender.

The shot accuracy results by gender and weapon reveal that there is a statistically 

significant difference between genders of the Marines carrying M4 and M16A4/M203 

within the PI squads. The overall accuracy declined and the percent difference 

increased as the weight of the weapon system increased. The M4 was the lightest 

weapon and yielded the best results, while the M16A4/M203 was the heaviest weapon 

and yielded the worst results. 

One might think that experience level of the Marines (male vs. female) influenced the 

results. However, when compared to the 0311 results, the PI results disprove this 

conjecture, as both the male and female PI Marines came to the unit without being 

trained in Infantry tactics at the fleet learning center and their performance mirrors the 

results of the 0311 Marines. With the exception of the difference in M27 accuracy, 

which was not statistically significant, the PI accuracy and percent difference increased 

as the weapon got heavier. Furthermore, a close look at the unit training plan, 

methodology, leadership, and ammunition expended will show that the 0311 and PI 

Marines in the GCEITF were well prepared for this assessment, minimizing the impact 

of past experience. Therefore, one would conclude that given the same type and 

amount of training, female Marines would have less lethality on the battlefield than male 

Marines. 

F.5.2.3.3 Attack & C-Atk Additional Insights 

To explore the operational effect of a 2-percentage point difference in percentage of hits

by integration level (see Table F-2), we conducted a Monte Carlo Simulation using the 

Lanchester Square Law as a model of a tactical-level engagement. For more 

information on the Lanchester Square Law, see the Methodology Annex. We chose the 

Lanchester Square Law for rudimentary analysis using a well-known combat model to 

explore the potential effects of the differences discovered between integration levels.

We make several important assumptions for this Lanchester model in terms of 

parameter selection. We chose parameters that model a worst-case scenario for a 

squad engagement in which the squad faces an equivalent adversary in terms of 

capability. The first assumption is that the force sizes are equal, which is a 12-on-12 

fight. The second assumption is the relative rate of fire between forces, and we assume 

the ratio of friendly to enemy rate of fire to be equal to one. Finally, with respect to 

accuracy, the enemy was assumed to be as good as the best experimental group, 

which was the C group. Thus, the enemy probability of hit was set at 0.39. 

Two hundred thousand simulated engagements were run for both the C and LD groups. 

A force won an engagement when its opposition was eliminated. By construct, the C 

group, with a probability of hit equal to the enemy’s at 0.39, won 50% of the 
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engagements with an average of three Marines remaining. This, the even-fight case, is 

useful only to assess the effect of the LD group’s decrement in probability of hit. In 

another two hundred thousand simulated engagements, the LD group, with a probability 

of hit equal to 0.37, won 49.2% of the engagements with three Marines remaining. 

Based on these results, we would expect the LD group to win 0.8% fewer tactical-level 

engagements. One may expect a similar comparison between the C and HD groups to 

fall between the above result and the result obtained for the 0311 simulation. 

F.5.2.3.4 Attack & C-Atk Subjective Comments

For subjective comments relating to this task, see the Appendix.

F.5.2.4 CASEVAC by FT 

F.5.2.4.1 CASEVAC by FT Overview

This experimental task assessed a fireteam’s ability to move a 220-lb dummy a distance 

of 100 meters to a CCP while wearing a fighting load and individual weapon. Marines 

conducted this task at the conclusion of the squad attack/counterattack. At the 

discretion of each fireteam, Marines used a two-Marine, a three-Marine, or a fourMarine carry in order to move the casualty. The recorded time started when a member 

of the fireteam touched the dummy, and it stopped when the dummy and all members of 

the fireteam arrived at the CCP.

Figure F-4 displays CASEVAC by FT data. All data on the scatter plot are valid for 

analysis. 

Figure F-4. CASEVAC by FT

For this task, sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA.
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The C group had a mean time of 1.31 minutes. This is statistically significantly faster 

than the LD mean time of 1.57 minutes and the HD mean time of 1.63 minutes. These 

differences result in a 20.12% (0.26-minute) and 24.88% (0.33-minute) degradation in 

times for the LD and HD groups, respectively. The LD group was faster than the HD 

group. There was a 3.97% (0.06-minute) degradation in hike time from the LD to the 

HD group, but this difference is not statistically significant. See Table F-2 and Table F-3

for detailed analytical results.

F.5.2.4.2 CASEVAC Contextual Comments

The implications of this task contain relevance to both the training and combat 

environment as survival is dependent on expeditious movement of the casualty to 

higher levels of care. The data demonstrate that LD groups took 15.6 seconds longer

(a 20.12% degradation in performance) and the HD groups took 19.2 seconds longer (a 

24.88% degradation in performance) to accomplish the same 100-meter casualty 

movement. 

F.5.2.4.3 CASEVAC Additional Insights 

While the “Golden Hour” is a common medical planning construct for C2 and logistical 

support, medical literature supports a “Platinum Ten” philosophy of first response. The 

U.S. National Library of Medicine references a French article that states, “On the 

battlefield, the majority of casualties die within ten minutes of the trauma” (Wounded in 

Action: The Platinum Ten Minutes and the Golden Hour, Daban). The fundamental 

principle is that a patient needs to be correctly triaged and moved to medical care as 

quickly as possible. Any time degradation will reduce the probability of survival. 

F.5.2.4.4 CASEVAC Subjective Comments

For subjective comments relating to this task, see the Appendix.

F.5.2.5 Prepare Fighting Positions 

F.5.2.5.1 Prepare Fighting Position Overview

This experimental task assessed the amount of earth moved by a fireteam in a two-hour 

period. Each fireteam was required to dig 2 two-man fighting holes while wearing a 

fighting load and maintaining 50% security (only two Marines were digging at any given 

time). All the earth was scooped into buckets and weighed by a non-assessed Marine. 

The recorded time began 10 minutes after finishing the 7-km hike, and time stopped 2 

hours after beginning to dig.

Figure F-5 displays all PI Prepare Fighting Positions data. Five invalid data points were 

removed from both the plot and the analysis. All data on the scatter plot are valid for 

analysis.
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Figure F-5. Prepare Fighting Positions

For this task, sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA.

The C group moved a mean weight of 5,146.13 lb. This difference is higher (but not 

statistically significantly) for both the LD mean weight of 5,257.46 lb and the HD mean 

weight of 5184.84 lb. These differences result in 2.16% (111.33-lb) and 0.75% (38.71-

lb) degradations in weight moved for the LD and HD groups, respectively. The HD 

group moved 1.38% (72.62 lb) less (but not statistically significantly) in weight than the 

LD group. See Table F-2 and Table F-3 for detailed analytical results.

F.5.2.5.2 Prepare Fighting Positions Contextual Comments

Marine Corps Warfighting Publication (MCWP) 3-11.2 Marine Rifle Squad specifies the 

dimensions of a two-person fighting hole: 6 ft long X 2 ft wide X 5 ft deep (assuming 

occupants who are 5’6” – 6’ tall). The volume of this fighting hole is 60 ft3

. Two such 

holes are required for a fireteam, and together they have a combined volume of 120 ft3. 

In Engineering Manual 1110-1-1905 (Engineering and Design: Bearing Capacity of 

Soils), the Army Corps of Engineers estimates that collapsible soil (of the type found at 

MCAGCC Twentynine Palms) has an average density of 85 lb/ft3

. Thus, a total of 

10,200 lb of dirt would have to be moved in order to construct two fighting positions to 

the MCWP 3-11.2 standard.

The C group moved earth at a rate of 2,573.07 lb/hr. At this rate, the C group would 

have completed digging its fighting holes in 3 hours and 58 minutes. The LD group 

moved earth at a rate of 2,628.73 lb/hr. At this rate, the LD group would have 

completed digging its fighting holes in 3 hours and 53 minutes. The HD group moved 

earth at a rate of 2,592.42 lb/hr. At this rate, the HD group would have completed 
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digging its fighting holes in 3 hours and 56 minutes. Thus, the three groups each would 

have completed digging their fighting holes within 5 minutes of each other. 

F.5.2.5.3 Prepare Fighting Positions Additional Insights 

Motivation and perspective provided by the unit leadership was a contributing factor to 

the overall morale and work ethic of the fireteams and each individual Marine. 

Leadership and teamwork were not explicitly measured in this tactical task but are 

thought to have a larger impact than anticipated. The PI squads performed nearly 20% 

better than the 0311 control and integrated squads at this same task. Of note, the PI 

Platoon Leadership was observed constantly engaging with their Marines, walking 

around and inspecting the holes, helping weigh buckets of sand, and providing historical 

relevance after the assessment. This engaged style of leadership is thought to have 

resulted in greater workload output.

F.5.2.5.4 Prepare Fighting Position Subjective Comments

For subjective comments relating to this task, see the Appendix.

F.5.2.6 1-km Hike

F.5.2.6.1 1-km Hike Overview

This experimental task assessed a squad of 12 Marines moving approximately 1 km 

while each Marine carried an assault load and individual weapon. Each squad moved 

as quickly as possible to reinforce a notional friendly squad pinned down by enemy fire. 

The recorded time started when the squad departed the assembly area on Range 107 

and ended upon reaching a designated attack position just prior to the wall/obstacle. 

Figure F-6 displays all PI 1-km hike data. All data on the scatter plot are valid for 

analysis. 
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Figure F-6. 1-km Hike

The data are not normally distributed, as evidenced by the Shapiro-Wilk Test that 

resulted in a p-value of < 0.01 for the C, LD and HD groups. Because of a lack of 

normality, we recommend using the Mann-Whitney test results (reported in Table F-3). 

We proceed with presenting ANOVA results because they were confirmed by MannWhitney Tests.

The C group had a mean time of 8.87 minutes. This time is statistically significantly 

faster than the LD mean time of 9.55 minutes and the HD mean time of 9.37 minutes. 

These differences result in 7.65% (0.68-minute) and 5.66% (0.50-minute) degradations 

in time for the LD and HD groups, respectively. The HD group was faster than the LD 

group. There was a 1.85% (0.18-minute) degradation in hike time from the HD to LD 

group, but this difference is not statistically significant. See Table F-2 and Table F-3 for 

detailed analytical results.

F.5.2.6.2 1-km Hike Contextual Comments 

The Infantry T&R Manual states that “the maximum assault load weight will be such that 

an average infantry Marine will be able to conduct combat operations indefinitely with 

minimal degradation in combat effectiveness.” While moving 1 km with the assault load, 

the integrated squad type each moved at least 5.66% slower on average than the C 

group, making them 30 seconds less responsive reinforcing an adjacent unit. On any 

given day (under the same environmental conditions), the C group was faster than the 

LD group 72.2% of the time (13 out of 18 trial cycles), and faster than the HD group 

77.8% of the time (14 out of 18 trial cycles). On any given day, the LD group was faster 

than the HD group 53.3% of the time (8 out of 15 trial cycles). 
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F.5.2.6.3 1-km Hike Additional Insights 

A purely objective evaluation of 30 seconds is elusive but may possess some practical 

significance on the battlefield that would reduce the survivability of a unit waiting on an 

integrated squad. Considering the 12-15 rounds-per-minute sustained rate of fire for 

both the M4 and AK-47 rifles, a single enemy fighter would have the opportunity to take 

six to seven more well-aimed shots on Marines while waiting for reinforcements from an 

integrated squad. A fireteam of enemy fighters would have time to call in indirect 82mm 

mortar fire or maneuver during this time delay. The resultant trade in casualty 

exchange could be significant.

F.5.2.6.4 1-km Hike Subjective Comments

For subjective comments relating to this task, see the Appendix.

F.5.2.7 Negotiate Obstacle

F.5.2.7.1 Negotiate Obstacle Overview

This experimental task assessed the time it took to get a squad of 12 Marines and all 

equipment over an 8-foot-tall ISO Container (wall/obstacle). The squad began this task 

as soon as it finished the 1-km movement. The recorded time started when the first 

Marine touched the wall and stopped when the last Marine touched both feet down on 

the other side. 

Figure F-7 displays all PI Negotiate Obstacle data. On trial cycle 11, the C group data 

point was removed for analysis as it represents a data outlier, and on trial cycle 15, the 

HD data point was removed for analysis as it represents a data outlier. With the 

exception of these points, all data on the scatter plot are valid for analysis.
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Figure F-7. Negotiate Obstacle

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.53 for the C group, 0.07 for the LD group, and 0.07 for the HD group. 

The C group had a mean time of 1.75 minutes. This is faster (but not statistically 

significantly) than the LD mean time of 1.78 minutes. The C group mean time is 

statistically significantly faster than the HD mean time of 2.13 minutes. These 

differences result in 1.88% (0.03-minute) and 21.80% (0.38-minute) degradations in 

time for the LD and HD groups, respectively. The LD mean time was statistically 

significantly faster than the HD group. There was a 19.55% (0.35-minute) degradation 

in hike time from the LD to the HD group. See Table F-2 and Table F-3 for detailed 

analytical results. 

F.5.2.7.2 Negotiate Obstacle Contextual Comments 

Sun Tzu stated, “Speed is the essence of war. Take advantage of the enemy’s 

unpreparedness; travel by unexpected routes and strike him where he has taken no 

precautions” (MCDP-1, p. 69). Speed and surprise are crucial to success. 

Furthermore, the enemy is reliably expected to cover obstacles with fires. When 

possible, obstacles are to be avoided. When not possible, they must be negotiated 

quickly. While no purely objective standard can be set for the negotiation of the 

obstacle presented in this task, any decrement in speed translates into increased 

exposure to enemy fires and greater risk for friendly casualties. On average, the LD

groups were 2 seconds slower than the C groups and the HD groups were 23 seconds 

slower in performing the same task. On any given day (under the same environmental 

conditions), the C group was faster than the LD group 58.8% of the time (10 out of 17

trial cycles) and faster than the HD group 86.7% of the time (13 out of 15 trial cycles). 
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On any given day, the LD group was faster than the HD group 76.9% of the time (10 out 

of 13 trial cycles).

F.5.2.7.3 Negotiate Obstacle Additional Insights

Of note, a large discrepancy may be observed when comparing the PI obstacle time 

with the 0311 obstacle time. This difference can be explained by the different 

techniques used by each group. The 0311 squads provided their own security and only 

used one launch-point up the wall, while the PI squads did not establish security and 

used three launch-points to get over the wall. Each group (0311 and PI) was consistent 

within itself, but the two groups should not be compared with each other.

F.5.2.7.4 Negotiate Obstacle Subjective Comments

According to the subjective leadership observations, 25 recorded comments about 

Marines requiring extra assistance to complete this task applied to female Marines, 

while only 2 applied to male Marines who were members of LD or HD squads. There 

were also four comments citing a male Marine who was a member of an LD or HD 

squad as compensating for another Marine, and no such comments for the female 

squad members.

For additional subjective comments for this task, see the Appendix.

F.6 Statistical Modeling Results 

F.6.1 Statistical Modeling Results Overview

The previous section discussed results only as they pertain to differences due to 

integration level alone. The goal of statistical modeling, as applied here, is to estimate, 

simultaneously, the effect of gender integration levels and other relevant variables on 

squad performance. Refer to the Methodology Annex for a broad overview of the 

analysis plan and the variables used in the models. 

For the same seven selected tasks described in the previous section, this section first 

presents an overview of the analysis and results, and then presents the modeling 

results for each of the tasks.

For each task, we describe the significant variables in the model and whether these 

variables are either positively or negatively correlated with the result. A negative 

correlation indicates that an increase in that variable will result in a decrease in the 

response variable, which is a desired outcome for elapsed time but not a desired 

outcome for the percent hits or for pounds of earth moved. The results indicate where 

certain patch numbers are significant for a given variable. The experiment tracked 

Marines within the rifle squad by a patch number that associated their random position 

within the squad to a specific billet. Table F-5 displays the patch numbers and 

associated billet titles for the rifle squad.
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Table F-5. Patch Numbers and Billet Titles for the Rifle Squad

Patch Number Billet Title

1 FT 1 Fireteam Leader

2 FT 1 Automatic Rifleman

3 FT 1 Grenadier

4 FT 1 Rifleman

5 FT 2 Fireteam Leader

6 FT 2 Automatic Rifleman

7 FT 2 Grenadier

8 FT 2 Rifleman

9 FT 3 Fireteam Leader

10 FT 3 Automatic Rifleman

11 FT 3 Grenadier

12 FT 3 Rifleman

F.6.2 PI Selected Tasks Method of Analysis

A mixed effects model does not work for the PI data set because of the low number of 

volunteers and trials. Therefore, we model the PI selected tasks using ordinary least 

squares regression. 

For the majority of each of the primary metrics for the rifle squad, there are only 60 

observations for each result. Because there are 12 Marines in a rifle squad and so few 

results, the regression model does not have a sufficient number of degrees of freedom 

to create a model using all types of personnel data for each squad member for each 

result. Thus, each variable combined with integration level is modeled separately. For 

example, age for each member of the rifle squad (12 variables) and integration level are 

modeled with the result (response time, percentage hits, or pounds of earth moved) as 

the response variable. Where possible, a backward stepwise regression, using AIC, 

determined which variables are optimal in the model. If there were missing values, 

backward stepwise could not run and significant variables are reported based on 

p-values from the overall model.

F.6.3 PI Selected Tasks Overall Modeling Results

There are no personnel data variables that are both statistically significant and have a 

practical impact on the model. Each time personnel data variables are statistically 

significant in a model, their effects are practically negligible, conflicting, and/or 
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incomplete for the squad — i.e., there are no tasks for which a variable is significant for 

all, or even most, members of the rifle squad. 

Integration level, however, consistently appears as statistically significant in each of the 

tasks (except prepare defensive position), and its effect is clear, causal, and practical. 

Therefore, integration level is the best variable for describing performance for each of 

these tasks. Refer to Section F.5 to see the ANOVA summary for each of the PI tasks

mentioned below. 

F.6.3.1 7-km Hike

We model elapsed time for the 7-km hike as a function of each personnel variable and 

integration level in a separate model. The covariates in each model are the values of 

each personnel variable for each patch number. For each model, we report statistically 

significant positive and negative correlations and whether we observe any patterns.

The models for the following variables do not run due to missing values: 

• None. 

Both the HD and LD integration levels are significant and positively correlated with the 

response for the models that include the following personnel variables: 

• All. 

Both the HD and LD integration levels are significant and negatively correlated with the 

response for the models that include the following personnel variables: 

• None.

The following variables are significant in their respective models and are positively 

correlated with the 7-km hike time: 

• Height of patch 5, 

• Weight of patch 5, 

• AFQT score of patch 1, 

• GT score of patch 1, 2, and 11, 

• CFT MTC of patches 5 and 8, 

• CFT MANUF of patches 5 and 8, 

• PFT 3-mile run of patch 6, 

• Rifle score of patches 3, 4, and 10. 

The following variables are significant in their respective models and are negatively 

correlated with the 7-km hike time: 
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• Age of patches 4 and 8, 

• Height of patch 8, 

• Weight of patch 6, 

• AFQT score of patch 10, 

• CFT MTC of patches 3, 4, and 11, 

• CFT MANUF time of patches 2, 3, 4, 6, 11, and 12, 

• PFT crunches of patches 2, 3, 6, 7, and 9, 

• Rifle score of patches 1, 5, and 8.

The following personnel variables have no significant variables in their respective 

models:

• None.

There are no patterns for any personnel variables for the 7-km hike. See Section 

F.5.2.1 for the ANOVA summary of this task.

F.6.3.2 Movement to LOA

We model elapsed time for the movement to LOA as a function of each personnel 

variable and integration level in a separate model. The covariates in each model are 

the values of each personnel variable for each patch number. For each model, we 

report statistically significant positive and negative correlations and whether we observe 

any patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following variables: 

• Age, 

• Weight, 

• AFQT score, 

• GT score, 

• PFT crunches, 

• PFT 3-mile run.

The LD integration level is significant and positively correlated with the response for the 

models that include the following variables: 
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• Age, 

• AFQT score, 

• GT score, 

• PFT 3-mile run. 

The HD and LD integration levels are significant and negatively correlated with the 

response for the models that include the following personnel variables: 

• None.

The following variables are significant in their respective models and are positively 

correlated with the movement to the LOA time: 

• Age of patches 5 and 7; 

• Height of patch 4, 

• Weight of patch 4, 

• GT score of patches 7 and 11, 

• CFT MTC of patches 5, 6, 9, 10, and 12, 

• PFT 3-mile run of patch 3, 

• Rifle score of patches 2 and 7. 

The following variables are significant in their respective models and are negatively 

correlated with the movement to the LOA time: 

• Age of patches 3, 4, and 8, 

• Height of patches 2, 3, 6, 9, and 12 

• Weight of patches 2, 3, and 12, 

• CFT MTC of patches 3, 4, and 11, 

• CFT MANUF time of patch 4, 

• PFT crunches of patches 5 and 6

• Rifle score of patches 4 and 8.

The following personnel variables have no significant variables in their respective 

models:

• None.

There are no patterns for any personnel variables for the movement to LOA time. See 

Section F.5.2.2 for the ANOVA summary of this task.
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F.6.3.3 Attack & C-Atk Percent Hits

We model the attack & c-atk percent hits as a function of each personnel variable and 

integration level in a separate model. The covariates in each model are the values of 

each personnel variable for each patch number. For each model, we report statistically 

significant positive and negative correlations and whether we observe any patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD and LD integration levels are significant and positively correlated with the 

response for the models that include the following variables: 

• None.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following variables: 

• Age,

• AFQT score,

• GT score,

• CFT MTC,

• CFT MANUF. 

The LD integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables: 

• None.

The following variables are significant in their respective models and are positively 

correlated with the percent of hits for the attack and counterattack: 

• Age of patches 3, 6, 7, 8, and 12, 

• Height of patch 12, 

• Weight of patches 7 and 12, 

• AFQT score of patch 2, 8, and 9,

• GT score of patch 9, 

• CFT MTC of patch 9, 

• CFT MANUF of patch 9,

• PFT crunches of patches 1 and 8,

• PFT 3-mile run of patch 1 and 8, 
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• Rifle score of patches 2 and 7. 

The following variables are significant in their respective models and are negatively 

correlated with the percent of hits for the attack and counterattack: 

• Age of patch 10, 

• Height of patches 3 and 10, 

• Weight of patch 3, 

• AFQT score of patches 5 and 12,

• CFT MTC of patch 5. 

The following personnel variables have no significant variables in their respective 

models:

• Rifle score.

There are no patterns for any personnel variables for the attack and c-atk percent hits. 

See Section F.5.2.3 for the ANOVA summary of this task.

F.6.3.4 CASEVAC by FT

We model elapsed time for the CASEVAC as a function of each personnel variable and 

integration level in a separate model. The covariates in each model are the values of 

each personnel variable for each patch number. For each model, we report statistically 

significant positive and negative correlations and whether we observe any patterns. 

The models for the following variables do not run due to missing values: 

• None.

Both the HD and LD integration levels are significant and positively correlated with the 

response for the models that include the following variables:

• All. 

The HD and LD integration level are significant and negatively correlated with the 

response for the models that include the following personnel variables: 

• None.

The following variables are significant in their respective models and are positively 

correlated with the CASEVAC by FT time: 

• Height of patch 3,

• Weight of patch 3,

• CFT MTC of patches 1 and 2,
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• CFT MANUF of patches 1 and 2,

• PFT 3-mile run of patch 1.

The following variables are significant in their respective models and are negatively 

correlated with the CASEVAC by FT time: 

• Height of patches 1 and 4,

• Weight of patch 1,

• AFQT score of patch 1,

• GT score of patches 1 and 2,

• PFT crunches of patch 1.

The following personnel variables have no significant variables in their respective 

models:

• None.

There are no patterns for any personnel variables for the CASEVAC time. See section 

F.5.2.4 for the ANOVA summary of this task.

F.6.3.5 Prepare Fighting Position by FT

We model the amount of earth moved to prepare a fighting position as a function of 

each personnel variable and integration level in a separate model. The covariates in 

each model are the values of each personnel variable for each patch number. For each 

model, we report any statistically significant positive and negative correlations and 

whether we observe any patterns.

The models for the following variables do not run due to missing values: 

• None.

Both the HD and LD integration levels are significant and positively correlated with the 

response for the model that includes: 

• CFT MANUF. 

The HD and LD integration levels are significant and negatively correlated with the 

response for the models that include the following personnel variables: 

• None.

The following variables are significant in their respective models and are positively 

correlated with the amount of earth moved for the defensive position: 

• Age of patches 1 and 2, 

• Weight of patch 2, 
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• AFQT score of patch 2, 

• Rifle score of patch 3.

The following variables are significant in their respective models and are negatively 

correlated with the amount of earth moved for the defensive position: 

• CFT MTC of patch 2, 

• CFT MANUF of patches 2, 3, and 4, 

• PFT 3-mile run of patch 2.

The models for the following variables have no significant variables in the model: 

• Height, 

• GT score, 

• PFT crunches. 

The following personnel variables have no significant variables in their respective 

models:

• None.

There are no patterns for any personnel variables for the amount of earth moved to 

prepare a fighting position. See Section F.5.2.5 for the ANOVA summary of this task.

F.6.3.6 1-km Hike

We model elapsed time for 1-km hike as a function of each personnel variable and 

integration level in a separate model. The covariates in each model are the values of 

each personnel variable for each patch number. For each model, we report any 

statistically significant positive and negative correlations and whether we observe any 

patterns.

The models for the following variables do not run due to missing values: 

• None.

Both HD and LD Integration levels are significant and positively correlated with the 

response for the models that include the following variables: 

• Age, 

• Height,

• Weight, 

• AFQT score,

• GT score, 
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• PFT crunches, 

• PFT 3-mile run, 

• Rifle score. 

The LD integration level is significant and positively correlated with the response in the 

models that include the following variables: 

• CFT MTC, 

• CFT MANUF. 

The HD and LD integration levels are significant and negatively correlated with the 

response for the models that include the following personnel variables: 

• None.

The following variables are significant in their respective models and are positively 

correlated with the 1-km hike time: 

• Age of patches 3 and 5, 

• Height of patch 1, 

• Weight of patch 1, 

• CFT MTC of patch 7, 

• CFT MANUF time of patch 10, 

• PFT 3-mile run time of patch 4. 

The following variables are significant in their respective models and are negatively 

correlated with the 1-km hike time: 

• AFQT score of patches 6, 9, 10, and 12, 

• CFT MTC of patch 12, 

• PFT crunches of patch 6, 

• Rifle score of patch 10.

The following personnel variables have no significant variables in their respective 

models:

• None.

There are no patterns for any personnel variables for the 1-km hike time. See section 

F.5.2.6 for the ANOVA summary of this task.
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F.6.3.7 Negotiate Obstacle

We model elapsed time for the negotiate obstacle of each personnel variable and 

integration level in a separate model. The covariates in each model are the values of 

each personnel variable for each patch number. For each model, we report statistically 

significant positive and negative correlations and whether we observe any patterns.

The models for the following variables do not run due to missing values: 

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following variables: 

• Age,

• Height, 

• Weight, 

• AFQT score, 

• CFT MTC, 

• CFT MANUF, 

• PFT crunches, 

• PFT 3-mile run, 

• Rifle score. 

The LD integration level is significant and positively correlated with the response for the 

models that include the following variables: 

• Weight,

• PFT crunches. 

The HD integration level is significant and negatively correlated with the response for 

the models that include the following variables: 

• None.

The LD integration level is significant and negatively correlated with the response for the 

model that includes:

• GT score. 

The following variables are significant in their respective models and are positively 

correlated with the negotiate obstacle time: 

• Age of patch 5, 
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• Height of patches 4 and 8, 

• Weight of patches 3 and 4, 

• CFT MTC of patches 3, 5, and 9, 

• PFT crunches of patches 6, 8, and 12, 

• PFT 3-mile run of 1, 5, 6, 7, and 9. 

The following variables are significant in their respective models and are negatively 

correlated with the negotiate obstacle time: 

• Age of patch 12, 

• AFQT score of patches 5, 10, and 11, 

• GT score of patches 3, 5, 10, and 12, 

• CFT MTC of patches 8 and 11, 

• PFT crunches of patches 1 and 3,

• PFT 3-mile run of patch 8, 

• Rifle score of patches 1, 8, and 9.

The following personnel variables have no significant variables in their respective 

models:

• None.

There are no patterns for any personnel variables for the negotiate obstacle time. See 

Section F.5.2.7 for the ANOVA summary of this task.
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Appendix to Annex F 

Provisional Infantry Supplemental Information

This appendix provides supplemental information for the Provisional Infantry (PI) portion 

of the GCEITF experiment. It provides information regarding the GCEITF leadership 

subjective comments and additional descriptive and basic inferential statistics not 

described in Annex F. 

Section 1. GCEITF Leadership Subjective Comments

The GCEITF leadership provided comments on their observations of the experiment 

throughout its execution. Table F A displays a summary of these comments broken 

down by task, integration level, gender, and type of comment.
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Table F A – Summary of GCEITF Leadership Comments

Section 2. Additional Task Basic and Inferential Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. The experiment included a number of tasks and associated metrics 

conducted to enhance operational realism and maintain consistent application of the 

experimental process. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

This section presents results for nine additional PI tasks. Annex F contains the 

descriptive statistics for the remainder of the PI tasks. The words “metric” and “task” 

are used interchangeably throughout this Appendix; they both refer to the experimental 

task. 

Task and Metric Description Gender Total

C LD HD Total C LD HD Total C LD HD Total C LD HD Total C LD HD Total C LD HD Total C LD HD Total C LD HD Total

M 35 7 1 43 1 0 1 2 0 1 0 1 1 2 0 3 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 52

F 0 10 21 31 0 2 4 6 0 1 2 3 0 2 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 44

Unit 0 0 0 0 0 1 0 1 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

M 25 17 5 47 0 0 0 0 24 10 12 46 11 11 4 26 0 2 1 3 0 0 0 0 0 0 0 0 1 0 0 1 123

F 1 22 17 40 0 0 0 0 3 13 27 43 0 3 4 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 90

Unit 0 0 1 1 0 0 0 0 0 1 1 2 4 4 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 12

M 0 1 0 1 0 0 0 0 0 0 0 0 22 17 7 46 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 47

F 0 1 0 1 0 0 0 0 0 2 0 2 0 7 4 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

M 1 0 0 1 0 0 0 0 0 0 0 0 15 15 8 38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 39

F 0 0 0 0 0 0 0 0 0 2 3 5 0 6 13 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 0 0 0 0 0 0 31 15 21 67 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 67

F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 0 0 2 2 0 4 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 6

F 0 1 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 6 3 0 9 0 0 0 0 6 0 0 6 6 3 4 13 1 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 30

F 0 1 0 1 0 0 0 0 0 0 0 0 0 1 4 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 3 0 2 5 0 0 0 0 5 1 0 6 6 4 3 13 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 25

F 0 0 2 2 0 0 0 0 0 1 0 1 0 0 7 7 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 11

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 2 2 0 4 0 0 0 0 2 2 4 8 9 2 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23

F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 2

F 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 3

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 0 0 3 1 1 5 1 0 1 2 1 1 3 5 0 0 0 0 0 0 0 0 0 0 0 0 12

F 0 0 1 1 0 0 0 0 0 8 17 25 0 1 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 29

Unit 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 3

CASEVAC to CCP; FT1 

Elapsed time

CASEVAC to CCP; FT3 

Elapsed Time

Negotiate Obstacle

CASEVAC to CCP; FT2 

Elapsed Time

No category Falling behind/slowing 

movement

Requesting extra 

breaks

Requires extra 

assistance Needs no assistance Compensating for another Marine Gear pass off Other

7-km Hike

Movement to LOA

1-km Hike

Attack & C-Atk (% hits)

Prepare Defensive Position; 

Total Weight FT1

Prepare Defensive Position; 

Total Weight FT3

Prepare Defensive Position; 

Total Weight FT2
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The two tables below display the results for nine additional PI metrics. Table F B

displays the metrics and integration levels with their respective sample sizes, means, 

standard deviations, and percent differences between integration levels. 

Table F C displays ANOVA and Tukey Test results, including metrics and integration 

levels, and p-values suggesting statistical significance. For each task, an ANOVA was 

conducted to compare the three groups and Tukey Tests were conducted to compare 

each pair of two groups. If non-parametric tests were needed, Table F C displays these 

results instead of ANOVA and Tukey Test results. If p-values are less than the a-priori 

determined significance level of 0.10, we conclude that there is statistical evidence that 

the result was not found to be the same across all three groups. We present basic 

inferential statistics for two tasks (one with a potential influential point).

Table F B – PI Test Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

7-km Hike; first km

C 17 9.74 0.61

LD 15 10.48 0.52 7.67% 9.00% 1.23%

HD 16 10.61 0.37

7-km Hike; second 

km

C 17 10.07 0.46

LD 15 11.02 0.52 9.37% 9.70% 0.30%

HD 16 11.05 0.47

7-km Hike; third 

km

C 17 9.81 0.48

LD 15 10.98 1.65 11.94% 8.95% -2.67%

HD 16 10.69 0.54

7-km Hike; fourth 

km

C 17 10.37 0.53

LD 15 11.08 0.76 6.87% 7.60% 0.68%

HD 16 11.15 0.59

7-km Hike; fifth km

C 17 12.39 1.47

LD 14 14.74 3.21 18.97% 18.94% 0.02%

HD 16 14.74 2.93

7-km Hike; sixth 

km

C 17 13.56 2.07

LD 15 14.20 2.56 4.72% 9.02% 4.11%

HD 15 14.78 2.53

7-km Hike; 

seventh km

C 18 12.87 1.34

LD 15 13.00 1.23 0.94% 2.95% 1.99%

HD 16 13.25 0.68

Attack(Hits on 

Target)* 

C 19 563.74 76.75

LD 17 528.71 60.84 -6.21% -17.25% -11.77%

HD 17 466.47 154.24

Attack [excluding 

potential 

influential point]

C 19 563.74 76.75

LD 17 528.71 60.84 -6.21% -12.22% -6.40%

HD 16 494.88 103.67
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Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

(Hits on Target)*

C-Atk (Hits on 

Target)

C 20 59.00 23.04

LD 17 57.47 20.17 -2.59% 10.81% 13.75%

HD 16 65.38 32.52

Table F C – PI ANOVA and Tukey Test Results

Metric

F 

statistic 

(df)

F Test

PvalueComparison 2-sided 

P-Value

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Attack(Hits on 

Target)†† 6.17 0.05*

LD-C 0.14 -65.06 -5.00 -73.89 3.83

HD-C 0.03* -151.83 -42.70 -168.14 -26.39

HD-LD 0.14 -115.46 -9.01 -131.45 6.98

Attack 

[excluding 

potential 

influential 

point] (Hits on 

Target)*

3.10

(2, 49) 0.05*

LD-C 0.41 -82.51 12.44 -92.29 22.23

HD-C 0.04* -117.11 -20.61 -127.06 -10.66

HD-LD 0.46 -83.36 15.70 -93.57 25.91

C-Atk (Hits on 

Target)

0.45

(2, 50) 0.64

LD-C 0.98 -16.17 13.11 -19.19 16.13

HD-C 0.74 -8.51 21.26 -11.58 24.33

HD-LD 0.65 -7.55 23.36 -10.74 26.55

*Indicates there is a statistically significant difference in a two-sided hypothesis test between integration 

levels according to ANOVA or a non-parametric equivalent test.

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given 

confidence level on its own. 

††Indicates results presented are from Robust ANOVA and Welch’s t-tests with p-values compared to 

0.033 for Bonferroni adjustment due to unequal variances. The reported F-statistic is a Chi-square 

statistic from Robust ANOVA, and the F-test p-value is the Robust ANOVA p-value. The p-values in 

columns labeled “2-sided P-value” and “1-sided P-value” are p-values from Welch’s t-tests, and the 

confidence intervals are from Welch’s t-tests.

Additional Task Results: 

7-km Hike by km. The general trend for the 7-km hike was that the difference between 

the LD and C groups, the HD and C groups, and the HD and LD groups increased over 

the course of the hike.

Attack (hits on target). The data are normally distributed, as evidenced by the 

Shapiro-Wilk Test that resulted in a p-value of 0.51 for the C group, 0.12 for the LD 

group, and 0.02 for the HD group.

The C group had a mean of 563.74 hits on target. This number is higher (but not 

statistically significant) than the LD group mean of 528.71 and statistically significantly 

higher than the HD group mean of 466.47. The LD group put 6.21% less shots on 

target than the C group. The HD group put 17.25% less shots on target than the C 

group. The HD group put 11.77% less shots on target than the LD group. 
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Attack with Potential Influential Point Removed (Hits on Target). The data are 

normally distributed, as evidenced by the Shapiro-Wilk Test that resulted in a p-value of 

0.51 for the C group, 0.12 for the LD group, and 0.95 for the HD group.

The C group had a mean of 563.74 hits on target. This number is higher (but not 

statistically significant) than the LD group mean of 528.71 and statistically significantly 

higher than the HD group mean of 494.88. The LD group put 6.21% less shots on 

target than the C group. The HD group put 12.22% less shots on target than the C 

group. The HD group put 6.40% less shots on target than the LD group. 

Counterattack (hits on Target). The data are normally distributed, as evidenced by 

the Shapiro-Wilk Test that resulted in a p-value of 0.97 for the C group, 0.22 for the LD 

group, and 0.72 for the HD group.

The C group had a mean of 59.00 hits on target. This number is higher (but not 

statistically significantly) than the LD group mean of 57.47 and lower (but not statistically 

significantly) than the HD group mean of 65.38. The LD group put 2.59% less shots on 

target than the C group, and the HD group put 10.81% more shots on target than the C 

group. The HD group put 13.75% more shots on target than the LD group. 
FOR OFFICIAL USE ONLY 

Annex G. 

Provisional Infantry Machine Gunner (PIMG) 

This annex details the Provisional Infantry Machine Gunner (PIMG) portion of the 

Ground Combat Element Integrated Task Force (GCEITF) experiment executed from 2 

March – 26 April 2015 at Range 107 and Range 110, aboard the Marine Corps Air 

Ground Combat Center (MCAGCC), Twentynine Palms, CA. The sections outline the 

PIMG Scheme of Maneuver (SOM), Limitations, Deviations, Data Set Description, 

Descriptive and Basic Inferential Statistics, and Modeling Results.

G.1 Scheme of Maneuver

G.1.1 Experimental Cycle Overview

The Provisional Infantry Machine-gunner (PIMG) assessment of the GCEITF took place 

in a field environment aboard MCAGCC, Twentynine Palms, CA. The assessment 

consisted of 21 trial cycles, each of which was a 2-day test cycle, conducted over the 

course of 55 days. Marines spent 1 recovery day at Camp Wilson after every 4 days of 

trials. Each machine-gun squad consisted of three volunteers and a direct-assignment 

(non-volunteer) squad leader. Each member of the squad was trained to fill each billet 

within the squad: gunner, assistant gunner, and ammo man. For consistency 

throughout the report, the term “squad” will be used for the M240B medium machinegun squad. The assessment was executed under the supervision of MCOTEA 

functional test managers and a range Officer in Charge (OIC)/Range Safety Officer 

(RSO) from the GCEITF. 

G.1.2 Experimental Details

The 2-day PIMG assessment replicated offensive and defensive tasks. The PIMG 

squads began each cycle on the Defensive task. Two PIMG squads executed each trial 

cycle: a control (C) all-male squad and a high-density (HD) all-female squad. 

Day 1 of the trial cycle was executed on Range 110 and consisted of defensive actions. 

The day started with a 7-km forced march from Range 107 to Range 110 wearing an 

approach load and carrying personal weapons, crew-served weapons, and ammunition. 

Each heavy machine-gun squad prepared a M2 heavy machine gun for employment. 

The squads engaged three targets based on a prescribed course of fire with 400 rounds 

of .50-cal ammunition. Immediately upon the gun going out of action, the machine-gun

squad displaced the machine gun to a designated location. The trials concluded with a 

mount and dismount of the M2 machine gun to a HMMWV.

Day 2 of the trial cycle was executed on Range 107 and consisted of supporting a 

squad attack from the support-by-fire (SBF) position then displaced to the limit of 
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advance. The PIMG squad repelled an enemy counterattack by fire for 90 seconds. 

Finally, each squad conducted a 100-m CASEVAC of a 220-lb dummy. At the 

conclusion of Day 2, the Marines reorganized into a new squad for the next 

experimental cycle.

G.1.3 Additional Context

Throughout the assessment, Marines bivouacked at Range 107, sleeping in two-man 

tents. Prior to the experiment, each machine gun was zeroed to maximize accuracy. 

During trial execution, Marines wore/carried prescribed loads for each task. Weighing 

packs each day prior to the 7-km forced march ensured consistency. After each trial 

day, the Marines operated under the guidance of their Company leadership, performing 

minimal physically demanding tasks. The Marines who were not part of an assessed 

PIMG squad conducted the same experimental subtasks after the assessed squads to 

ensure equity between individuals participating in a trial cycle and those not chosen for 

that particular cycle. These tasks will be discussed in detail in the loading section 

below.

Fatigue surveys were designed to capture the volunteers’ cumulative fatigue level at the 

beginning and end of each day’s trials. The data collected provide additional insight into 

apparent aberrations in the performance level of a given volunteer on a specific day. It 

allows for outside fatigue-related factors (minor illness, lack of sleep the night before, 

etc.) to be accounted for in the analysis of the performance data. Workload surveys 

collected the volunteers’ perceived average and maximal level of exertion during the 

performance specified tasks. Cohesion surveys provided a method of collecting 

subjective data relating to each machine-gun squad’s ability to work as a team and their 

overall perspective on the cohesiveness of the squad.

G.1.4 Experimental Tasks

G.1.4.1 7-km Hike

Infantry units must move through all sorts of terrain on foot. Units train by conducting a 

forced march with an approach load at a sustained rate of march. For the assessment, 

each PIMG squad moved a distance of 7.2 km as quickly as possible while carrying an 

approach load, and the M240B machine gun, tripod, spare barrel, and ammunition 

spread-loaded across all three members. This task determined the squad’s rate of 

movement over a 7.2-km route while carrying the approach load and their crew-served 

weapon. Each Marine took a fatigue and workload survey after completion of the 

7.2-km hike.

G.1.4.2 M2 Emplacement, Engagement, and Displacement 

Providing defensive fires with the M2 heavy machine gun entails moving the system to a 

position of advantage, engaging the enemy, and conducting a rapid displacement. 
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Oftentimes, the M2 is employed from the tripod. During the assessment, each PIMG 

squad emplaced the M2 on a tripod at a specified firing location. The assessment 

began with targets exposed and engaged by the squad. Three targets and 400 rounds 

were allocated for this course of fire. Immediately upon going out of action, the squad 

displaced from the firing line to a designated location, moving a heavy load a short 

distance, manipulating a weapon while fatigued, and accurately engaging targets. This 

task determined accuracy and displacement times. 

G.1.4.3 M2 Mount and Dismount

The M2 heavy machine gun is often employed from a vehicular platform, such as a 

HMMWV. To mount this system, the squad must lift all components from the ground to 

the turret and assemble the system. Similarly, to dismount the system, the squad must 

manually lower each component to the ground. During the assessment, each PIMG 

squad worked together to mount and dismount an M2 from a HMMWV. This task 

required the strength to lift, manipulate, and lower heavy components. This task 

determined the time for a squad of three Marines to fully mount and dismount the M2 

from a tactical vehicle.

At completion of the mount and dismount tasks, Marines took a fatigue and workload 

survey to assess their fatigue and workload during execution (see GCEITF EAP, 

Annex D). 

G.1.4.4 1-km Movement 

Assaulting an enemy position never starts from a static position; first, a movement must 

be conducted to the assault position (AP). The distance from the line of departure to 

the AP is dependent upon myriad factors. Based on time and space constraints, this 

distance was set at just under 1 km for the experimental event. Each PIMG squad

moved this distance as quickly as possible while carrying an assault load in addition to 

the M240B machine gun, tripod, spare barrel, and ammunition (600 rounds of 7.62 mm) 

divided among the members. 

G.1.4.5 Occupy and Engagement from SBF Position 

Prior to commencing an assault, it is common for the machine-gun section to occupy a 

position of overwatch and provide SBF for the attacking unit. Movement to a SBF 

position varies in distance based on the terrain, which is often challenging. From the 

SBF position, the PIMG squad must rapidly get their gun into action, acquire targets, 

and accurately engage the enemy. During the assessment, each PIMG squad moved 

approximately 100 meters from an AP to the SBF position and emplaced the M240B. 

Once the squad leader confirmed “gun up,” they engaged targets presented in a 

predetermined course of fire. Three targets and 400 rounds were allocated during this 

course of fire. This task determined how quickly the squad could move to a SBF 
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position and get the gun into action, as well as determined the squad’s accuracy while 

engaging targets. 

G.1.4.6 Displace to the LOA

After providing initial suppressive fires from a SBF position to support an assault, 

machine-gun squads generally move to another position of advantage. Given the 

command, they must break down their weapon system and displace to a follow-on firing 

position, quickly. During the assessment, each PIMG squad displaced from their initial 

SBF position approximately 300 meters to a limit of advance/secondary SBF position. 

From this new position, they prepared to repel the enemy counterattack. This task 

determined how much time it took for a machine-gun squad to displace and prepare for 

an enemy counterattack.

G.1.4.7 Repel Counterattack

At the conclusion of every assault, the attacking unit must be prepared for the enemy to 

regroup and organize a counterattack. Upon consolidation at the LOA, the squad

oriented its weapons in the direction of the enemy’s retreat. Upon targets being 

presented, the counterattack commenced for 90 seconds. Two targets and 200 rounds 

were allocated during the machine-gun counterattack course of fire. 

G.1.4.8 CASEVAC

Casualties are an inevitable part of conducting combat operations. Units train to 

become proficient in triaging, handling, and transporting a casualty. When a casualty is 

sustained, it is essential to move with a sense of urgency to get the injured Marine to 

the appropriate level of care. At the conclusion of the live-fire and counterattack, each 

PIMG squad moved a 220-lb dummy 100 meters from a position of cover to a casualty 

collection point (CCP) while also transporting their assault packs and crew-served 

weapon system (M240B, tripod, and spare barrel). The machine-gun squad could use a 

variety of techniques for transport but had to carry the dummy off the ground. This task 

determined the PIMG squad’s proficiency in moving a simulated casualty to a CCP. 

After the CASEVAC, each Marine took a fatigue and workload survey to assess overall 

fatigue and workload of the entire offensive task (see GCEITF EAP, Annex D).

At the completion of the 2-day cycle, Marines took a cohesion survey to record their 

cohesion during execution of the 2-day trial cycle (see GCEITF EAP, Annex M.) 

G.1.5 Loading Plan

The loading plan ensured, to the greatest extent possible, equity of physical activity 

amongst all volunteers throughout the duration of the experimental assessment. Every 

trial and task was conducted in the same manner and sequence to ensure consistency. 

Due to the number of volunteers, a handful of Marines were not part of an assessed 

squad each 2-day cycle. Collaboration with the Company leadership determined the 
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best method of loading non-assessed Marines was to have them perform the same 

tasks as an assessed squad to experience the same conditions and physical strain. 

Minor modifications were permitted due to the reduced squad of the squad, such as 

conducting a trial as the fourth Marine in a 3-Marine element when not enough 

individuals were available to form another squad. 

G.1.6 Scheme of Maneuver Summary

The Provisional Infantry Machine-gun experiment consisted of a 2-day trial cycle 

comprising of a defensive day and an offensive day. The defensive day involved four 

subtasks: a 7.2-km forced march, M2 engagement, displacement, and mount/dismount 

drill. The offensive day involved five subtasks based around supporting a squad attack: 

1-km movement, movement and occupy a SBF position, displacement, repel a 

counterattack, and CASEVAC. During the course of the experiment, the PIMG squad

executed 2 pilot trial cycles and 21 record trial cycles. During trial execution, Marines 

rotated through every billet within the machine-gun squad, carrying components of the 

crew-served load.

G.2 Limitations 

G.2.1 Limitations Overview

The GCEITF experiment was designed to allow operationally relevant tasks to occur as 

naturally as possible, while gathering unbiased measurements. Most tasks were 

performed in a similar manner to those in an operational environment. Under certain 

situations, artificial limitations or interruptions were introduced that changed or altered 

the way a task would normally be performed. While these limitations represent a 

degree of artificiality, they do not detract significantly from our abilities to generalize the 

conclusions of this experiment to the performance of Marines in a field environment. 

The following limitations were observed for PIMG assessment. 

G.2.2 Relative Difficulty of Record Test

The PIMG GCEITF assessment was designed to gather data associated with some of 

the most physically demanding tasks that an open MOS Marine could perform when 

assigned to an Infantry unit with the collateral responsibilities as a machine-gunner. 

These tasks in isolation do not fully replicate life experienced by a Marine during a 

typical FEX or a combat environment and did not obtain the maximum cumulative load 

that could be placed on a Marine assigned to a ground combat element. With limited 

time available, only selective tasks were assessed. Other tasks/duties outside of the 

assessment were minimized due to specific experimental constraints and human 

factors. During a typical FEX, it is common for Marines to conduct 24-hour operations 

that include day and nighttime operations/patrols, standing firewatch or a security post, 

and conducting continuing tactical actions. The offensive day SOM took squads 

approximately 1 hour to complete, and the defensive day SOM took approximately 3 
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hours to complete. Outside the assessed trials, there were minimal tasks required of 

the volunteers that demanded any degree of physical strain.

Another concern in designing the PIMG assessment was making it was achievable and 

sustainable for a 60-day period. The 7-km forced march distance was selected based 

on the training time available prior to the assessment. However, many of the loads 

carried were decreased; the crew-served load was altered from the M2 heavy machine

gun to the M240B medium machine gun. Marines were authorized 1 day off after every 

4 days of training; this artificial recovery period is not achievable when conducting 

training or combat operations.

A final factor affecting the relative difficulty of the record test pertains to the intangible 

physiological impact of the volunteers’ ability to DOR at any point during a trial. Any

time a volunteer dropped during a trial cycle, that squad performed the following 

subtasks with fewer personnel. This factor could have affected the cohesion of each 

squad and influenced its performance.

G.2.3 Geometries of Fire and Conditions Set 

Several artificialities were present during the M240B live-fire portion of the assessment. 

Although the SBF position was realistic, the geometries of fire for the initial and 

secondary position were offset to prevent fires from interfering with the rifle-squad 

assessment. The PIMG course of fire began when they reached the SBF position, 

rather than waiting for the tactical conditions to be established. The loss of tactical 

realism in basing fires off a maneuver element resulted in this task being less 

challenging than in training or combat, in which the squad leader and gunner must 

make intuitive decisions regarding rates of fire, target precedence, and shifting and 

ceasing fire criteria.

G.2.4 Number of Volunteer Participants

For the PIMG experiment, four male and four female volunteers began the experiment, 

but by the end three males and four females completed the assessment. The results 

presented in this annex are based on the performance of 7 to 8 Marines. 

G.2.5 PIMG Limitations Summary

The PIMG assessment was designed to replicate realistic training in a field 

environment. The end-state was to create an experiment in which the volunteers felt 

they were conducting realistic and operationally relevant tasks, but unavoidable

limitations to the assessed tasks and non-assessed operating environment introduced a 

level of artificiality not normally present in a field training or combat environment. 
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G.3 Deviations 

G.3.1 M2 Heavy Machine-gun Employment

The EAP stated that just prior to the M2 .50-cal engagement, the Marines would be 

assessed moving the M2 and ammunition approximately 100 meters to the firing line. 

Discussion with Company leadership about the relevancy of this subtask informed the 

decision not to make the emplacement a timed event, but to administratively move the 

M2 to the firing line. This subtask was not assessed as a standalone measurement.

G.4 Data Set Description 

G.4.1 Data Set Overview

The PIMG portion of the experiment consisted of 2 pilot trial cycles and 21 record trial

cycles. The pilot trial cycles were conducted from 2 to 6 March 2015. Pilot trial cycle

data are not used in analysis due to variations in the conduct of the test. We based all 

analysis on the 21 record trial cycles executed from 7 March to 26 April 2015.

G.4.2 Record Test Volunteer Participants

At the beginning of the first record trial, there were four male PIMG volunteers and four 

female volunteers. There was one male DOR.

G.4.3 Planned, Executed and Analyzed Trial Cycles

Table G-1 displays the number of trial cycles planned, executed and analyzed by task. 

The planned number of trial cycles for the PIMG MOS per Section 7.5.3 of the GCEITF

EAP is 78 trial cycles or 26 per planned integration level (C, LD, and HD). The plan 

called for 4 squads per day over the 20 trial cycles. Due to the number of Marines who 

voluntarily withdrew or were involuntarily withdrawn from the experiment prior to the 

execution of the first record trial cycle, only one squad of the C and HD integration 

levels remained. The planned number of trial cycles in Table G-1 reflects 21 planned 

trial cycles for each integration level.

Of note, there are several occurrences of missing data for the 7-km hike by individual 

kilometer. The individual kilometer times were derived from GPS data. Early in the 

experiment, the Garmin GPS’s were set to record a volunteer’s position every second. 

Due to the storage space on the GPS and length of the trial when volunteers executed 

the 7-km hike and then follow-on tasks, the GPS could not hold all of the data and 

overwrote the hike data. Once the problem was found, the GPS’s were corrected to 

record location every 2 seconds. 
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Table G-1. PIMG Planned, Executed, and Analyzed Trial Cycles1

Task and 

Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

Trials 

Conducted 

Number of 

trials used 

in analysis

Notes

7-km Hike C 21 19 19

HD 21 21 21

M240B 

Movement & 

Emplacement

C 21 19 19

HD 21 21 21

M240B 

Engagement

C 21 19 17 TIR: Apr 7, Apr 12

HD 21 21 20 TRACR malfunction Apr 12

CASEVAC C 21 19 18 Task failure-Mar 8

HD 21 21 19 Task failure-Mar 10, Mar 18

M2 

Mount/Dismount

C 21 19 19

HD 21 21 21

M240B Displace 

to LOA

C 21 19 19

HD 21 21 20 High outlier: Mar 8

M2 

Displacement

C 21 19 18 High outlier: Apr 11

HD 21 21 21

1-km Hike C 21 19 19

HD 21 21 21

7-km Hike; 1km 

Time

C 21 19 19

HD 21 21 17 No data: Mar 7, Mar 9, Mar 12, 

Mar 14

7-km Hike; 2km 

Time

C 21 19 19

HD 21 21 17 No data: Mar 7, Mar 9, Mar 12, 

Mar 14

7-km Hike; 3km 

Time

C 21 19 17 High outlier: Mar 7, Apr 11

HD 21 21 16 High outlier: Apr 3; No data: Mar 7, 

Mar 9, Mar 12, Mar 14

7-km Hike; 4km 

Time

C 21 19 18 High outlier: Mar 7

HD 21 21 18 Low outlier: Apr 3; No data: Mar 7, 

Mar 12

7-km Hike; 5km 

Time

C 21 19 19

HD 21 21 19 No data: Mar 7, Mar 12

7-km Hike; 6km 

Time

C 21 19 19

HD 21 21 19 High outlier: Apr 18; No data: Mar 

7

7-km Hike; 7km 

Time

C 21 19 19

HD 21 21 20 No data: Mar 7

M240B 

Movement

C 21 19 19

HD 21 21 21

M240B 

Emplacement

C 21 19 19

HD 21 21 20 Low outlier: Mar 18

M240B Attack 

Hits on Target

C 21 19 17 TRACR malfunction: Apr 12; TIR: 

Apr 7

HD 21 21 20 TRACR malfunction: Apr 12

M240B 

Counterattack 

hits on Target

C 21 19 16 TRACR malfunction: Apr 12; 

Missing Apr 2; TIR: Apr 7

HD 21 21 20 TRACR malfunction: Apr 12

Mount M2; C 21 19 19

 

1 A TIR in this table refers to a Test Incident Report, which is a report the test team or direct assignment 

leaders completed when an incident occurred that affected the natural execution of a trial. If a data point 

is removed due to a TIR, it is because the TIR affected the data in such a way that it is not comparable to 

the rest of the data set.
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Task and 

Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

Trials 

Conducted 

Number of 

trials used 

in analysis

Notes

Elapsed Time HD 21 21 21

Dismount M2; 

Elapsed Time

C 21 19 19

HD 21 21 21

M2 

Engagement

C 21 19 19

HD 21 21 21

G.5 Descriptive and Basic Inferential Statistics 

G.5.1 Descriptive Statistics Overview

Performance metrics were measured during the conduct of common infantry tasks and 

are indicative of unit-level proficiency during either field exercises or combat operations. 

This section presents results for 7 out of 16 tasks. The Appendix to this Annex contains 

the descriptive statistics for the remainder of the PIMG tasks. The words “metric” and 

“task” are used interchangeably throughout this Annex; both refer to the experimental 

task. 

Each machine-gun squad consisted of three volunteer Marines: the gunner, assistgunner, and ammo man. A direct assignment (non-volunteer) squad leader led each 

squad. There were two integration levels for all tasks. A C group was all male and a

HD group had three females.

This section includes experimental results based on descriptive statistics, analysis of 

variance (ANOVA) (or non-parametric tests as necessary), and scatter plots. The 

subsequent sections will cover each task in detail. Lastly, contextual comments, 

additional insights, and subjective comments (as applicable) tying back to each 

experimental task are incorporated. 

Use caution when comparing similar tasks executed by different MOSs within the 

GCEITF experiment. Comparative analysis may be misleading due to differing factors 

between MOS tasks, such as distances, techniques, leadership, load carried, group 

size, and group composition.

G.5.2 PIMG Selected Tasks Overview

The two tables below display the results for the seven selected PIMG metrics. Table 

G-2 displays the metrics and integration levels with their respective sample sizes, 

means, and standard deviations. Table G-3 displays ANOVA results, including metrics

and integration levels, p-values suggesting statistical significance, integration level 

elapsed-time differences, and percentage differences between integration levels. For 

each task, an ANOVA and t-test were conducted to compare the two groups. If nonparametric tests were needed, Table G-3 displays these results instead of ANOVA and 

t-test results. If p-values are less than the a-priori determined significance level of 0.10, 

we conclude that there is statistical evidence that the response for the HD group is 

different from that in the C group.
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Table G-2. PIMG Selected Task Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD 

7-km Hike (minutes)*

C 19 103.34 8.68

HD 21 128.96 14.19

M240B Movement & Emplacement

(minutes)* 

C 19 3.81 0.43

HD 21 4.38 0.48

M240B Engagement (% hits)

C 17 32.31% 15.61%

HD 20 31.71% 9.60%

CASEVAC (minutes)*

C 18 4.04 1.61

HD 19 6.55 2.21

M2 Mount/Dismount

(minutes)* 

C 19 6.00 0.82

HD 21 5.47 0.80

M240B Displace to LOA (minutes)*

C 19 4.98 0.44

HD 20 5.87 0.85

M2 Displacement (minutes)*

C 18 1.71 0.26

HD 21 1.98 0.59

M2 Displacement [excluding potential 

influential point] (minutes)*

C 18 1.71 0.26

HD 20 1.88 0.41

*Indicates there is a statistically significant difference, in either a one-sided or 

two-sided hypothesis test, between integration levels according to ANOVA or a 

non-parametric equivalent test.

Table G-3. PIMG Selected Task ANOVA and Welch’s T-test Results

Metric

F 

Statistic 

(df)

F Test 

PValueComparison Difference % 

Difference

2-sided 

P-Value

1-

sided 

PValue 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

7-km Hike 

(minutes)*

46.22 

(1, 38) < 0.01* HD-C 25.62 24.79% < 0.01* < 0.01* 20.81 30.43 19.39 31.85

M240B 

Movement & 

Emplacement

(minutes)*

15.77 

(1, 38) < 0.01* HD-C 0.57 15.10% < 0.01* < 0.01* 0.39 0.76 0.33 0.82

M240B 

Engagement (% 

hits)

0.02 

(1, 35) 0.89 HD-C -0.01 -1.87% 0.89 0.45 -0.06 0.05 -0.08 0.07

CASEVAC 

(minutes)*

15.42 

(1, 35) < 0.01* HD-C 2.51 62.10% < 0.01* < 0.01* 1.68 3.34 1.44 3.58

M2 

Mount/Dismount 

(minutes)*

4.26 (1, 

38) 0.05* HD-C -0.53 -8.84% 0.05* 0.02* -0.87 -0.19 -0.96 0.98

M240B Displace 

to LOA 

(minutes)*

16.67 

(1, 37) < 0.01* HD-C 0.89 17.91% < 0.01* < 0.01* 0.61 1.17 0.53 1.26

M2 

Displacement 

(minutes)*

2.68†† 0.10†† HD-C 0.27 15.79% 0.10† 0.05† 0.05† 0.28† 0.00† 0.33†

M2 

Displacement 

[excluding 

2.41 

(1, 36) 0.13 HD-C 0.18 10.25% 0.13 0.06* 0.03 0.32 -0.01 0.36
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Metric

F 

Statistic 

(df)

F Test 

PValueComparison Difference % 

Difference

2-sided 

P-Value

1-

sided 

PValue 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

potential 

influential 

point] (minutes)

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test. 

†Results presented are from a Mann-Whitney non-parametric test due to non-normality.

††Indicates results presented are from Robust ANOVA due to unequal variances. The reported Fstatistic is a Chi-square statistic from Robust ANOVA, and the F-test p-value is the Robust ANOVA pvalue. 

G.5.2.1 7-km Hike

G.5.2.1.1 7-km Hike Overview

This experimental task assessed a squad of three Marines moving 7.20 km while each 

Marine carried an approach load, and individual weapon (M-4), and a portion of the 

crew-served weapon load. The crew-served load consisted of an M240B medium 

machine gun, tripod, A-bag with spare barrel, and four cans of ammo resulting in a 

cumulative load of 118-130 lb per Marine. The recorded time for this task started when 

the squad departed the Range 107 start point and stopped when the squad arrived at 

the Range 110 stop point.

Figure G-1 displays all PIMG 7-km hike data. All data on the scatter plot are valid for 

analysis.
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Figure G-1. 7-km Hike

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.13 for the C group and 0.32 for the HD group.

The C group had a mean time of 103.34 minutes. This time is statistically significantly 

faster than the HD mean time of 128.98 minutes. This difference results in a 24.79%, or 

25.62-minute, degradation in hike time between the groups. The HD group had greater 

variability in times, as shown by the 5.51-minute increase in standard deviation (SD) 

(8.68 minutes for the C group and 14.19 minutes for the HD group). See Table G-2 and 

Table G-3 for detailed analytical results.

G.5.2.1.2 7-km Hike Contextual Comments

G.5.2.1.2.1 USMC Hike Standards

The 7-km hike is a task that the following MOSs completed during the experiment: 

0311, 0331, 0341, 0351 and 0352, PI, Provisional Machine Gunners, and Combat 

Engineers. There are varying standards to which we can compare this result. The 

following sections define those standards as well as the one we choose as a 

comparison.

The Infantry T&R Manual (30 Aug 2013) identifies minimum standards that Marines 

must be able to perform in combat, to include standards for tactical marches. In 

Chapter 8 of the Infantry T&R Manual in the MOS 0300 Individual Events section, task 

“0300-COND-1001: March under an approach load” is applicable to all 03XX MOSs, 

ranks PVT – LtCol. The condition and standard established by this task is: “Given an 
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assignment as a member of a squad, individual weapon, and an approach load, 

complete a 20 kilometer march in under 5 hours.” The march pace required by this 

standard is 4 kilometers per hour (km/h). In Chapter 9 of the Infantry T&R Manual in the 

MOS 0302/0369 Individual Events section, tasks “0302-OPS-2001: Lead an approach 

march” and “0369-OPS-2501: Lead an approach march” are applicable to MOS 0302 

and 0369, ranks SSgt – MGySgt and 2ndLt – LtCol. The condition and standard 

established by these tasks is: “Given a mission, time constraints, an approach march 

load, organic weapons, and a route, move 24.8 miles (40 km) in a time limit of 8 hours.” 

The march pace required by this standard is 5 km/h. Appendix E of the Infantry T&R 

Manual (Load Terms and Definitions) states: “The approach march load will be such 

that the average infantry Marine will be able to conduct a 20 mile hike in 8-hours with 

the reasonable expectation of maintaining 90% combat effectiveness.” The march pace 

required by this definition is 4.02 km/h.

Chapter 3 of Fleet Marine Force Reference Publication (FMFRP) 3-02A, Marine 

Physical Readiness Training for Combat (16 Jun 2004) states: “The normal pace is

30 inches. A pace of 30 inches and a cadence of 106 steps per minute result in a 

speed of 4.8 km/h or 3 mi/h and a rate of 4 km/h or 2.5 mi/h if a 10-minute rest halt per 

hour is taken.” Common Infantry practice today is to hike for 50 minutes and take a 10-

minute break, while maintaining an overall pace of 4 km/h (resulting in a hiking pace of 

4.8 km/h). 

Driven by the need to pick an evaluative reference standard, this report follows the T&R 

Manual’s intent to establish minimum standards and uses the 4 km/h march pace for a 

20 km march established by task 0300-COND-1001 and supported by the definition of 

an approach load. Further, while an established reference standard is required to 

anchor observed performance to the T&R program, more important information is 

provided by performance differences observed between gender integrated and nongender integrated units.

G.5.2.1.2.2 PIMG 7-km Hike Pace

This result is relevant to the training and combat environments as it will take integrated 

squads more time to conduct foot movements. Per the tactical march standards noted 

above, the Marine Corps standard of hiking is 4.0 km/h. The HD groups failed to meet 

this standard. The C group average pace was 4.18 km/h; the HD group average pace 

was 3.35 km/h, finishing 25.62 minutes behind the C group. To extrapolate this pace 

over a 20-km movement (an optimistic assumption that does not account for any further 

degradation of performance), it would take the C group 4.78 hr and the HD group 

5.97 hr to complete the movement, meaning the HD group would finish 71.4 minutes 

behind the C group. 

Furthermore, on any given day (under the same environmental conditions), the C group 

was faster than the HD group 100% of the time (19 of 19 trial cycles). 
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G.5.2.1.3 7-km Hike Additional Insights 

A 25.62-minute difference in the 7-km hike for machine-gun squads is statically 

significant and operationally relevant, based on the fact that the HD group failed to meet 

the USMC standard of 4 km/h. Based on the USMC standard of a 4 km/h pace over a 

7.20-km route (which would result in a 108-minute hike completion time over the 7.20 

km), the HD group was 20.96 minutes slower than that standard.

Marine Corps Doctrinal Publications (MCDP) consistently emphasize the importance of 

speed. MCDP 1-3 Tactics devotes an entire chapter to “Being Faster” and states, 

“Physical speed, moving more miles per hour, is a powerful weapon in itself.” MCDP-6 

Command and Control also speaks to speed relative to the enemy and states, “The 

speed differential does not necessarily have to be a large one: a small advantage 

exploited repeatedly can quickly lead to decisive results.” Further insights may be 

gleaned from the Appendix, which shows the difference in speed by kilometer. In 

general, the difference in performance increased as the movement got longer.

G.5.2.1.4 7-km Hike Subjective Comments

For subjective comments relating to this task, see the Appendix. 

G.5.2.2 M240B Movement & Emplacement

G.5.2.2.1 M240B Movement & Emplacement Overview

This experimental task assessed the time for a 3-Marine squad to move approximately 

100 meters to a SBF position and prepare the M240B medium machine gun for firing. 

This task was conducted immediately after completing a 1-km movement. The 

recorded time started immediately upon completing the 1-km movement and stopped 

when the gunner yelled “Gun up,” indicating that it was ready to fire. During 

emplacement, the squad assembled the M240, checked headspace and timing, and 

loaded the source of ammunition. A direct-assignment squad leader verified all 

procedures.

Figure G-2 displays all PIMG M240B Movement & Emplacement data. All data on the 

scatter plot are valid for analysis.
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Figure G-2. M240B Movement & Emplacement

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.34 for the C group and 0.40 for the HD group.

The C group had a mean time of 3.81 minutes. This time is statistically significantly 

faster than the HD mean time of 4.38 minutes. This difference results in a 15.10%, or 

0.57-minute, degradation in time. See Table G-2 and Table G-3 for detailed analytical 

results. 

G.5.2.2.2 M240 Movement & Emplacement Contextual Comments 

This result is relevant to the combat environment, as it will take integrated squads more 

time to move and initiate supporting fires. On average, it took the HD group 34 seconds 

longer to conduct this movement and emplacement. On any given day (under the same 

environmental conditions), the C group was faster than the HD group 84.2% of the time 

(16 of 19 trial cycles).

G.5.2.2.3 M20B Movement & Emplacement Additional Insights 

A purely objective evaluation of 34 seconds is elusive but may possess some practical 

significance on the battlefield that would reduce the survivability of an integrated squad. 

Considering the 650 rounds-per-minute sustained rate of fire for the Russian RPK-47 

machine gun, a single enemy machine-gun squad would have the opportunity fire 368 

rounds against the pinned down squad prior to the initiation of friendly suppression by 

an integrated squad. The resultant trade in casualty exchange could be significant.
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G.5.2.2.4 M240B Movement & Emplacement Subjective Comments 

For subjective comments relating to this task, see the Appendix. 

G.5.2.3 M240B Engagement

G.5.2.3.1 M240B Engagement Overview

This experimental task assessed the accuracy of a medium machine-gun squad 

engaging GTSs with 400 rounds during an attack and 200 rounds during a 

counterattack. Machine-gun squads engaged three GTSs during the attack and two 

during the counterattack. Each GTS captured the precise location of a round that 

passes within 3 meters of the location of hit and miss (LOMAH) sensor. A significant 

limitation of the GTS was that it did not capture any data that impacted the low (the 

berm of the target). The accuracy was determined by dividing the number of rounds 

detected on each target by the total amount of ammunition expended by each squad.

Figure G-3 displays all PIMG M240B Engagement data. All data on the scatter plot are 

valid for analysis.

Figure G-3. M240B Engagement

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.61 for the C group and 0.11 for the HD group. See Table G-2 and Table 

G-3 for detailed analytical results.

The C group had an average percent hit of 32.31%. This percentage is higher (but not 

statistically significantly) than the HD average of 31.71%. This difference in probability 

results in a 1.87%, or 1-percentage point, degradation in accuracy. The HD group was 
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less variable than the C group, as shown by the 6.01-percentage point decrease in SD 

(15.61% for the C group and 9.60% for the HD group). 

G.5.2.3.2 M240B Engagement Contextual Comments 

In combat operations, accuracy is highly desirable in destroying or effectively 

suppressing an enemy position. On average, the HD group was only 0.6% less 

accurate than the C group.

G.5.2.3.3 M240B Engagement Additional Insights 

The overall accuracy of each group had a downward (negative) trend over the course of 

the experiment. One would have expected the accuracy to improve over time. This can 

be attributed to a loss in interest due to the repetitive nature of the task and a lack of 

feedback to the volunteers.

G.5.2.3.4 M240B Engagement Subjective Comments

For subjective comments relating to this task, see the Appendix. 

G.5.2.4 CASEVAC

G.5.2.4.1 CASEVAC Overview

This experimental task assessed the machine-gun squad’s ability to move a 220-lb. 

dummy a distance of 100 meters to a CCP while wearing an assault load, individual 

weapon (M4), and the M240B crew-served load. Squads could use a variety of 

techniques, but they had to move all personnel and gear the entire distance, as well as 

carry the dummy off the ground. The machine-gun squad conducted this task at the 

conclusion of the counterattack engagement. Techniques varied between the 1-Marine 

(fireman) and 2-Marine carry. The recorded time started when Marines touched the 

dummy and stopped when the dummy and all members of the squad arrived at the 

CCP. 

Figure G-4 displays all PIMG CASEVAC data. All data on the scatter plot are valid for 

analysis.
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Figure G-4. PIMG CASEVAC

Figure 4. PIMG CASEVAC Plot

The data are normally distributed, as evidenced by the Shapiro-Wilk Test that resulted 

in a p-value of 0.34 for the C group and 0.18 for the HD group.

The C group had a mean time of 4.04 minutes. This time is statistically significantly 

faster than the HD mean time of 6.55 minutes. This difference results in a 62.10%, or 

2.51-minute, degradation in CASEVAC time. Additionally, the HD had more variability, 

as shown by the 0.60-minute increase in SD (1.61 minutes for the C group and 2.21 

minutes for the HD group). See Table G-2 and Table G-3 for detailed analytical results.

G.5.2.4.2 CASEVAC Contextual Comments 

The implications of this task contain relevance to training and combat environments as 

a casualty must be moved expediently to a higher echelon of medical care. The data 

demonstrates that the HD group took 2.5 minutes longer on average than the C group. 

On any given day (under the same environmental conditions), the C group was faster 

than the HD group 87.5% of the time (14 of 16 trial cycles).

G.5.2.4.3 CASEVAC Additional Insights 

While the “Golden Hour” is a common medical planning construct for C2 and logistical 

support, medical literature supports a “Platinum Ten” philosophy of first response. The 

U.S. National Library of Medicine references a French article that espouses, “on the 

battlefield, the majority of casualties die within ten minutes of the trauma.” (Wounded in 

Action: The Platinum Ten Minutes and the Golden Hour, Daban) The fundamental 
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principle is that a patient needs to be correctly triaged and moved to medical care as 

fast as possible. 

G.5.2.4.4 CASEVAC Subjective Comments

For subjective comments relating to this task, see the Appendix. 

G.5.2.5 M2 Mount/Dismount

G.5.2.5.1 M2 Mount/Dismount Overview

This experimental task assessed the machine-gun squad’s ability to mount an M2 heavy 

machine gun onto a tactical vehicle (HMMWV) and then dismount it. A brief, nonassessed administrative pause was conducted between the mounting and dismounting 

sub-tasks. This task was conducted immediately following the M2 live-fire portion of the 

experiment. The recorded time started when Marines touched a component of the M2 

and it stopped when the last component of the M2 was back on the deck. 

Figure G-5 displays all PIMG M2 Mount/Dismount data. All data on the scatter plot are 

valid for analysis.

Figure G-5. M2 Mount/Dismount

The data are normally distributed, as evidenced by the Shapiro-Wilk Test that resulted 

in a p-value of 0.30 for the C group and 0.22 for the HD group.

The C group had a mean time of 6 minutes. This time is statistically significantly slower 

than the HD mean time of 5.47 minutes. This difference results in a 8.84%, or 
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0.53-minute, improvement in mount/dismount time. See Table G-2 and Table G-3 for 

detailed analytical results.

G.5.2.5.2 M2 Mount/Dismount Contextual Comments 

The challenging aspect of mounting and dismounting the M2 heavy machine gun is the 

weight of the components. On average, it took the HD group 32 seconds longer than 

the C group. On any given day (under the same environmental conditions), the HD 

group was faster than the C group 52.6% of the time (10 of 19 trial cycles).

G.5.2.5.3 M2 Mount/Dismount Additional Insights 

This task began with all the equipment prestaged on the deck within 2 meters of the 

HMMWV. The Marines were not required to move the components to/from a secured 

location (armory). For an indication of the performance when moving heavy objects, 

see the TOW Engagement data, which involved moving a 50-lb missile a distance of 

100 meters. An interesting comparison can be made to the 0331 squads. For 

unexplainable reasons, the PIMG C group was, on average, 2.05 minutes slower than 

the 0331 C group.

G.5.2.5.4 M2 Mount/Dismount Subjective Comments

For subjective comments relating to this task, see the Appendix. 

G.5.2.6 M240B Displace to LOA

G.5.2.6.1 M240B Displace to LOA Overview

This experimental task assessed a medium machine-gun squad moving approximately 

300 meters to an LOA immediately after engaging targets from a SBF position. The 

recorded time started when the squad was told to displace and stopped when the tripod 

was down at the LOA.

Figure G-6 displays all PIMG M240B Displace to LOA data. The HD data point on trial 

cycle one was a high outlier based on a trial anomaly and removed from analysis. All 

other data on the scatter plot are valid for analysis.
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Figure G-6. M240B Displace to LOA

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.53 for the C group and 0.55 for the HD group. 

The C group had a mean time of 4.98 minutes. This time is statistically significantly 

faster than the HD mean time of 5.87 minutes. This difference results in a 17.97%, or 

0.89-minute, degradation in movement time. Additionally, the HD had more variability 

as shown by the 0.41-minute increase in SD (0.44 minutes for the C group and 0.85 

minutes for the HD group). See Table G-2 and Table G-3 for detailed analytical results.

G.5.2.6.2 M240B Displace to LOA Contextual Comments

The ability to close with the objective after having conducted an attack is a crucial 

aspect to maintaining the momentum during offensive operations. On average, the HD 

group took 53.4 seconds longer, which results in that much less time to prepare for a 

counterattack. Based on the standard deviations, the variation in performance of the 

HD group is nearly than twice as much as the variation in performance of the C group. 

This inconsistency in the performance of the integrated squads leads to greater 

uncertainty and less confidence in their future performance from the mean.

G.5.2.6.3 M240B Displace to LOA Additional Insights

A purely objective evaluation of 53-second average delay is elusive but may possess 

some practical significance on the battlefield that would reduce the survivability of an 

integrated squad. Considering the 650 rounds-per-minute sustained rate of fire for the 

Russian RPK-47 machine gun, a single enemy machine-gun squad would have the 

opportunity fire 578 rounds against an integrated squad while moving to the LOA and 
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exposed to enemy fire. Similarly, the integrated squad would have that much less time 

to provide reinforcing fires against an enemy counterattack. The resultant trade in 

casualty exchange could be significant.

G.5.2.6.4 M240B Displace to LOA Subjective Comments

For subjective comments relating to this task, see the Appendix. 

G.5.2.7 M2 Displacement

G.5.2.7.1 M2 Displacement Overview

This experimental task assessed the machine-gun squad’s ability to move an M2 heavy 

machine gun approximately 100 meters from a firing position to a rally point. The 

recorded time started when the machine-gun squad yelled “Out of action” and the time 

stopped when the entire squad arrived at the rally point.

Figure G-7 displays all PIMG M2 displacement data. There was one influential point: 

the HD on trial cycle 1. Because the impact of this point is unknown, we perform all 

analysis with and without this point. The C on trial cycle 15 is an outlier due to unit 

attrition and excluded for analysis. The data point with the thin circle is the influential 

point, and the data point with the thicker circle is the outlier. With the exception of the C 

group data point on trial cycle 15, all data on the scatter plot are valid for analysis.

Figure G-7. M2 Displacement with Potential Influential Point Circled

The inclusion of the potential influential points does not change the statistical 

significance between groups. It does change the SD and percent differences between 

the integration levels. Once we remove the potential influential points, the percent 
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difference between the C group and HD group decreases. The SD for the HD groups 

decreases without the potential influential point. Additionally, the removal of the 

potential influential points results in the data for HD group being normally distributed. 

The following sections discuss results with and with the potential influential points.

G.5.2.7.1.1 M2 Displacement Descriptive Statistics with Potential Influential Points 

The data for the C group are normally distributed as evidenced by the Shapiro-Wilk Test 

that resulted in a p-value of 0.64 but not normally distributed for the HD group, which 

had a p-value of <0.01. We proceed with presenting ANOVA results because they were 

confirmed by a Mann-Whitney Test with a two-sided p-value of 0.10 (0.05 for a onesided).

The C group had a mean time of 1.71 minutes. This time is statistically significantly 

faster than the HD mean time of 1.98 minutes. This difference results in a 15.79%, or 

0.27-minute, degradation in displacement time. Additionally, the HD had more 

variability as shown by the 0.33-minute increase in SD (0.26 minutes for the C group 

and 0.59 minutes for the HD group). See Table G-2 and Table G-3 for detailed 

analytical results.

G.5.2.7.1.2 M2 Displacement Descriptive Statistics without Potential Influential Points 

The data are normally distributed as evidenced by the Shapiro-Wilk Test that resulted in 

a p-value of 0.64 for the C group and 0.03 for the HD group.

Without the influential point, the HD group mean time was 1.88 minutes. The C group is 

statistically significantly faster in a one-sided test. This difference results in a 10.25%, 

or 0.18-minute, degradation in displacement time. Additionally, the HD group had more 

variability as shown by the 0.15-minute increase in SD (0.26 minutes for the C group 

and 0.41 minutes for the HD group). See Table G-2 and Table G-3 for detailed 

analytical results.

G.5.2.7.2 M2 Displacement Contextual Comments 

After an engagement, a machine-gun squad must be able to breakdown their weapon 

system and move to a position of cover as rapidly as possible. On average, the HD 

group took 16 seconds longer, which results in being exposed to the enemy that much 

longer. Based on the standard deviations, the variation in performance of the HD group 

is nearly than twice as much as the variation in performance of the C group. This 

inconsistency in the performance of the integrated squads leads to greater uncertainty 

and less confidence in their future performance from the mean.

G.5.2.7.3 M2 Displacement Additional Comments 

One interesting comparison can be made between this task and the PIMG M240B 

Displacement. The PIMG M2 Displacement involved a shorter movement of 100 meters

with a heavier load versus the PIMG M240B Displacement that involved a longer 
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movement of 300 meters with a lighter load. The data reveals roughly the exact same 

result: a 15.79% difference and 17.91% difference, respectively, between the two 

different tasks.

G.5.2.7.4 M2 Displacement Subjective Comments

For subjective comments relating to this task, see the Appendix. 

G.6 Statistical Modeling Results 

G.6.1 Statistical Modeling Results Overview

The previous section discussed results only as they pertain to differences due to 

integration level alone. The goal of statistical modeling, as applied here, is to estimate, 

simultaneously, the effect of gender-integration levels and other relevant variables on 

squad performance. Refer to the Methodology Annex for a broad overview of the 

analysis plan and the variables used in the models.

For the same seven selected tasks described in the previous section, this section 

presents an overview of the analysis and results, and then presents the modeling 

results for each of the tasks.

For each task, we describe the significant variables in the model and whether these 

variables are either positively or negatively correlated with the result. A negative 

correlation indicates an increase in that variable will result in a decrease in the response 

variable, which is a desired outcome for elapsed time but not a desired outcome for the 

percent hits outcome. The results report where certain patch numbers are significant 

for a given variable. The experiment tracked Marines within the machine-gun squad by 

a patch number that associated their random position within the squad to a specific 

billet. Table G-4 displays the patch numbers and associated billet titles for the machinegun squad.

Table G-4. Patch Numbers and Billet Titles for the Machine-gun Squad

Patch Number Billet Title

1 Gunner

2 Assistant Gunner

3 Ammo Man

G.6.2 PIMG Selected Tasks Method of Analysis

Due to the small number of trials, a mixed effects model with all machine-gun squad

members and all types of personnel data does not work for the PIMG data set. Thus, 

we model each personnel variable with integration level separately with a random effect 

for who filled each position within the machine-gun squad. For example, age for each 

member of the machine-gun squad (three variables), a random effect for who filled each 
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billet, and integration level are modeled with the result (response time or percentage 

hits) as the response variable. Where maximum likelihood estimation converged, AIC 

was used for variable selection. Otherwise, we comment on the significance of 

individual variables in the full model. Variables reported as significant are concluded to 

be significant based on at least a one-sided test.

G.6.3 PIMG Selected Tasks Overall Modeling Results

The weight for the entire machine-gun squad appears in the final reduced mixed effects 

model for the CASEVAC and M2 displacement with the potential influential point 

included. Weight is negatively correlated with the CASEVAC time but positively 

correlated with the M2 displacement time. The weight of each member of the machinegun squad is highly correlated with integration level. 

Rifle score for the entire machine-gun squad appears in the final reduced mixed effects 

model for the 7-km hike and M240B movement and emplacement and is positively 

correlated with both of these results. The rifle score for each patch number is highly 

correlated with integration level. The positive correlation with the response variable 

does not make sense from a theoretical perspective. Use caution when interpreting 

these results.

Integration level is significant for the M2 mount/dismount and M240B displace to LOA. 

For each task, modeling the random effects for the individuals participating in the task 

resulted in changes from the initial results in the descriptive statistics. Each respective 

task paragraph describes these changes.

The M240 engagement and M2 displacement without the potential influential point did 

not have a final model with any significant variables. Refer to Section G.5.2.3 and 

Section G.5.2.7.1.2, respectively, for these tasks’ ANOVA results.

G.6.3.1 7-km Hike

We model elapsed time for the 7-km hike as a function of each personnel variable and 

integration level in a separate mixed effects model with a random effect for who filled 

each position within the machine-gun squad. The covariates in each model are the 

values of each personnel variable for each patch number. For each model, we report 

statistically significant positive and negative correlations and whether we observe any 

patterns.

The models for the following variables do not run due to missing values:

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• Squad leader,
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• Age,

• Height,

• AFQT score,

• CFT MTC,

• CFT MANUF,

• PFT crunches,

• PFT 3-mile run.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables:

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the 7-km hike time:

• GT score of patches 2 and 3,

• PFT crunches of patch 1,

• PFT 3-mile run of patches 1 and 2,

• Rifle score of patches 1, 2 and 3.

The following personnel variables are significant in their respective models and are 

negatively correlated with the 7-km hike time:

• Age of patch 1,

• Height of patches 1 and 3,

• Weight of patches 1, 2, and 3,

• CFT MTC of patch 1,

• CFT MANUF of patch 1.

The following personnel variables have no significant variables in their respective 

models:

• None

Because weight and rifle score were significant for all Marines, we fit a final mixed 

effects model with integration level, a random effect for who filled each billet, weight and 

rifle score. Table G-5 displays the coefficients and standard errors for the final model 

based on AIC results. All three weights are highly correlated (~0.76) with integration 

level, and all three rifle scores are highly correlated (~0.75) with integration level. Given 
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the highly significant ANOVA results when treating integration level as the lone factor 

and considering the limited sample size of integrated squads, it calls into question the 

validity of the reduced model that includes the rifle score of all individuals. The positive 

relationship between rifle score and 7-km hike time does not make sense from a 

theoretical perspective. We report results for completion; however, use caution when 

interpreting the results.

Table G-5. Coefficients and Standard Errors for the Final 7-km Hike Model

Effect Estimate Std. Error

Rifle score patch 1 0.55 0.13

Rifle score patch 2 0.42 0.14

Rifle score patch 3 0.47 0.13

G.6.3.2 M240B Movement & Emplacement

We model elapsed time for the M240B movement and emplacement as a function of 

each personnel variable and integration level in a separate model in a mixed effects 

model where the random effect is who filled each position within the machine-gun

squad. The covariates in each model are the values of each personnel variable for 

each patch number. For each model, we report statistically significant positive and 

negative correlations and whether we observe any patterns.

The models for the following variables do not run due to missing values:

• None

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• Squad leader,

• Age,

• Height,

• Weight,

• AFQT score,

• PFT crunches,

• PFT 3-mile run.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables:

• None.
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The following personnel variables are significant in their respective models and are 

positively correlated with the M240 movement and emplacement time:

• Age of patch 3,

• Weight of patch 3,

• CFT MTC of patch 3,

• Rifle score of patches 1, 2, and 3.

The following personnel variables are significant in their respective models and are 

negatively correlated with the M240B movement and emplacement time:

• None.

The following personnel variables have no significant variables in their respective 

models:

• GT score,

• CFT MUF.

Because rifle score was significant for all Marines, we fit a final mixed effects model with 

integration level, a random effect for who fills each billet, and rifle score. Table G-6

displays the coefficients and standard errors for the final model based on AIC results. 

All three rifle scores are highly correlated (~0.75) with integration level. Given the highly 

significant ANOVA results when treating integration level as the lone factor and 

considering the limited sample size of integrated squads, it calls into question the 

validity of the reduced model that includes the rifle score of all individuals. The positive 

relationship between rifle score and M240 movement and engagement time does not 

make sense from a theoretical perspective. We report results for completion; however, 

use caution when interpreting the results.

Table G-6. Coefficients and Standard Errors for the Final M240B Movement & Emplacement Model

Effect Estimate Std. Error

Rifle score patch 1 0.01 0.005

Rifle score patch 2 0.01 0.005

Rifle score patch 3 0.01 0.006

G.6.3.3 M240B Engagement

We model percent hits for the M240B engagement as a function of each personnel 

variable and integration level in a separate model in a mixed effects model where the 

random effect is who filled each position within the machine-gun squad. The covariates 

in each model are the values of each personnel variable for each patch number. For 

each model, we report statistically significant positive and negative correlations and 

whether we observe any patterns.
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The models for the following variables do not run due to missing values:

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• None.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables:

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the M240B engagement percent hits:

• Squad leader,

• GT score of patch 2,

• PFT 3-mile run of patch 2.

The following personnel variables are significant in their respective models and are 

negatively correlated with the M240B engagement percent hits:

• None.

The following personnel variables have no significant variables in their respective 

models:

• Age,

• Height,

• Weight,

• AFQT score,

• CFT MTC,

• CFT MUF,

• PFT crunches,

• Rifle score.

Because the effects of the personnel variables do not have any patters and their effects 

are often negligible, our final model includes only the intercept, meaning that we could 

not determine a mixed model that fits the data well. Refer to Section G.5.2.3 for this 

task to see the ANOVA result for differences between integration groups.
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G.6.3.4 CASEVAC

We model elapsed time for the CASEVAC as a function of each personnel variable and 

integration level in a separate model in a mixed effects model where the random effect 

is who filled each position within the machine-gun squad. The covariates in each model 

are the values of each personnel variable for each patch number. For each model, we 

report statistically significant positive and negative correlations and whether we observe 

any patterns.

The models for the following variables do not run due to missing values:

• CFT MTC,

• CFT MUF.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• Squad leader,

• Age,

• Height,

• AFQT score,

• PFT crunches,

• PFT 3-mile run,

• Rifle score.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables:

• GT score.

The following personnel variables are significant in their respective models and are 

positively correlated with the CASEVAC time:

• AFQT score of patch 1,

• GT score of patch 1, 2, and 3,

• Rifle score of patch 1.

The following personnel variables are significant in their respective models and are 

negatively correlated with the CASEVAC time:

• Weight of patches 1, 2, and 3.
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The following personnel variables have no significant variables in their respective 

models: 

• None.

Weight and GT score were significant for all Marines. Ideally, we would fit a final mixed 

effects model with integration level, GT and weight. Because GT score is missing for 

several Marines, AIC did not work for this variable. GT score is also highly correlated 

(~0.92) with integration level. Therefore, the final model includes integration level, a 

random effect for who filled each billet, and weight. Table G-7 displays the coefficients 

and standard errors for the final model based on AIC results. Weight is highly 

correlated (~0.90) with integration level. Given the highly significant ANOVA results 

when treating integration level as the lone factor and considering the limited sample size 

of integrated squads, it calls into question the validity of the reduced model that includes 

the weight of all individuals. 

Table G-7. Coefficients and Standard Errors for the Final CASEVAC Model

Effect Estimate Std. Error

Weight patch 1 -0.05 0.01

Weight patch 2 -0.04 0.01

Weight patch 3 -0.03 0.02

G.6.3.5 M2 Mount/Dismount

We model elapsed time for the M2 mount/dismount as a function of each personnel 

variable and integration level in a separate model in a mixed effects model where the 

random effect is who filled each position within the machine-gun squad. The covariates 

in each model are the values of each personnel variable for each patch number. For 

each model, we report statistically significant positive and negative correlations and 

whether we observe any patterns.

The models for the following variables do not run due to missing values:

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• None.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables:

• Squad leader,

• Age,

• Height,
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• AFQT score,

• PFT crunches.

The following personnel variables are significant in their respective models and are 

positively correlated with the M2 mount/dismount time:

• Weight of patches 2 and 3.

The following personnel variables are significant in their respective models and are 

negatively correlated with the M2 mount/dismount time:

• Height of patch 2,

• PFT 3-mile run of patch 1,

• Rifle score of patch 1.

The following personnel variables have no significant variables in their respective 

models:

• GT score,

• CFT MTC,

• CFT MUF.

Because the effects of the personnel variables do not have any patters and their effects 

are often negligible, our final model includes integration level only where HD has a 

difference of -0.50 minutes when compared to a C group and a statistically significant pvalue of 0.06 in a one-sided test. This difference is a decrease from the -0.53-minute 

difference identified in the descriptive statistics, which is a 5.66% change.

G.6.3.6 M240B Displace to LOA

We model elapsed time for the M240B displace to LOA as a function of each personnel 

variable and integration level in a separate model in a mixed effects model where the 

random effect is who filled each position within the machine-gun squad. The covariates 

in each model are the values of each personnel variable for each patch number. For 

each model, we report statistically significant positive and negative correlations and 

whether we observe any patterns.

The models for the following variables do not run due to missing values:

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• Squad leader,

• Height,
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• Weight,

• AFQT score,

• PFT crunches,

• PFT 3-mile run.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables:

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with the M240B displace to LOA time:

• Age of patch 3,

• Height of patch 3,

• Weight of patch 3,

• CFT MTC of patch 3,

• CFT MUF of patch 3,

• PFT 3-mile run of patch 3.

The following personnel variables are significant in their respective models and are 

negatively correlated with the M240B displace to LOA time:

• None.

The following personnel variables have no significant variables in their respective 

models:

• GT score.

Because the effects of the personnel variables do not have any patters and their effects 

are often negligible, our final model includes integration level only where HD has a 

difference of 0.92 minutes when compared to a C group and a statistically significant pvalue of 0.09 in a one-sided test. This difference is an increase from the 0.89-minute 

difference identified in the descriptive statistics, which is a 3.37% change. 

G.6.3.7 M2 Displacement

G.6.3.7.1 M2 Displacement Overview

We model elapsed time for the M2 displacement as a function of each personnel 

variable and integration level in a separate model in a mixed effects model where the 

random effect is who filled each position within the machine-gun squad. The covariates 

in each model are the values of each personnel variable for each patch number. For 
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each model, we report statistically significant positive and negative correlations and 

whether we observe any patterns.

There was one influential point (HD group on trial cycle 1), and we model the M2 

displacement time with and without this point. For this task, the influential point largely 

drives the conclusion that we draw about which variables affect the M2 displacement 

time. Including this point results in a model where height, weight and integration level 

are significantly correlated with the result. Excluding this point results in a model where 

no variables are consistently good predictors. The data point is valid, and there is no 

reason to exclude it; however, use caution when interpreting the results.

G.6.3.7.2 M2 Displacement with Influential Point

The models for the following variables do not run due to missing values:

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• Squad leader,

• Age,

• Height,

• Weight,

• AFQT score,

• GT score,

• PFT crunches,

• PFT 3-mile run,

• Rifle score.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables:

• CFT MUF.

The following personnel variables are significant in their respective models and are 

positively correlated with the M2 displacement time:

• Squad leader,

• Age of patch 2,

• Height of patches 1, 2, and 3,

• Weight of patches 1, 2, and 3,
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• CFT MTC of patch 1,

• CFT MUF of patch 1.

The following personnel variables are significant in their respective models and are 

negatively correlated with the M2 displacement time:

• PFT 3-mile run of patch 2,

• Rifle score of patch 2.

The following personnel variables have no significant variables in their respective 

models:

• None.

Because height and weight were significant for all Marines, we fit a final mixed effects 

model with integration level, a random effect for who filled each billet, height, and 

weight. Table G-8 displays the coefficients and standard errors for the final model 

based on AIC results. All three weights are highly correlated (~0.76) with integration 

level. Given the highly significant ANOVA results when treating integration level as the 

lone factor and considering the limited sample size of integrated squads, it calls into 

question the validity of the reduced model that includes the weights of all individuals.

Table G-8. Coefficients and Standard Errors for the Final M2 Displacement Model with Influential 

Point

Effect Estimate Std. Error

Integration level 0.72 0.25

Height patch 1 0.05 0.03

Weight patch 1 0.03 0.01

Weight patch 2 0.02 0.01

Weight patch 3 0.03 0.01

G.6.3.7.3 M2 Displacement without Influential Point

The models for the following variables do not run due to missing values:

• None.

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• Squad leader,

• Height,

• PFT 3-mile run.

The HD integration level is significant and negatively correlated with the response for 

the models that include the following personnel variables:

• CFT MUF.
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The following personnel variables are significant in their respective models and are 

positively correlated with the M2 displacement time:

• Age of patches 1 and 2,

• Height of patch 1,

• AFQT score of patch 1,

• CFT MTC of patch 1,

• CFT MUF of patch 1.

The following personnel variables are significant in their respective models and are 

negatively correlated with the M2 displacement time:

• PFT crunches of patch 2,

• PFT 3-mile run of patch 2.

The following personnel variables have no significant variables in their respective 

models:

• Weight,

• GT score,

• Rifle score.

We fit a final model with just integration level because there are no personnel variables 

significant for the whole machine-gun squad. Integration level is not significant in this 

model. We recommend referring back to ANOVA results in Section G.5.2.7 for 

differences between integration levels.
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Appendix to Annex G 

PIMG Supplemental Information

This appendix provides supplemental information for the PIMG portion of the GCEITF

experiment. It provides additional descriptive and basic inferential statistics not 

described in Annex G. 

Section 1. GCEITF Leadership Subjective Comments

The GCEITF leadership provided comments on their observations of the experiment 

throughout its execution. Table G A displays a summary of these comments broken 

down by task, integration level, gender, and type of comment.

Table G A – Summary of GCEITF Leadership Comments

Task and Metric Description Gender Total

C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total

M 0 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 3

F 0 6 6 0 3 3 0 3 3 0 0 0 0 0 0 0 6 6 0 0 0 0 1 1 19

Unit 0 3 3 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 1 1 6

M 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

F 0 3 3 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 5

Unit 0 2 2 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1

F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Unit 0 0 0 0 0 0 3 3 6 2 2 4 0 0 0 0 0 0 0 0 0 1 0 1 11

M 0 0 0 0 0 0 0 0 0 6 0 6 0 0 0 0 0 0 0 0 0 0 0 0 6

F 0 2 2 0 0 0 0 0 0 0 4 4 0 0 0 0 0 0 0 0 0 0 0 0 6

Unit 0 1 1 0 0 0 0 1 1 0 2 2 0 0 0 0 0 0 0 0 0 0 1 1 5

M 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1

F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 2 2 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 3

Unit 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

M 0 0 0 0 0 0 2 0 2 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 3

F 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2

Unit 0 1 1 0 0 0 5 3 8 3 2 5 0 0 0 0 0 0 0 0 0 1 3 4 18

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M240B Movement & 

Emplacement

Falling 

behind/slowing 

movement

Requesting extra 

breaks

Requires extra 

assistance Other No category

7-km Hike

Needs no 

assistance

Compensating 

for another 

Marine

Gear pass off

M240B Engagement

Displace to LOA

CASEVAC to CPP

M2 Mount/Dismount

M2 Displacment

1-km Hike
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Section 2. Additional Task Basic and Inferential Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. The experiment included a number of tasks and associated metrics 

conducted to enhance operational realism and maintain consistent application of the 

experimental process. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

This section presents results for 15 additional PIMG tasks. Annex G contains the 

descriptive statistics for the remainder of the PIMG tasks. The words “metric” and “task” 

are used interchangeably throughout this Appendix; they both refer to the experimental 

task. 

The two tables below display the results for 15 additional PIMG metrics. Table G B

displays the metrics and integration levels with their respective sample sizes, means, 

standard deviations, and percent differences between integration levels.

Table G C displays ANOVA results, including metrics and integration levels, and 

p-values suggesting statistical significance. For each task, an ANOVA and t-test were 

conducted to compare the two groups. If p-values are less than the a-priori determined 

significance level of 0.10, we conclude that there is statistical evidence that the 

response for the HD group is different from that in the C group. We present basic 

inferential statistics for eight additional tasks. 

Table G B – PIMG Test Results (Descriptive Statistics)

Metric Integration 

Level Sample Size Mean SD

% 

Difference 

(HD-C)

1-km Hike 

(minutes)

C 19 10.49 0.60 7.66% HD 21 11.29 0.64

7-km Hike; first 

km (minutes)

C 19 11.48 1.13 8.73% HD 17 12.48 1.43

7-km Hike; 

second km 

(minutes)

C 19 11.99 0.97

24.23% HD 17 14.90 2.84

7-km Hike; third 

km (minutes)

C 17 11.40 0.35 30.56% HD 16 14.89 2.83

7-km Hike; 

fourth km 

(minutes)

C 18 12.91 2.55

40.19% HD 18 18.09 4.20

7-km Hike; fifth 

km (minutes)

C 19 18.36 3.95 14.33% HD 19 21.00 3.61

7-km Hike; 

sixth km 

(minutes)

C 19 15.16 3.21

42.80% HD 19 21.66 3.95

7-km Hike; 

seventh km 

(minutes)

C 19 16.35 3.09

19.92% HD 20 19.60 3.47
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Metric Integration 

Level Sample Size Mean SD

% 

Difference 

(HD-C)

M240B 

Movement 

(minutes)

C 19 2.20 0.24

26.77% HD 21 2.79 0.31

M240B 

Emplacement 

(minutes)

C 19 1.61 0.38

3.93% HD 20 1.67 0.44

M240B 

Engagement 

Attack (hits on 

target)

C 17 99.76 64.98

-14.60% HD 20 85.20 42.20

M240B 

Engagement CAtk (hits on 

target)

C 16 94.81 47.60

10.22% HD 20 104.50 43.98

M2 Mount 

(minutes)

C 19 4.80 0.71 -8.73% HD 21 4.38 0.73

M2 Dismount 

(minutes)

C 19 0.98 0.21 -0.13% HD 21 0.98 0.28

M2 hits on 

target (% hits)

C 19 25.53% 15.22% 59.06% HD 21 40.60% 14.25%

Table G C – PIMG ANOVA and T-Test Results

Metric F Statistic 

(df) 

F Test PValue Comparison 2-Sided 

P-Value 

1-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

1-km Hike 

(minutes)

16.56 

(1, 38) < 0.01* HD-C < 0.01* < 0.01* 0.55 1.06 0.47 1.14 

7-km Hike; first km 

(minutes)

5.47 

(1, 34) 0.03* HD-C 0.03* 0.01* 0.43 1.57 0.27 1.74 

7-km Hike; second 

km 

(minutes)

17.61 

(1, 34) < 0.01* HD-C < 0.01* < 0.01* 1.94 3.87 1.65 4.16 

7-km Hike; third km 

(minutes)

25.48 

(1, 31) < 0.01* HD-C < 0.01* < 0.01* 2.53 4.44 2.24 4.73 

7-km Hike; fourth km 

(minutes)

20.06 

(1, 34) < 0.01* HD-C < 0.01* < 0.01* 3.67 6.71 3.22 7.16 

7-km Hike; fifth km 

(minutes)

4.59 

(1, 36) 0.04* HD-C 0.04* 0.02* 1.03 4.24 0.56 4.71 

7-km Hike; sixth km 

(minutes)

30.86 

(1, 36) < 0.01* HD-C < 0.01* < 0.01* 4.96 8.02 4.52 8.47 

7-km Hike; seventh 

km 

(minutes)

9.52 

(1, 37) < 0.01* HD-C < 0.01* < 0.01* 1.88 4.63 1.48 5.03 

M240B Movement 

(minutes)

43.42 

(1, 38) < 0.01* HD-C < 0.01* < 0.01* 0.47 0.70 0.44 0.74 
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Metric F Statistic 

(df) 

F Test PValue Comparison 2-Sided 

P-Value 

1-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

M240B

Emplacement 

(minutes)

0.23 

(1, 38) 0.64 HD-C 0.64 0.32 -0.11 0.24 -0.16 0.29 

M240B Engagement 

Attack 

(hits on target)

0.76 

(1, 35) 0.42 HD-C 0.43 0.22 -38.70 9.57 -

45.87 16.74 

M240B Engagement 

C-Atk 

(hits on target)

0.40 

(1, 34) 0.53 HD-C 0.53 0.27 5.74 13.63 -16.49 35.86 

M2 Mount

(minutes)

3.39 

(1, 38) 0.07* HD-C 0.07* 0.04* -0.71 -0.12 -0.80 -0.04 

M2 Dismount

(minutes)

0.00 

(1, 38) 0.99 HD-C 0.99 0.51 -0.10 0.10 -0.13 0.13 

M2 hits on target (% 

hits)

10.47 (1, 

38) < 0.01* HD-C <0.01* < 0.01* 0.09 0.22 0.07 0.23 

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between 

integration levels according to ANOVA.

Additional Task Results:

7-km Hike by km. The general trend for the 7-km hike was that the difference between 

the LD and C groups, the HD and C groups, and the HD and LD groups increased over 

the course of the hike.

1-km Hike. The data are normally distributed, as evidenced by the Shapiro-Wilk Test 

that resulted in a p-value of 0.17 for the C group and 0.84 for the HD group.

The C group had a mean time of 10.49 minutes. This time is statistically significantly 

faster than the HD group mean time of 11.29 minutes. The HD group was 7.66% 

slower than the C group.

M240B Movement. The data are normally distributed, as evidenced by the ShapiroWilk Test that resulted in a p-value of 0.18 for the C group and 0.81 for the HD group.

The C group had a mean time of 2.20 minutes. This time is statistically significantly 

faster than the HD group mean time of 2.79 minute. The HD group was 26.77% slower

than the C group. 

M240B Emplacement. The data are normally distributed, as evidenced by the ShapiroWilk Test that resulted in a p-value of 0.50 for the C group and 0.48 for the HD group.

The C group had a mean time of 1.61 minutes. This time is faster (but not statistically 

significantly) than the HD group mean time of 1.67 minutes. The HD group was 3.93% 

slower than the C group.
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M240B Engagement Attack. The data are normally distributed, as evidenced by the 

Shapiro-Wilk Test that resulted in a p-value of 0.66 for the C group and 0.32 for the HD 

group.

The C group had a mean of 99.76 hits on target. This number is higher (but not 

statistically significantly) than the HD group mean of 85.2 hits. The HD group produced 

14.60% fewer hits than the C group and the difference is not statistically significant in a 

t-test. 

M240B Engagement C-atk. The data are normally distributed, as evidenced by the 

Shapiro-Wilk Test that resulted in a p-value of 0.66 for the C group and 0.32 for the HD 

group.

The C group had a mean of 94.81 hits on target. This number is lower (but not 

statistically significantly) than the HD group mean of 104.5 hits. The HD group 

produced 10.22% more hits than the C group. 

Mount M2 on Vehicle. The data are normally distributed, as evidenced by the ShapiroWilk Test that resulted in a p-value of 0.94 for the C group and 0.07 for the HD group.

The C group had a mean time of 4.8 minutes. This time is statistically significantly 

slower than the HD group mean time of 4.38 minutes. The HD group was 8.73% faster 

than the C group. 

Dismount M2 from Vehicle. The data are normally distributed, as evidenced by the 

Shapiro-Wilk Test that resulted in a p-value of 0.68 for the C group and 0.01 for the HD 

group.

The C group had a mean time of 0.9798 minutes. This time is slower (but not 

statistically significantly) than the HD group mean time of 0.9786 minutes. The HD 

group was 0.13% faster than the C group. 

M2 hits on target. The data are normally distributed, as evidenced by the Shapiro-Wilk 

Test that resulted in a p-value of 0.04 for the C group and 0.90 for the HD group.

The C group had a mean percentage hit of 25.53%. This average is statistically 

significantly lower than the HD group mean of 40.60%. The HD group was 59.06% 

more accurate than the C group.
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Annex H. 

Field Artillery Cannoneer (MOS 0811) 

This annex details the Field Artillery Cannoneer (MOS 0811) portion of the Ground 

Combat Element Integrated Task Force (GCEITF) experiment executed from 3 March – 

11 April 2015 at training area Quakenbush, the Marine Corps Air Ground Combat 

Center (MCAGCC), Twentynine Palms, California. The following sections outline the 

Field Artillery Cannoneer Scheme of Maneuver, Limitations, Deviations, Dataset 

Description, Descriptive and Basic Inferential Statistics, and Modeling Results.

H.1 Scheme of Maneuver

H.1.1 Experimental Cycle Overview

The GCEITF volunteers executed a variety of subtasks over the course of a 1-day trial 

cycle at the MCAGCC in Twentynine Palms, California. A record trial consisted of 

randomly selected gun sections with zero, 1, or 2 females integrated into the gun crews 

for the entire SOM. Volunteers were assigned to one of six billets on each gun: 

Assistant Gunner/#1, #2, #3, #4/5, Recorder, or Driver. 

The daily SOM consisted of four phases. Phase one was a preparatory phase, where 

volunteers received their randomized gun and billet assignments. Phase two was 

Reconnaissance, Selection, and Occupation of Position (RSOP). This was the Section 

Chief’s opportunity to familiarize each volunteer with his leadership style, the howitzer, 

and terrain surrounding the gun position. Phase three was the live-fire trial, as 

described in the following paragraphs. After the trial was complete, the battery entered 

phase four, where the battery prepared for the next day by sanitizing the position and 

conducting sustainment, resupply, and bivouac. 

H.1.2 Experimental Details

The experimental daily SOM was designed around the mission of Marine Artillery and 

its function in a tactical environment. The mission of Marine Artillery is to furnish close 

and continuous fire support by neutralizing, destroying, or suppressing targets that 

threaten the success of the supported unit. The design of the experiment was to mirror 

an artillery section providing timely, accurate, and continuous-fire support. The 

evaluated subtasks were the most physically demanding and operationally relevant 

tasks that a cannoneer executes when operating the M777A2 howitzer. Initial Fatigue 

surveys were given to each volunteer at the beginning of each experimental day, 

followed by a final Fatigue survey at the completion of that particular day’s tasks. 

Workload surveys were administered immediately following specified tasks. Finally, 
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volunteers completed cohesion surveys at the end of each trial cycle. For survey 

instruments, see the GCEITF EAP Annexes D and M.

Objective and subjective measures of performance were captured for each task. The 

objective measures of performance included the time required to perform the task and 

the heart rate of volunteers while performing the task (reported separately). Subjective 

measures of performance and ability included Fatigue, Workload, and Cohesion 

Surveys conducted at various times during each trial cycle.

H.1.3 Additional Context

H.1.3.1 Training and Readiness Standards

Marine Corps artillery training and readiness standards are defined in NAVMC 3500.7A. 

It is critical to understand that the role of the T&R standard is not to determine whether 

the unit is performing adequately; rather, per the T&R Manual, “it identifies the minimum 

standards that Marines must be able to perform in combat.” Particularly in the realm of 

Fire Support, given the safe and proper operation of the howitzer and ancillary 

equipment, this standard should not be construed as “fast enough.” It is merely a tool by 

which commanders can train and evaluate a unit.

H.1.3.2 Individual Loads and Battery Timeline

Volunteers carried a standard 40-lb. load, which included a flak jacket with full set of 

SAPI plates, Kevlar helmet, six magazines, and individual first-aid kit. The artillery SOM

included 6 days of trials followed by 1 rest day. Between trial days, the battery 

bivouacked in the training area. Personnel stayed in two-man tents with the standardissue sleeping system. The Battery redeployed to Camp Wilson on the seventh day 

and returned the following day to execute follow-on 6-day cycles. All normal battery 

operations, such as logistics resupply and dunnage removal, were completed by the 

volunteers. 

H.1.3.3 Fire Commands Standards 

The artillery experiment conducted five trials concurrently in 1 day. All howitzers 

conducted each task at the same time, much like they would in a real training exercise. 

This method of execution was the safest and fastest way to complete the trials. If it 

were possible to have more time in the training area and to subject the volunteers to the 

same environmental variables and rest schedule, performing the SOM one howitzer 

section at a time would have been preferred. By completing the trials simultaneously, 

one howitzer had the ability to hamstring the entire gun-line’s SOM. To combat this 

effect, each task was queued manually by the Battery Gunnery Sergeant or the Fire 

Direction Center (FDC) with regimented 5-to-10-minute breaks after certain tasks. The 

FDC used a parallel sheaf, e.g., every howitzer on the gun-line used the same firing 

data and “At My Command” fire commands to ensure each howitzer began firing at the 
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same time. The result was safe, as close to operational realism as the experiment 

could be, and with easily identifiable start and stop timelines.

H.1.3.4 Digital vs Manual 

The Digital Fire Control System (DFCS) is a computer-based indirect-fire control system 

for the M777A2 howitzer. The DFCS provides gun location, navigation, and digital 

communications, and displays the direction and elevation of the howitzer. DFCS 

enhances a cannoneer’s ability to perform many tasks rapidly. However, introducing 

the DFCS into the experiment would increase the likelihood of technical difficulties 

requiring a pause in the trial to troubleshoot. The DFCS requires many cables to be 

connected and disconnected rapidly. The cables and digital-communications 

equipment require a tempered and methodical procedure for employment. Because the 

crews would be randomized each day for all howitzers, the trials were executed without 

the aid of the DFCS.

H.1.4 Experimental Tasks

H.1.4.1 Emplacing the Howitzer

Emplacement of the howitzer involves bursts of speed, heavy lifting, entrenching, and 

safe, meticulous transitioning from subtask to subtask. It is the method by which a 

howitzer is changed from its towed configuration (attached to a Medium Tactical Vehicle 

Replacement (MTVR), also known as a prime mover) and seated on the deck, capable 

of firing. This task involves dismounting the prime mover, placing the trident bar on the 

deck, manually manipulating the trail arms, entrenching the spades, and setting up the 

aiming stakes 100 meters away. Batteries can expect to emplace three to four positions 

a day during a normal field-training evolution. The experiment captured two 

emplacement times during each trial.

H.1.4.2 Ammunition Handling

A significant portion of a cannoneer’s time in the field is spent moving ammunition. The 

Artillery projectiles used during the experiment were approximately 40 inches long and 

weighed 105 pounds. The Marine Corps uses a separate, 7-ton truck to carry 

munitions. Additional stowage for complete rounds, which include the fuse, primer, and 

propellant, can be located in the prime mover using the Loose Projectile Restraint 

System (LPRS). The experiment required volunteers to offload and upload projectiles 

from both the ammunition truck and the LPRS. 

In the operational environment, load ammunition can be distributed among howitzers 

dispersed hundreds of meters apart. A battery under resupply by an air-delivered slingloaded pallet requires a howitzer section to move ammunition by foot over a long 

distance. To simulate these situations, the experiment required each individual to carry 

two projectiles 100 meters each. 
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H.1.4.3 Indirect-Fire Missions 

The howitzer section is the final link between requested support and delivery of fires. 

When a unit requests artillery support in the operating forces, timeliness is of utmost 

importance. The task is physically demanding, specifically for the ammunition-handling 

billets, where they must manually pick up projectiles, place them on the loading tray, 

and ram the round into the breech while the tube is elevated. Each trial consisted of 

firing 21 projectiles in five fire missions throughout the day, at high and low angle. 

H.1.4.4 Out-of-Traverse Limits 

The left and right traverse limit on an emplaced howitzer is a cone of 45 degrees. To 

engage targets outside this cone, the crew pumps up the suspension and pivots the 

howitzer on its wheels by pushing the tube left or right as a team. Once aligned in the 

direction of the target, the crew will emplace the howitzer by digging in the trail arms 

and preparing for the fire mission. This task is common with deployed batteries 

supporting multiple units throughout a battlespace. 

H.1.4.5 Gun Nets 

To simulate concealing the howitzer’s position from enemy aerial observation, 

volunteers emplaced and displaced camouflaged nets using a sledgehammer and 

stakes. Volunteers were administered a workload survey during emplacement and 

displacement of the nets.

H.1.4.6 Displacement

Timely displacement enables a battery to deliver fire support to maneuver units and 

move to the next firing point before the enemy has the opportunity to conduct counterbattery fire. During this task, which occurred twice per day, volunteers dismantled the 

ammunition pit, attached the trident bar, pumped the howitzer to ride height, and 

dislodged the howitzer’s dug-in trail arms, transitioning the howitzer from a firing 

configuration to a towed configuration. Volunteers were administered workload and 

fatigue surveys during this event.

H.1.5 Loading Events

These loading events ensured, to the greatest extent possible, that all volunteers were 

equally fatigued, and simulated the intense physical and mental workload present in 

combat or in a combat-focused training environment. A separate howitzer was used for 

loading volunteers not randomly selected on any given day’s assessment. A regular 

full-day’s SOM was executed on this additional howitzer to accomplish proper loading. 

H.1.6 Scheme of Maneuver Summary

Table H-1 displays number of trial cycles planned, executed, and analyzed by task. The 

artillery experiment executed 143 of 144 planned record trials over a 40-day period. A 
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recorded trial occurred over the course of 1 day, during which a randomly selected 6-

Marine gun section with zero, 1, or 2 females completed the entire SOM. The howitzer 

sections completed the SOM simultaneously to maximize time, safety, and similar 

conditions for each trial. The Marines remained in the field 6 days a week and 

completed all required tasks to sustain the battery outside the actual assessment. A 

trial consisted of repeatable tasks that a battery expects to conduct during field training 

or in the operational environment. Key experimental tasks included emplacing and 

displacing the howitzer, conducting indirect-fire missions, defending the battery, and 

moving and handling ammunition. When not selected to participate in a trial, volunteers 

completed the SOM on a loaded gun so they were equally fatigued. 

H.2 Limitations 

H.2.1 Limitations Overview

The GCEITF experiment was designed to allow operationally relevant tasks to occur as 

naturally as possible, while gathering unbiased measurements. Most tasks were 

performed in a similar manner to those in an operational environment; however, artificial 

limitations or interruptions were introduced that changed or altered the normal 

performance of a task. Although these limitations represent a degree of artificiality, they 

do not detract significantly from the data-collection plan. The following limitations were 

observed for the 0811 Field Artillery Cannoneer assessment. 

H.2.2 Relative Difficulty of Record Test

Though the tasks included in the artillery assessment were among the more physically 

strenuous experienced by 0811s in training and combat, the overall difficulty of the 

assessment was significantly less challenging than a comparatively long training 

exercise in the operating forces, much less combat. The entirety of the daily 

assessment, from billet assignment to final displacement, averaged approximately 5 

hours. Following the assessment, volunteers conducted post-firing maintenance, as 

well as dunnage and resupply activities. One day a week was a rest day, during which 

the volunteers were trucked out of the training area for showers and laundry. In a 

regimental- or battalion-level exercise, Marines generally conduct battery activities, to 

include firing, moving, and conducting ancillary tasks, throughout the day and into the 

night. A cannoneer during these training exercises can expect to average 18-20 hours 

of work a day. 

H.2.3 Qualified Section Chiefs 

Leadership played a key role in task results. By controlling for leadership, performance 

differences between experimental groups can be more readily attributed to the 

volunteers. Section Chiefs slated by Manpower to the Battery were of disparate quality 

and, in some cases, uncertified (all Section Chiefs attained certification prior to the 
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execution of the assessment). These direct-assignment Marines varied in their 

fundamental and implicit understanding of the howitzer, how to train junior Marines, and 

how to run the section at peak efficiency. Some Section Chiefs were noticeably less 

experienced than others, imparting performance disparity not attributable to the 

volunteers into the data. From a statistical standpoint, this did not hinder the ability to 

draw conclusions from results; given the spread of data collected over the variety of 

Section Chiefs, performance levels often were of sufficient consistency to attain 

statistical significance. Rather, the effect of this reality was imparting noise in the data 

that may obscure some performance trends, reducing their visibility and statistical 

significance. As discussed in the previous paragraph, these data should not be 

construed as effective benchmarks for timeliness or performance of tasks in regards to 

fire support standards.

H.2.4 Quantity of Howitzers in Training 

The experiment was designed to assess an eight-Marine (six volunteers per gun) 

howitzer section in the executions of the SOM. Six firing howitzers and one backup 

provided the workup phase’s approximately 40 volunteers the opportunity to maximize 

training time and experimental reality. In training, only three howitzers were used, with 

a fourth in reserve. For the first few months of training, sections comprised 15+ Marines 

per gun and, in the latter months, 8 Marines per gun, with half of the volunteers not 

training on a howitzer at any given time. This caused reduced realism in training and 

forfeited training opportunities, hobbling the effectiveness of the battery during the 

experiment. 

H.2.5 Consistency of SOP in training 

To compare task performance between sections and experimental groups, it is 

necessary that operating procedures are constant between sections and across the 

battery. During the pilot test, lack of a common SOP became apparent during the 

performance of tasks not well defined by the M777 technical manual. The Guns 

Platoon Sergeant was aggressive in attempting to create consistency across guns 

throughout the assessment as discrepancies arose. However, minute variations in 

operating procedures were frequent and difficult to detect. 

H.2.6 Equipment

The howitzers used by the battery were of varied quality, but universally aged. Although 

the failure rate of the guns was not significantly higher than counterpart guns, frequent 

mechanical problems remained. These issues ranged from scavenge system failures to 

hydraulic fluid leaks to fire-linkage failures. Captured incidents of impacts are noted, 

but, in many cases, the nuances of each gun created uncaptured variations in section 

performance. 
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H.2.7 Terrain

The assessment called for two emplacements and displacements per day. In training 

and in combat, the result of the movement is, generally speaking, a new firing position. 

For the experiment, to allow for fluidity of communications and avoid the requirement to 

move the entire battery, only the guns emplaced and displaced. This saved time and 

minimized interruptions, but created unrealistic conditions. As time passed, the initial 

emplacement gun position for each howitzer became worn and uneven. The 

assessment team mitigated this by backblading each position with heavy equipment 

and making minor adjustments to gun placements, but constant digging quickly 

changed the consistency of the soil and the experience of digging, particularly from 

howitzer to howitzer.

H.3 Deviations 

Deviations to the execution of the Field Artillery Cannoneer SOM were made and can 

be found in the Experimental Data Report signed May 2015; however, no deviations 

affected the analysis methodology outlined in the EAP.

H.4 Data Set Description 

H.4.1 Data Set Overview

The Artillery experiment timeline included 4 pilot trial days and 29 record trial days. 

Pilot trial data was not used for analysis. Record trials were conducted as planned from 

8 March through 11 April 2015. 

H.4.2 Record Test Volunteer Participants

Forty Marine volunteers participated in the Artillery experiment, including 28 males and 

12 females. One female volunteer dropped from the experiment before record trials

began, leaving a total of 39 volunteers, 28 males and 11 females.

H.4.3 Planned, Executed, and Analyzed Trial Cycles

The original plan called for 6 trials to be captured in each cycle, equating to 144 planned 

trials for each task. Only 5 trials could be completed each day due to the volunteer 

population. In order to reach the 144 planned trials, all make-up days were used. Two 

trials were discarded because of a howitzer recoil malfunction on 9 March and an ankle 

injury on 19 March. Part of a trial on 3 April was also discarded because the gunner’s

sights were not secured to the howitzer. Any other lost trial data is due to data collector 

or Toughbook program error, terrain, improper procedure, or equipment malfunction that 

led to an invalid data point. 
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Table H-1. 0811 Planned, Executed, and Analyzed Trial Cycles1

Task

Number of 

planned 

observations

Number of 

executed 

observations

Number of 

observations 

used in analysis

3-Round Low-Angle WP; 1st Round 

Response 144 136 121

3-Round Low-Angle WP; Indiv. Subsequent 

Rounds 144 140 125

3-Round Low-Angle WP; Total Fire Mission 144 136 121

3-Round High-Angle WP; 1st Round 

Response 144 139 122

3-Round High-Angle WP; Indiv. Subsequent 

Rounds 144 141 132

3-Round High-Angle WP; Total Fire Mission 144 139 123

3-Round Low-Angle HE from FP2; 1st 

Round Response 144 132 105

3-Round Low-Angle HE from FP2; Indiv. 

Subsequent Rounds 144 140 121

3-Round Low-Angle HE from FP2; Total Fire 

Mission 144 132 103

3-Round Low-Angle HE; 1st Round 

Response 144 137 121

3-Round Low-Angle HE; Indiv. Subsequent 

Rounds 144 142 133

3-Round Low-Angle HE; Total Fire Mission 144 137 120

9-Round Low-Angle HE; 1st Round 

Response 144 137 110

9-Round Low-Angle HE; Indiv. Subsequent 

Rounds 144 140 128

9-Round Low-Angle HE; Total Fire Mission 144 137 107

Ammo Prep Ammo; Truck Offload 144 142 141

Ammo Prep; LPRS Offload 144 142 140

Ammo Resupply; Ammo Movement 144 143 141

Displacement of Howitzer; Ammo Truck 

Upload 144 140 136

Displacement of Howitzer; LPRS Upload 144 142 138

Displacement of Howitzer; Total 

Displacement 144 139 126

Displacement of Howitzer; Trail Arms 144 138 132

Displacement of Howitzer; Trident Bar 144 142 137

Emplacing Howitzer; Dismount 144 143 136

Emplacing Howitzer; Total Emplacement 144 143 135

Emplacing Howitzer;Trident Bar Drop 144 143 137

Final Displacement of Howitzer; Mount 

Prime Mover 144 143 104

Final Displacement of Howitzer; Total 

Displacement 144 143 121

Final Displacement of Howitzer; Trail Arms 144 143 131

Final Displacement of Howitzer; Trident Bar 144 143 133

Gun Nets 144 141 139
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Hasty Ammo Prep; LPRS Offload 144 141 140

Hasty Emplacement of Howitzer; Dismount 144 142 136

Hasty Emplacement of Howitzer; Total 

Emplacement 144 141 132

Hasty Emplacement of Howitzer; Trident 

Bar Drop 144 142 141

Speed Shift #1; First Drop 144 141 139

Speed Shift #2; First Drop 144 141 132

Strike Nets 144 139 136 1

Some data was not captured or captured incorrectly due to human (Data Collector - DC) error or data processing equipment 

(Toughbook) error. Other data points were classified as outliers or potential influential points and were excluded from the 

analysis as described in the methodology section. 

H.5 Descriptive and Basic Inferential Statistics 

H.5.1 Descriptive Statistics Overview

This report accounts for various Artillery Section combinations when integrating MOS 

qualified female Marines with MOS qualified male Marines. It is important to quantify 

the billets within a Howitzer Section and to understand which billets a Marine could be 

expected to fill. These billets will be mentioned throughout the Annex. A Howitzer 

Section often consists of eight Marines. The section positions include Section Chief, 

Gunner, #1 Cannoneer/A-Gunner, #2 Cannoneer, #3 Cannoneer, #4/5 Cannoneer, 

Recorder, and Driver. The Section Chief is responsible for everything that happens on 

his Howitzer. His responsibilities are technical and require extensive MOS experience. 

The Gunner position also requires technical knowledge. He is responsible for giving 

commands and using the instruments to aim the howitzer. Because the nature of these 

positions is supervisory, requires leadership and experience, and is not very physical, 

these two billets were filled by direct assignments and were not moved to different

howitzers during the experiment. Each of the other six billets was filled by a volunteer 

and randomized daily. For a complete list of each of the duties of the cannoneer, read 

the Marine Corps TM 10407C-OR/1. This experiment uses the 7:1 configuration, 

meaning 7 cannoneers, Gunner included, and 1 Section Chief on each gun. This is a 

common configuration used by operational units, which are generally constrained by the 

number of cannoneers available. 

This report also refers to various concentrations of Howitzer Sections in terms of 

integration levels. A control group (C group) refers to an all-male crew filling any 

combination of the six volunteer billets; this type of crew was the control for the 

experiment. The low-density crew (LD group) was made up of five males and one 

female filling any combination of the six billets. The high-density crew (HD group) 

included four males and two females filling any combination of the six billets. The 

Marines were rotated among the billets by random selection without respect to MOS 

knowledge or experience. This was done in an effort to examine the effects of 
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integration at all crew levels and to allow Marines to step in and fill any of the six billets 

at any given time. 

In addition to integration level comparisons, there are certain tasks that were analyzed 

by what is referred to as “critical billet.” Though most tasks are to be completed as a 

section, where Marines can assist other Marines, it is important to understand that 

certain tasks, such as the conduct of fire missions, require each cannoneer to perform 

his or her duties. Compensation for a Marine failing to do his or her tasks results in 

slower performance and unresponsive fires. A critical billet was identified for tasks 

where a physically demanding duty was the bottleneck for a section. For example, the 

#4 cannoneer is the loader and must carry each round to the howitzer. The rest of the 

section relies on the #4 to complete his or her task before they can proceed with their 

own. Each critical billet is explained in the results that follow.

In every case, the integration concentration level was evaluated for statistical 

differences in performance, but in only select cases were critical billets considered. In 

these cases, the bottleneck in task performance was such that, were it not identified as 

a variable in success, the impact of integration might be masked. For instance, in the 

case of the speed shift, or out of traverse, two Marines are executing the 

preponderance of physical labor: numbers 1 and 2 cannoneers. These Marines are 

responsible for pumping the suspension of the howitzer, a particularly demanding task. 

Were analysis to be conducted based purely on integration level, the contribution of, as 

an example, the recorder could be misinterpreted as providing an inordinate impact on 

mission accomplishment.

All the tasks selected for this experiment were based on Training and Readiness (T&R) 

Manual requirements for Artillery Training NAVMC 3500.7, Marine Corps Warfighting 

Publication 3-16.3 TTP for the field Artillery Cannon Gunnery, Marine Corps TM 

10407C-OR/1, and guidance from Plans Policies & Operations (PP&O), Training and 

Education Command (TECOM), and Operating Forces Units. In addition, the tasks 

selected for the experiment were deemed physically demanding, repeatable, and 

commonly performed under time-constrained conditions in training and potentially in a 

combat environment. 

This section includes experimental results based on descriptive statistics, analysis of 

variance (ANOVA), Tukey Tests (or non-parametric equivalent as necessary), and 

scatter plots. The first table displays the metric, integration levels, sample sizes, means, 

and standard deviations. The second table shows ANOVA and Tukey test results 

including, but not limited to, metrics, p-values suggesting statistical significance, 

integration level elapsed time differences, and percentage differences between 
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integration levels. If non-parametric tests were needed, the second table displays these 

results instead of ANOVA and Tukey test results. Subsequent subsections cover each 

task in detail, along with scatterplots of the data. If p-values are less than the a-priori 

significance level of 0.10, we conclude that there is statistical evidence that the mean 

elapsed time for the experimental groups, LD and HD, are different from the C group

H.5.1.1 Emplacement of Howitzer by Integration Level

The emplacement task is the link between tactical march and the battery being fire 

capable. During a tactical march, the howitzer is in a towed configuration and is moved 

by a prime mover over long distances. In order for the howitzer to provide fire support 

to friendly units in an area of operations, the howitzer must emplace. 

To assess the proficiency of the cannon crewman sections conducting an emplacement, 

time hacks for certain subtasks were captured and used in the metric calculations 

below. These subtasks included the howitzer being disconnected from the prime 

mover, the command “ready drop” given by the gunner, the #4 cannoneer removing the 

trident bar, and the entrenchment of the spades. The emplacement time started when 

the Section Chief gave the order to begin and finished when the section chief ordered 

the offload of ammunition. The total time for this task did not include the time it took for 

the direct assignment Section Chief and battery staff to lay the howitzer with the M2A2 

aiming circles. Because the laying process does not involve physical labor or the 

volunteers, and it was subtracted from the total times. 

The experiment captured two separate emplacements during each trial. The first 

emplacement began at the first firing position with volunteers seated in the back of the 

prime mover and the howitzer in a towed configuration. The second emplacement time 

began with the volunteers moving 300 meters by foot to a supplemental firing position 

where the howitzer halted in the towed configuration. The only difference between the 

two emplacements was the position where volunteers began the task. The results for 

total emplacement times for both positions are displayed in the tables below. See the 

Artillery Appendix for dismount, repositioning, and trident bar calculations. Statistical 

analysis included analysis of variance (ANOVA) and Tukey tests, which is a multiple 

comparison statistical test. 

H.5.1.2 Emplacement of Howitzer by Integration Level Scatterplots

The scatterplots in figures H-1 and H-2 display the data used in the analysis of the 

results. All data points shown in the scatterplots were determined to be valid and used 

in the analysis and modeling.

Figure H-1. Emplacement of Howitzer by Integration Level
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Figure H-2. Second Emplacement of Howitzer by Integration Level

H.5.1.3 Emplacement of Howitzer Data Tables and Analysis

The tables below summarize the results of the task Emplacement of Howitzer. Table H2 compares means across metrics and integration levels. Table H-3 presents ANOVA 
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and Tukey test results, bringing into focus those metrics that resulted in statistical 

significance along with their percentage differences. 

Table H-2. Emplacement of Howitzer by Integration Level

Metric Integration 

Level

Sample

Size Mean SD

First Emplacement of Howitzer; Total 

Emplacement

(minutes)

C 40 7.86 2.58

LD 44 8.12 2.53

HD 51 8.19 2.83

Second Emplacement of Howitzer; Total 

Emplacement

(minutes)

C 38 4.08 1.44

LD 42 4.39 1.81

HD 52 4.76 2.06

Table H-3. Emplacement of Howitzer by Integration Level ANOVA and Tukey Test 

Metric F Statistic

(df)

F Test 

PValueComparison Difference % 

Difference

2-Sided 

P-Value

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

First 

Emplacement 

Howitzer; Total 

Emplacement

(minutes)

0.18

(2, 132)

0.83

LD-C 0.25 3.21% 0.90 -0.75 1.26 -0.95 1.46

HD-C 0.33 4.20% 0.83 -0.64 1.30 -0.84 1.49

HD-LD 0.08 0.95% 0.99 -0.87 1.02 -1.06 1.21

Second 

Emplacement of 

Howitzer; Total 

Emplacement

(minutes)

1.60

(2, 129)

0.21

LD-C 0.31 7.67% 0.72 -0.39 1.01 -0.53 1.16

HD-C 0.69 16.87% 0.18 0.02 1.36 -0.12 1.49

HD-LD 0.38 8.55% 0.58 -0.28 1.03 -0.41 1.16

H.5.1.3.1 First Emplacement of Howitzer 

The data are normally distributed as evidenced by the Shapiro-Wilk Test that results in 

a p-value of 1.00 for the C group, 0.19 for the LD group, and 0.77 for the HD group. In 

addition, group standard deviations are sufficiently similar to satisfy the equal variance 

assumption for ANOVA. 

For the first emplacement, the tables above show that, on average, the C group had a 

mean time of 7.86 minutes, compared to the LD group and HD group, who had a mean 
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time of 8.12 minutes (15 seconds slower than the C group) and 8.19 minutes (15 

seconds slower than the C Group), respectively. The C group was faster, on average, 

than both LD and HD groups. Neither of these comparisons was deemed statistically 

significant. 

H.5.1.3.2 Second Emplacement of Howitzer 

The C group data and HD group are not normally distributed, as evidenced by the 

Shapiro-Wilk Test that results in a p-value of < 0.01, but LD group data is normally 

distributed with a p-value of 0.10. We proceed with presenting ANOVA results because 

sample sizes are sufficiently large (n > 30) to satisfy the normality assumption for 

ANOVA. In addition, group standard deviations are sufficiently similar to satisfy the 

equal variance assumption for ANOVA.

For the second emplacement, the tables above show, on average, that the C group had

a mean time of 4.08 minutes compared to the LD group and HD group, which had mean 

times of 4.39 minutes (18 seconds slower than the C Group) and 4.7 minutes (40 

seconds slower than the C Group), respectively. The C group executed the task faster, 

on average, than both LD and HD groups, but neither comparison was statistically 

significant. 

H.5.1.4 Emplacement of Howitzer by Integration Level Contextual Comments

Although, in both emplacements, the differences between the integrated groups and the 

control groups were not statistically significant, speed and consistency in the execution 

of this task is critical to the success of a battery. Although the task of howitzer 

emplacement is expected to be executed expeditiously, safety and precision must also 

be present to guarantee the well-being of Marines and the accuracy of supporting fires. 

Additional time to complete an emplacement task leads to non-responsive fires, which 

has the potential to give the enemy a significant advantage in fire superiority. Speed 

directly affects the battery’s mission to be fire capable in order to achieve fire superiority 

over the enemy.

H.5.2 Ammunition Handling by Integration Level 

As stated in the Artillery SOM, a significant portion of a cannoneer’s time in the field is 

spent moving ammunition. This task is physically demanding, as it requires the Marines 

to lift a 155-mm round, weighing 106 lbs., from the ground to their shoulder and 

maintain positive control while transporting the round 100 meters. Ammunition 

offloading in this experiment was regimented in order to capture the differences among 

groups. In an operational environment, ammunition is constantly being shifted, 

redistributed, and organized. In addition, a common practice is to spread-load 

munitions among howitzers, moving them from howitzer to howitzer as necessary. The 
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ammunition-handling tasks were broken down into five subtasks: Ammo Truck Offload, 

Ammo Truck Upload, LPRS Offload, LPRS Upload, and Ammo Resupply.

H.5.2.1 Ammunition Truck Offload/Upload by Integration Level Scatterplots

The scatterplots in figures H-3 and H-4 display the data used in the analysis of the 

results. All data points shown in the scatterplots were determined to be valid and used 

in the analysis and modeling. Influential points are identified by dark solid black circles. 

Figure H-3. Ammunition Truck Offload by Integration Level
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Figure H-4. Upload Ammo Truck Offload by Integration Level

H.5.2.2 Ammunition Truck Offload/Upload by Integration Level Data Tables and Analysis

The tables below summarize the results of the subtasks, Ammo Truck Offload and

Ammo Truck Upload. Table H-4 compares means across metrics and integration 

levels. Table H-5 presents ANOVA and Tukey test results, bringing into focus those 

metrics that resulted in statistical significance along with their percentage differences. 

Table H-4. Ammunition Truck Offload/Upload by Integration Level

Metric Integration Level Sample Size Mean SD

Truck Offload

(minutes)

C 42 6.58 1.75

LD 45 7.45 2.10

HD 54 6.94 2.27

Truck Offload [Excluding Influential Points]

(minutes)* 

C 41 6.45 1.55

LD 45 7.45 2.10

HD 54 6.94 2.27

Ammo Truck Upload

(minutes)*

C 42 1.76 0.56

LD 43 2.18 0.82

HD 51 2.13 0.80
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Ammo Truck Upload [Excluding Influential Points]

(minutes)* 

C 42 1.76 0.56

LD 41 2.06 0.63

HD 50 2.07 0.69

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

Table H-5. Ammunition Truck Offload/Upload by Integration Level ANOVA and Tukey Test 

Metric

F 

Statistic

(df) 

F 

Test 

PValue

Comparison Difference % 

Difference

PValue80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Truck Offload

(minutes)

1.95

(2, 138)

0.15

LD-C 0.87 13.22% 0.13 0.10 1.64 -0.05 1.79

HD-C 0.36 5.46% 0.68 -0.38 1.09 -0.52 1.24

HD-LD -0.51 -6.86% 0.44 -1.23 0.21 -1.38 0.35

Truck Offload 

[Excluding 

Influential 

Points]

(minutes)

2.61

(2, 137)

0.08*

LD-C 1.00 15.48% 0.06* 0.24 1.75 0.09 1.91

HD-C 0.49 7.56% 0.48 -0.24 1.21 -0.38 1.36

HD-LD -0.51 -6.86% 0.43 -1.22 0.19 -1.36 0.34

Ammo Truck 

Upload

(minutes)

4.19

(2, 133)

0.02*

LD-C 0.42 24.04% 0.03* 0.14 0.70 0.09 0.75

HD-C 0.37 21.25% 0.04* 0.11 0.64 0.05 0.69

HD-LD -0.05 -2.25% 0.95 -0.31 0.22 -0.37 0.27

Ammo Truck 

Upload 

[Excluding 

Influential 

Points]

(minutes)

3.45

(2, 130)

0.03*

LD-C 0.30 17.28% 0.08* 0.06 0.54 0.01 0.59

HD-C 0.32 18.03% 0.05* 0.09 0.55 0.04 0.59

HD-LD 0.01 0.64% 0.99 -0.22 0.24 -0.26 0.29

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

The first subtask, Ammunition Truck Offload, consisted of four cannoneers offloading 20 

M795 High Explosive (HE) rounds and six M825 Smoke Rounds from the bed of an 

MTVR to an ammunition pit on the ground 10 yards away. The M795 and M825 are 

ballistically and dimensionally similar and offer the same experience in moving the 

projectile manually. This task occurred once during each trial. The start of the event 
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was recorded by the Section Chief’s command to offload, and the stop cue was 

recorded after all rounds were on the deck. The #3 and #4 Cannoneers were not 

involved in this task as they were concurrently completing the LPRS task.

The data are normally distributed as evidenced by the Shapiro-Wilk Test that results in 

a p-value of 0.03 for the C group, 0.16 for the LD group, and 0.08 for the HD group. In 

addition, group standard deviations are sufficiently similar to satisfy the equal variance 

assumption for ANOVA.

On average, the C group had a mean time of 6.58 minutes, compared to the LD group 

and HD group, which had a mean time of 7.45 minutes and 6.94 minutes, respectively. 

Neither comparison is statistically significant. However, the C group was faster, on 

average, than both the LD and HD groups.

After excluding influential points, the average of the C group drops to 6.45 minutes. 

This comparison with the LD group becomes significant; however, the HD group 

remains not statistically significant. 

H.5.2.2.1 Ammunition Truck Upload by Integration Level Overview and Results

The second subtask, Ammunition Truck Upload, consisted of moving eight HE rounds 

from the ammunition pit back onto the bed of the truck. This task occurred once during 

each trial. The start of the event was recorded by the Section Chief’s command to 

upload the ammunition, and the stop cue was recorded after all rounds were on the 

truck. The #3 and #4 Cannoneers were not involved in this task as they were 

concurrently completing the LPRS task.

The C group data and HD group are not normally distributed as evidenced by the 

Shapiro-Wilk Test that results in a p-value of < 0.01, but the LD group data is normally 

distributed with a p-value of 0.01. We proceed with presenting ANOVA results because 

sample sizes are sufficiently large (n > 30) to satisfy the normality assumption for 

ANOVA. In addition, group standard deviations are sufficiently similar to satisfy the 

equal variance assumption for ANOVA.

On average, the C group had a mean time of 1.76 minutes; the LD group, 2.18 

minutes; and the HD group, 2.13 minutes. Both the LD and HD groups are statistically 

significant when compared to the C group. The C group is faster, on average, than both 

the LD and HD groups. 

Excluding Influential Points reveals the LD group having a mean time of 2.06 minutes 

and the HD group having a mean time of 2.07 minutes. The C group remains the same,
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but is still faster and is still statistically significant when compared to the LD and HD 

groups.

H.5.2.2.2 Ammunition Truck Contextual Comments

Unloading or moving ammunition slower than a howitzer is firing has the potential to 

result in untimely fires. Cannoneers will rarely have all the time they need to keep 

ammunition orderly, remove dunnage, and keep the ready board fully stocked. Keeping 

up with these tasks is continuous and must be accomplished as quickly as possible so 

as to not delay a fire mission.

H.5.2.3 Ammunition Resupply by Integration Level 

In the ammunition resupply task, all volunteers were required to carry two individual 

projectiles for 100 meters. This was completed by moving to a turnaround point 50 

meters away. The start time began when all six volunteers stepped off, and it stopped 

when they returned with the projectile. 

H.5.2.4 Ammunition Resupply by Integration Level Scatterplot 

The scatterplot in Figure H-5 displays the data used in the analysis of the results. All 

data points shown in the scatterplot were determined to be valid and used in the 

analysis and modeling. 

Figure H-5. Ammunition Resupply by Integration Level
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H.5.2.5 Ammunition Resupply by Integration Level Data Table and Analysis

The tables below summarize the results of the task Ammunition Resupply. Table H-6 

compares means across metrics and integration levels. Table H-7 presents ANOVA and 

Tukey test results, bringing into focus those metrics that resulted in statistical 

significance along with their percentage differences. 

Table H-6. Ammunition Resupply by Integration Level

Metric Integration 

Level

Sample

Size Mean SD

Ammo Resupply; Ammo Movement

(minutes)* 

C 42 6.05 0.56

LD 45 6.36 1.04

HD 54 6.58 1.06

Ammo Resupply; Ammo Movement 

[Excluding Influential Points]

(minutes)* 

C 42 6.05 0.56

LD 43 6.36 0.74

HD 54 6.58 1.06

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

Table H-7. Ammunition Resupply by Integration Level

Metric

F 

Statistic

(df)

F 

Test 

PValue

Comparison Difference % 

Difference

PValue80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Ammo 

Resupply; 

Ammo 

Movement

(minutes)

3.83

(2, 138)

0.02*

LD-C 0.31 5.08% 0.28 -0.04 0.65 -

0.11 0.72

HD-C 0.53 8.78% 0.02* 0.20 0.86 0.13 0.93

HD-LD 0.22 3.52% 0.46 -0.10 0.55 -

0.17 0.61

Ammo 

Resupply; 

Ammo 

Movement 

[Excluding 

Influential 

Points]

4.74

(2, 136)

0.01*

LD-C 0.31 5.06% 0.22 -0.01 0.62 -

0.07 0.68

HD-C 0.53 8.78% < 

0.01* 0.23 0.83 0.17 0.89

HD-LD 0.23 3.55% 0.39 -0.07 0.50 -

0.13 0.58
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(minutes)

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

The C group and HD group data are normally distributed as evidenced by the ShapiroWilk Test that results in p-values of 0.20 and 0.88, but the LD group data is not normally 

distributed with a p-value of < 0.01. We proceed with presenting ANOVA results 

because sample sizes are sufficiently large (n > 30) to satisfy the normality assumption 

for ANOVA. In addition, group standard deviations are sufficiently similar to satisfy the 

equal variance assumption for ANOVA.

The tables above show that, on average, the C group had a mean time of 6.05 minutes; 

the LD group, 6.36 minutes; and the HD group, 6.58 minutes. The C group is faster, on 

average, than both the LD and HD groups. The difference between the C and HD 

groups is statistically significant. 

Excluding Influential Points reveals the LD group’s mean time remains the same; 

however, the standard deviation is reduced. The effect is minimal on the comparisons 

and remains not statistically significant.

H.5.2.5.1 Ammunition Resupply by Integration Level Contextual Comments

When ammunition must be moved over a long distance, such as 100 meters or longer, 

every Marine in the position is expected to assist in the task. In training and combat, 

movement of ammunition is usually done when there is a pause in firing or not when it 

can be done without hindering fire mission response time. However, immediate 

resupply being conducted while requests for fires are being called to the battery can 

require this task be done as swiftly as possible. This task is physically demanding and 

requires Marines to share the burden equally.

H.5.2.6 Loose Projectile Restraint System (LPRS) Offload / Upload by Integration Level

Two LPRS offloads and one LPRS upload were completed during the cycles. The 

offload task is physically demanding because it requires #3 and #4 Cannoneers to move 

three M795 High Explosive Rounds from the LPRS on the bed of the MTVR to the 

ammunition pit on the ground 10 yards away. The upload is the reverse of the offload, 

i.e., stowing rounds from the ammunition pit into the truck. During this task, #3 was 

located in the prime mover while #4 was on the ground. These two Marines were the 

only Cannoneers participating in this task and therefore were deemed as critical billets. 

The data collected from this task was analyzed in two separate ways. The first method 

of comparison looked at performance differences between the control group (C), the 

low-density group (LD), and a high-density group. The second method of comparison 
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looked at performance differences between gun crews grouped only by the gender of 

the two critical billets—Cannoneer #3 and #4 (regardless of the crew composition). 

H.5.2.6.1 LPRS Offload / Upload by Integration Level Scatterplots

The scatterplots in figures H-6, H-7, and H-8 display the data used in the analysis of the 

results. All data points shown in the scatterplots were determined to be valid and used 

in the analysis and modeling. 

 

Figure H-6. LPRS Offload by Integration Level 

Figure H-7. Upload by Integration Level 
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

H-23 AUGUST 2015

Figure H-8. LPRS Offload by Integration Level 
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

AUGUST 2015 H-24

H.5.2.7 LPRS Offload / Upload by Integration Level Data Table and Analysis

The tables below summarize the results of the subtasks, LPRS Offload/Upload. Table 

H-8 compares means across metrics and integration levels. Table H-9 presents ANOVA 

and Tukey test results, bringing into focus those metrics that resulted in statistical 

significance along with their percentage differences.

Table H-8. LPRS Offload / Upload by Integration Level

Metric Integration 

Level

Sample

Size Mean SD

First Emplacement LPRS Offload

(minutes)

C 42 2.03 0.84

LD 44 2.34 0.95

HD 54 2.10 1.00

First Emplacement LPRS Offload 

[Excluding Influential Points]

(minutes)

C 42 2.03 0.84

LD 44 2.34 0.95

HD 53 2.03 0.84

Second Emplacement LPRS 

Offload

(minutes)

C 42 1.77 1.02

LD 44 1.67 0.88

HD 54 1.84 1.04

Second Emplacement LPRS 

Offload [Excluding Influential 

Points]

(minutes)

C 41 1.67 0.78

LD 43 1.57 0.62

HD 53 1.76 0.86

LPRS Upload

(minutes)

C 43 1.15 0.44

LD 44 1.33 0.65

HD 53 1.35 0.54

LPRS Upload [Excluding Influential 

Points]

(minutes)

C 43 1.15 0.44

LD 43 1.28 0.55

HD 53 1.35 0.54

Table H-9. LPRS Offload / Upload by Integration Level ANOVA and Test Results

Metric F F 

Test 

Comparison Difference % P- 80 

% 80% 90% 90% 
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

H-25 AUGUST 2015

Statistic

(df)

PValueDifference Value LCB UCB LCB UCB

First 

Emplacement 

LPRS Offload

(minutes)

1.28

(2, 137)

0.28

LD-C 0.31 15.10% 0.29 -

0.04 0.66 -0.11 0.73

HD-C 0.07 3.59% 0.92 -

0.26 0.41 -0.33 0.47

HD-LD -0.23 -10.01% 0.44 -

0.56 0.10 -0.63 0.16

First 

Emplacement 

LPRS Offload 

[Excluding 

Influential 

Points]

(minutes)

1.86

(2, 136)

0.16

LD-C 0.31 15.10% 0.24 -

0.02 0.63 -0.08 0.70

HD-C 0.00 -0.15% 1.00 -

0.32 0.31 -0.38 0.37

HD-LD -0.31 -13.26% 0.20 -

0.62 0.00 -0.68 0.06

Second 

Emplacement 

LPRS Offload

(minutes)

0.38

(2, 137)

0.69

LD-C -0.10 -5.85% 0.88 -

0.47 0.26 -0.54 0.34

HD-C 0.07 3.97% 0.94 -

0.28 0.42 -0.35 0.49

HD-LD 0.17 10.43% 0.66 -

0.17 0.52 -0.24 0.59

Second 

Emplacement 

LPRS Offload 

[Excluding 

Influential 

Points]

(minutes)

0.71

(2, 134)

0.49

LD-C -0.09 -5.65% 0.84 -

0.38 0.19 -0.44 0.25

HD-C 0.09 5.61% 0.83 -

0.18 0.37 -0.24 0.42

HD-LD 0.19 11.94% 0.46 -

0.08 0.46 -0.14 0.51

LPRS Upload

(minutes)

1.99

(2, 135)

0.14

LD-C 0.21 17.90% 0.20 0.00 0.41 -

0.04 0.45

HD-C 0.20 17.12% 0.19 0.00 0.39 -

0.04 0.43

HD-LD -0.01 -0.66% 1.00 - 0.19 - 0.23
GCEITF EAR ANNEX H

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AUGUST 2015 H-26

0.20 0.24

LPRS Upload 

[Excluding 

Influential 

Points]

(minutes)

1.84

(2, 134)

0.16

LD-C 0.15 13.05% 0.38 -

0.04 0.34 -0.08 0.38

HD-C 0.20 17.12% 0.15 0.02 0.38 -

0.02 0.42

HD-LD 0.05 3.59% 0.90 -

0.14 0.23 -0.17 0.27

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

H.5.2.7.1 First LPRS Offload by Integration Level

The C group data and LD group data are normally distributed as evidenced by the 

Shapiro-Wilk Test that results in p-values of 0.05 and 0.01, but the HD group data is not 

normally distributed with a p-value of < 0.01. We proceed with presenting ANOVA 

results because sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA. In addition, group standard deviations are sufficiently similar to 

satisfy the equal variance assumption for ANOVA. 

The tables above show that, on average, the C group had a mean time of 2.03 minutes; 

the LD group, 2.34 minutes; and the HD group, 2.10 minutes. The C group is faster but 

not statistically significant. 

Excluding Influential Points shows the HD group to be as fast as the C group; however, 

it remains statistically insignificant.

H.5.2.7.2 Second LPRS Offload by Integration Level

No groups’ data are normally distributed as evidenced by the Shapiro-Wilk Test that 

results in p-values of < 0.01. We proceed with presenting ANOVA results because 

sample sizes are sufficiently large (n > 30) to satisfy the normality assumption for 

ANOVA. In addition, group standard deviations are sufficiently similar to satisfy the 

equal variance assumption for ANOVA.

The tables above show that, on average, the C group had a mean time of 1.77 minutes; 

the LD group, 1.67 minutes; and the HD group, 1.84 minutes. The LD group was the 

fastest group, but no comparison is statistically significant. 

Excluding Influential Points shows the C group mean time dropping to 1.67 minutes, the 

LD group dropping to 1.57 minutes, and the HD group dropping to 1.76 minutes. 

Ultimately, the comparisons remain similar with no statistical significance in comparison.
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

H-27 AUGUST 2015

H.5.2.7.2.1 LPRS Upload by Integration Level

The C group and LD group data are normally distributed as evidenced by the ShapiroWilk Test that results in p-values of 0.13 and 0.01, but the HD group data is not 

normally distributed with a p-value of < 0.01. We proceed with presenting ANOVA 

results because sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA. In addition, group standard deviations are sufficiently similar to 

satisfy the equal variance assumption for ANOVA.

The tables above show that, on average, the C group had a mean time of 1.15 minutes; 

the LD group; 1.36 minutes; and the HD group, 1.35 minutes. The C group was faster 

than both the LD and HD groups, but this is not statistically significant. 

Excluding Influential Points, the LD group drops in mean time to 1.30 minutes. The C 

group remains the fastest group, but this is not statistically significant.

H.5.2.7.3 Loose Projectile Restraint System (LPRS) Offload / Upload by Critical Billet

This second method of comparison for LPRS Offload / Upload looks at performance 

differences between gun crews grouped only by the gender of the Marines serving in 

two critical billets. In this analysis, the first critical billet is the Cannoneer #3, and it is 

denoted by either a (M) for male or a (F) for female. The second critical billet is the 

Cannoneer #4 and, again, is marked by a (M) or (F) to denote the gender of the Marine. 

In the tables below, the gender of the Cannoneer #3 and #4 billets are represented in 

two letters, with the first letter corresponding to the Cannoneer #3 billet and the second 

letter to the Cannoneer #4 billet.

H.5.2.7.4 LPRS Offload / Upload by Critical Billet Scatterplot

The scatterplots in figures H-9, H-10, and H-11 display the data used in the analysis of 

the results. All data points shown in the scatterplots were determined to be valid and 

used in the analysis and modeling. 

Figure H-9. First Emplacement LPRS Offload by Critical Billet
GCEITF EAR ANNEX H

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AUGUST 2015 H-28

Figure H-10. Second Emplacement LPRS Offload by Critical Billet 
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

H-29 AUGUST 2015

Figure H-11. LPRS Upload by Critical Billet 
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

AUGUST 2015 H-30

H.5.2.7.5 Loose Projectile Restraint System (LPRS) Offload / Upload by Critical Billet

The tables below summarize the results of the task LPRS Offload/Upload analysis by 

critical billet. Table H-10 compares means across metrics and integration levels. Table 

H-11 presents ANOVA and Tukey test results, bringing into focus those metrics that 

resulted in statistical significance along with their percentage differences.

Table H-10. LPRS Results by critical billet

Metric Integration 

Level

Sample

Size Mean SD

First Emplacement LPRS Offload

(minutes)

MM 99 2.12 0.93

MF 21 2.37 0.85

FM 17 2.13 1.20

FF 3 1.96 0.52

First Emplacement LPRS Offload 

[Excluding Influential Points]

(minutes)

MM 99 2.12 0.93

MF 21 2.37 0.85

FM 16 1.88 0.63

FF 3 1.96 0.52

Second Emplacement LPRS Offload

(minutes)

MM 99 1.73 0.97

MF 21 1.60 0.59

FM 17 2.07 1.33

FF 3 2.46 1.01

Second Emplacement LPRS Offload 

[Excluding Influential Points]

(minutes)

MM 97 1.64 0.75

MF 21 1.60 0.59

FM 16 1.84 0.96

FF 3 2.46 1.01

LPRS Upload

(minutes)*

MM 97 1.20 0.47

MF 20 1.71 0.64

FM 18 1.25 0.61
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H-31 AUGUST 2015

FF 3 1.67 0.95

LPRS Upload [Excluding Influential 

Points]

(minutes)*

MM 97 1.20 0.47

MF 19 1.61 0.46

FM 18 1.25 0.61

FF 3 1.67 0.95

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

Table H-11. LPRS Results by Critical Billet ANOVA and Tukey Test 

Metric

F 

Statistic

(df)

F 

Test 

PValue

Comparison Difference % 

Difference

PValue80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

First 

Emplacement 

LPRS Offload

(minutes)††

2.53 0.47

MF-MM 0.25 11.67% 0.24 -0.02 0.52 -0.10 0.60

FM-MM 0.01 0.42% 0.98 -0.40 0.41 -0.52 0.54

FF-MM -0.16 -7.56% 0.65 -0.71 0.39 -0.98 0.65

MF-FM 0.25 11.20% 0.50 -0.21 0.69 -0.35 0.83

FF-MF -0.41 -17.22% 0.31 -0.95 0.14 -1.17 0.35

FF-FM -0.17 -7.95% 0.70 -0.76 0.42 -0.96 0.62

First 

Emplacement 

LPRS Offload 

[Excluding 

Influential 

Points]

(minutes)

0.98

(3, 135)

0.40

MF-MM 0.25 11.67% 0.65 -0.17 0.67 -0.24 0.74

FM-MM -0.24 -11.38% 0.74 -0.71 0.23 -0.79 0.31

FF-MM -0.16 -7.56% 0.99 -1.19 0.86 -1.36 1.04

MF-FM 0.49 26.00% 0.34 -0.09 1.07 -0.19 1.17

FF-MF -0.41 -17.22% 0.88 -1.49 0.67 -1.67 0.85

FF-FM 0.08 4.30% 1.00 -1.02 1.18 -1.20 1.37

Second 

Emplacement 

LPRS Offload

(minutes)††

3.88 0.28

MF-MM -0.13 -7.53% 0.43 -0.34 0.08 -0.40 0.14

FM-MM 0.34 19.97% 0.32 -0.10 0.79 -0.24 0.93

FF-MM 0.73 42.21% 0.34 -0.37 1.82 -0.94 2.40

MF-FM -0.47 -22.92% 0.19 -0.93 -0.02 -1.07 0.12
GCEITF EAR ANNEX H

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AUGUST 2015 H-32

FF-MF 0.86 53.78% 0.28 -0.23 1.95 -0.79 2.51

FF-FM 0.38 18.54% 0.60 -0.68 1.45 -1.12 1.89

Second 

Emplacement 

LPRS Offload 

[Excluding 

Influential 

Points]

(minutes)

1.46

(3, 133)

0.23

MF-MM -0.04 -2.46% 1.00 -0.40 0.32 -0.46 0.38

FM-MM 0.21 12.56% 0.75 -0.20 0.61 -0.27 0.68

FF-MM 0.82 49.99% 0.26 -0.07 1.70 -0.22 1.85

MF-FM -0.25 -13.34% 0.77 -0.75 0.26 -0.83 0.34

FF-MF 0.86 53.78% 0.27 -0.07 1.79 -0.23 1.95

FF-FM 0.61 33.26% 0.58 -0.34 1.56 -0.50 1.72

LPRS Upload

(minutes)††

13.08 < 

0.01*

MF-MM 0.51 42.15% < 

0.01* 0.31 0.71 0.25 0.76

FM-MM 0.05 3.88% 0.76 -0.15 0.25 -0.21 0.31

FF-MM 0.47 39.07% 0.48 -0.56 1.50 -1.11 2.05

MF-FM 0.46 36.83% 0.03 0.02 0.72 0.12 0.80

FF-MF -0.04 -2.16% 0.95 -1.05 0.97 -1.55 1.48

FF-FM 0.42 33.88% 0.52 -0.58 1.43 -1.09 1.94

LPRS Upload 

[Excluding 

Influential 

Points]

(minutes)††

13.69 < 

0.01*

MF-MM 0.40 33.65% < 

0.01* 0.25 0.65 0.21 0.60

FM-MM 0.05 3.88% 0.76 -0.15 0.25 -0.21 0.31

FF-MM 0.47 39.07% 0.48 -0.56 1.50 -1.11 2.05

MF-FM 0.36 28.66% 0.05 0.12 0.59 0.06 0.66

FF-MF 0.07 4.06% 0.92 -0.95 1.08 -1.48 1.61

FF-FM 0.42 33.88% 0.52 -0.58 1.43 -1.09 1.94

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

††Indicates results presented are from Robust ANOVA and Welch’s t-tests with p-values compared to 

0.0167 for Bonferroni adjustment. F-statistics is a Chi-square statistic from Robust ANOVA, and the F-test 

Pp-value is from a Robust ANOVA. The P-values are two-sided p-values from Welch’s t-tests and the CIs 

are from Welch’s t-tests.
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

H-33 AUGUST 2015

H.5.2.7.5.1 First and Second LPRS Offload by Critical Billet

The MM and FM groups’ data are not normally distributed as evidenced by the ShapiroWilk Test that results in p-values of < 0.01, but the FF and MF groups’ data are normally 

distributed with p-values of 0.66 and 0.13. In addition, the FM group standard deviation 

is more than twice that of the FF group standard deviation. As such, we recommend 

using the robust ANOVA results shown above. We proceed with presenting robust 

ANOVA results because they were confirmed by a Kruskal-Wallis Test with a p-value of 

0.55. 

The tables above show that, on average, the mean times for the MM, MF, FM, and FF 

groups showed no statistical significance. The results are similar when excluding 

Influential Points.

H.5.2.7.5.2 Second LPRS Offload by Critical Billet

The MM and FM groups’ data are not normally distributed as evidenced by the ShapiroWilk Test that results in p-values of < 0.01, but the FF and MF groups’ data are normally 

distributed with p-values of 0.52 and 0.61. In addition, the FM group standard deviation 

is more than twice that of the MF group standard deviation. As such, we recommend 

using the robust ANOVA results shown above. We proceed with presenting robust

ANOVA results because they were confirmed by a Kruskal-Wallis Test with a p-value of 

0.28. 

The tables above show that, on average, the mean times for the MM, MF, FM, and FF 

groups showed no statistical significance. The results are similar when excluding 

Influential Points. 

H.5.2.7.5.3 LPRS Upload by Critical Billet

The MM and FM groups’ data are not normally distributed as evidenced by the ShapiroWilk Test that results in p-values of < 0.01, but the FF and MF groups’ data are normally 

distributed with p-values of 0.52 and 0.61. In addition, the FF group standard deviation 

is more than twice that of the MM group standard deviation. As such, we recommend 

using the robust ANOVA results shown above. We proceed with presenting robust 

ANOVA results because they were confirmed by a Kruskal-Wallis Test with a p-value of 

< 0.01. 

The tables above show that, on average, the MM group had a mean time of 1.20

minutes with a SD of 0.47 minutes. The MF group had a mean time of 1.71 minutes. 

The FM group had a mean time of 1.25 minutes. The FF group had a mean time of 

1.67 minutes. The MF-MM and MF-FM group comparisons are statistically significant. 
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

AUGUST 2015 H-34

Excluding Influential Points results in a drop in the MF mean time to 1.61 minutes. The 

MF-FM group comparison is no longer statistically significant. The MF-MM group 

comparison remains statistically significant as MM are 33.65% faster.

H.5.2.7.5.4 LPRS Offload / Upload by Critical Billet Contextual Comments

In the case of weaker Marines, it was a constant effort to dissuade the practice of 

disassembling the LPRS in order to reduce the effort required to execute the task. 

Intuitively, this tendency makes logical sense, as it eliminates the requirement to lift the 

projectile straight out of the system. However, the disassembly of the system results in 

an unsafe condition, in that, during normal operations, there are likely more than three 

projectiles in the load. Furthermore, terrain can result in the (unsecured) projectiles 

falling. This can cause injuries and damage to projectiles and equipment. In the above 

data, the result of this practice masks the disparity in performance between stronger 

and weaker Marines, regardless of gender. 

H.5.3 Indirect-Fire Missions Overview

Five fire missions were executed by a howitzer section during each 1-day cycle. The 

missions were: a 3-round low-angle HE, a 3-round high-angle white phosphorus (WP) 

smoke, a 9-round low-angle HE, a 3-round low-angle smoke out-of-traverse limits, and, 

finally, another 3-round low-angle HE from the supplemental position. The M795 (HE) 

and M825 (WP) are ballistically and dimensionally similar and offer the same 

experience in the handling of the projectile. There is no ostensible difference at the gun 

section level between a HE and WP mission.

Procedures for each fire mission were largely the same, regardless of shell/fuze 

combination or angle of fire. Each fire mission began with the Fire Direction Center 

(FDC) starting the event. As the gun was receiving the firing data from the FDC, they 

were simultaneously aiming the howitzer by traversing left or right and adjusting the 

quadrant up or down. The loader, or #4 Cannoneer, would pick up a projectile from the 

ammunition pit, hold it to allow the Section Chief to inspect the round, and then place 

the round onto the loading tray. Cannoneer #4 would then join the Driver and ram the 

round into the breech. The #2 Cannoneer would then load the powder increments into 

the breech powder chamber and close the breech. Data collectors recorded the time 

hacks for both the ram and the closing of the breech. Finally, the howitzer was fired by 

the #1 Cannoneer on the Section Chief’s command. Every shot and misfire was 

captured and used to calculate shot rate (seconds per shot) and elapsed time. 

In the case of a high-angle mission, the loading of the projectile would occur prior to 

fully elevating the howitzer, a minor departure in procedure from the low-angle missions. 

The tube would be depressed between shots in order to facilitate the loading of the 

howitzer.
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

H-35 AUGUST 2015

For all five fire missions, the #4 Cannoneer was identified as a critical billet. This was 

due to the Marine’s physically challenging position and place on the critical path of the 

fire mission. The #1 Cannoneer was identified as an additional critical billet in the case 

of the high-angle mission. This Marine’s role in high-elevation missions is the elevating 

and depressing of the gun to facilitate loading. The manipulation of elevation is 

executed through the spinning of a hand wheel; each turn of the wheel results in a delta 

of approximately 10 mils of elevation. For the high-angle missions, projectiles were 

loaded at 800 mils, and the missions averaged approximately 1050 mils, requiring 

roughly 25 turns of the wheel per elevation or depression. This task does not require 

pure strength so much as short bursts of endurance.

The data collected from the indirect-fire missions were analyzed in two separate ways. 

The first method of comparison looked at performance differences between the control 

group (C), the low-density group (LD), and the high-density group (HD). The second 

method of comparison looked at performance differences between gun crews grouped 

only by the gender of the critical billets, regardless of the crew composition. The critical 

billets identified for the high-angle mission were the #1 and #4 Cannoneers. All other 

fire missions had #4 as a critical billet. 

H.5.3.1 Indirect-Fire Missions by Integration Level

The scatterplots in figures F-12 through F-16 display the data used in the analysis of the 

results. All data points shown in the scatterplots were determined to be valid and used 

in the analysis and modeling. 

 
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

AUGUST 2015 H-36

Figure H-12. 3-Round Low-Angle HE; Indiv. Subsequent Rounds by Integration 

Level
GCEITF EAR ANNEX H

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H-37 AUGUST 2015

Figure H-13. 3-Round High-Angle WP; Indiv. Subsequent Rounds by Integration 

Level
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

AUGUST 2015 H-38

Figure H-14. 9-Round Low-Angle HE; Indiv. Subsequent Rounds by Integration 

Level 

Figure H-15. 3-Round Low-Angle WP; Indiv. Subsequent Rounds by Integration 

Level
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

H-39 AUGUST 2015

Figure H-16. 3-Round Low-Angle HE from FP2; Indiv. Subsequent Rounds by 

Integration Level

H.5.3.2 Indirect-Fire Missions by Integration Level Data Table and Analysis

The tables below summarize the results of the task Indirect-Fire Missions analysis by 

Integration Level. Table H-12 compares means across metrics and integration levels. 

Table H-13 presents ANOVA and Tukey test results, bringing into focus those metrics 

that resulted in statistical significance along with their percentage differences.

Table H-12. Indirect-Fire Mission Results by Integration Level

Metric Integration 

Level

Sample

Size Mean SD

3-Round Low-Angle HE; Indiv. Subsequent 

Rounds

(average seconds per round)* 

C 41 24.74 4.66

LD 42 27.75 7.18

HD 50 32.53 14.02

3-Round High-Angle WP; Indiv. Subsequent 

Rounds

(average seconds per round)* 

C 39 50.32 11.08

LD 42 54.87 14.03

HD 51 60.96 19.27
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9-Round Low-Angle HE; Indiv. Subsequent 

Rounds

(average seconds per round)* 

C 38 22.72 3.68

LD 41 25.52 7.01

HD 49 26.06 6.96

3-Round Low-Angle WP; Indiv. Subsequent 

Rounds

(average seconds per round)* 

C 40 23.66 5.56

LD 39 24.09 6.77

HD 46 26.83 7.48

3-Round Low-Angle HE from FP2; Indiv. 

Subsequent Rounds

(average seconds per round)* 

C 36 19.88 5.10

LD 38 22.32 5.43

HD 47 24.44 9.41

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

Table H-13. Indirect-Fire Missions by Integration Level ANOVA and Tukey Test 

Metric

F 

Statistic

(df)

F 

Test 

PValue

Comparison Difference % 

Difference

PValue80 % 

LCB**

80% 

UCB**

90% 

LCB**

90% 

UCB**

3-Round 

Low-Angle 

HE; Indiv. 

Subsequent 

Rounds

(average 

second per 

round)††

12.70) < 

0.01*

LD-C 3.00 12.14% 0.03* 0.02 0.08 0.01 0.09

HD-C 7.79 31.47% < 

0.01* 0.08 0.18 0.07 0.19

HD-LD 4.78 17.24% 0.04 0.03 0.13 0.02 0.14

3-Round 

High-Angle 

WP; Indiv. 

Subsequent 

Rounds

(average 

second per 

round)

5.28

(2, 129)

< 

0.01*

LD-C 4.54 9.03% 0.39 -1.43 10.52 -2.63 11.71

HD-C 10.64 21.14% < 

0.01* 4.92 16.35 3.78 17.50

HD-LD 6.09 11.11% 0.15 0.50 11.69 -0.63 12.81

9-Round 3.42 0.04* LD-C 2.80 12.31% 0.12 0.39 5.20 -0.09 5.68
GCEITF EAR ANNEX H

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H-41 AUGUST 2015

Low-Angle 

HE; Indiv. 

Subsequent 

Rounds

(average 

second per 

round)

(2, 125) HD-C 3.34 14.72% 0.04* 1.03 5.65 0.57 6.12

HD-LD 0.55 2.14% 0.91 -1.71 2.81 -2.17 3.26

3-Round

Low-Angle 

WP; Indiv. 

Subsequent 

Rounds

(average 

seconds 

per round)

2.88

(2, 122)

0.06*

LD-C 0.43 1.83% 0.96 -2.16 3.03 -2.69 3.55

HD-C 3.17 13.40% 0.08* 0.67 5.66 0.17 6.17

HD-LD 2.74 11.36% 0.15 0.22 5.25 -0.28 5.75

3-Round 

Low-Angle 

HE from 

FP2; Indiv. 

Subsequent 

Rounds

(average 

second per 

round)

4.13

(2, 118)

0.02*

LD-C 2.45 12.32% 0.31 -0.43 5.33 -1.01 5.91

HD-C 4.56 22.96% 0.01* 1.82 7.31 1.27 7.86

HD-LD 2.11 9.47% 0.37 -0.52 4.82 -1.13 5.36

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.††Indicates results 

presented are from Robust ANOVA and Welch’s t-tests with p-values compared to 0.033 for Bonferroni 

adjustment. F-statistics is a Chi-square statistic from Robust ANOVA, and the F-test Pp-value is from a 

Robust ANOVA. The P-values are two-sided p-values from Welch’s t-tests and the CIs are from Welch’s 

t-tests.

H.5.3.2.1.1 3-Round Low-Angle (HE) Results by Integration Level

The C and LD groups’ data are normally distributed as evidenced by the Shapiro-Wilk 

Test that results in p-values of 0.08 and 0.25, but the HD group’s data are not normally 

distributed with a p-value of < 0.01. In addition, the HD group standard deviation is 

more than twice that of the C group standard deviation. As such, we recommend using 

the robust ANOVA results shown above. We proceed with presenting robust ANOVA 

results because sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA.
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The first Indirect-Fire Mission is the 3-round low-angle HE Indiv. Subsequent Rounds 

fire mission. The tables above show that, on average, the C group had a mean time of 

24.74 seconds per round; the LD group, 27.75 seconds per round; and the HD group, 

32.53 seconds per round. On average, the C group was faster than the LD and HD 

groups, and the differences between the HD and C groups, and the HD and LD groups

are statistically significant.

H.5.3.2.1.2 3-Round High-Angle (WP) Results by Integration Level 

The C and HD groups’ data are not normally distributed as evidenced by the ShapiroWilk Test that results in p-values of < 0.01, but the LD group’s data is normally 

distributed with a p-value of 0.28. We proceed with presenting ANOVA results because 

sample sizes are sufficiently large (n > 30) to satisfy the normality assumption for

ANOVA. In addition, group standard deviations are sufficiently similar to satisfy the 

equal variance assumption for ANOVA. 

The second Indirect-Fire Mission is the 3-round high-angle WP Indiv. Subsequent 

Rounds fire mission. The tables above show, on average, the C group had a mean time 

of 50.32 seconds per round; the LD group, 54.87 seconds per round; and the HD group, 

60.96 seconds per round. On average, the C group was faster than the LD and HD 

groups, and the difference between the HD and C groups is statistically significant.

H.5.3.2.1.3 9-Round Low-Angle (HE) Results by Integration Level

The C and LD groups’ data are normally distributed as evidenced by the Shapiro-Wilk 

Test that results in p-values of 0.30 and 0.02, but the HD group’s data is not normally 

distributed with a p-value of < 0.01. We proceed with presenting ANOVA results 

because sample sizes are sufficiently large (n > 30) to satisfy the normality assumption 

for ANOVA. In addition, group standard deviations are sufficiently similar to satisfy the 

equal variance assumption for ANOVA

The third Indirect-Fire Mission is the 9-round low-angle HE Indiv. Subsequent Rounds 

fire mission. The tables above show that, on average, the C group had a mean time of 

22.72 seconds per round, while the LD group recorded a mean time of 25.52 seconds 

per round and the HD group noted a mean time of 26.06 seconds per round. On 

average, the C group was faster than the LD and HD groups. The difference between 

the HD and C groups is statistically significant. 

H.5.3.2.1.4 3-Round Low-Angle (WP) Results by Integration Level

The C, LD, and HD groups’ data are not normally distributed as evidenced by the 

Shapiro-Wilk Test that results in p-values of < 0.01. We proceed with presenting 

ANOVA results because sample sizes are sufficiently large (n > 30) to satisfy the 

normality assumption for ANOVA. In addition, group standard deviations are sufficiently 

similar to satisfy the equal variance assumption for ANOVA. 

The fourth Indirect-Fire Mission is the 3-round low-angle WP Indiv. Subsequent Rounds 

task. The tables above show that, on average, the C group had a mean time of 23.66 
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seconds per round. The LD and HD groups had mean times of 24.09 and 26.83

seconds per round, respectively. On average, both LD and HD groups were slower 

than the C group. The difference between the HD and C groups is statistically 

significant.

H.5.3.2.1.5 3-Round Low-Angle (HE) from FP2 Results (Analysis by Integration Level)

The C and HD groups’ data are not normally distributed as evidenced by the ShapiroWilk Test that results in p-values of < 0.01, but the LD group’s data is normally 

distributed with a p-value of 0.10. We proceed with presenting ANOVA results because 

sample sizes are sufficiently large (n > 30) to satisfy the normality assumption for 

ANOVA. In addition, group standard deviations are sufficiently similar to satisfy the 

equal variance assumption for ANOVA. 

The fifth Indirect-Fire Mission is the 3-round low-angle HE from FP2 Indiv. Subsequent 

Rounds fire mission. The tables above show that, on average, the C group had a mean 

time of 19.88 seconds per round; the LD group, 22.32 seconds per round; and the HD 

group, 24.44 seconds per round. On average, the C group was faster than the LD and 

HD groups. The difference between the HD and C groups is statistically significant. 

H.5.3.2.2 Indirect-Fire Missions by Critical Billet

This second method of comparison for Indirect-Fire Missions looks at performance 

differences between gun crews grouped only by the gender of the Marines serving in 

critical billets. In this analysis, the critical billet for all Low-Angle Fire Missions is the 

Cannoneer #4, and it is denoted by either an (M) for male or an (F) for female. 

For the High-Angle Missions, there are two critical billets—the #1 Cannoneer and #4 

Cannoneer. The tables below display the Cannoneer #1 and #4 billets as a two-letter 

representation, where the first letter represents the gender of the Marine occupying the 

Cannoneer #1 billet and the second letter represents the gender of the Marine 

occupying the Cannoneer #4 billet.

H.5.3.2.2.1 Low-Angle Fire Mission by Critical Billet—Cannoneer #4

Four out of the five fire missions are low-angle fire missions and are analyzed below by 

the critical billet—Cannoneer #4. The four fire missions are: a 3-round low-angle High 

Explosive (HE), a 9-round low-angle HE, a 3-round low-angle smoke out-of-traverse 

limits, and, finally, another 3-round low-angle HE from the supplemental position. 

H.5.3.2.2.2 Low-Angle Fire Mission by Critical Billet—Cannoneer #4 Scatterplots

The scatterplots in figures H-17 through H-20 display the data used in the analysis of 

the results. All data points shown in the scatterplots were determined to be valid and 

used in the analysis and modeling. 
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Figure H-17. 3-Round Low-Angle HE; Indiv. Subsequent Rounds by Critical Billet
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Figure H-18. 9-Round Low-Angle HE; Indiv. Subsequent Rounds by Critical Billet

Figure H-19. 3-Round Low-Angle WP; Indiv. Subsequent Rounds by Critical Billet
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Figure H-20. 3-Round Low-Angle HE from FP2; Indiv. Subsequent Rounds by 

Critical Billet

H.5.3.2.2.3 Low-Angle Fire Mission by Critical Billet—Cannoneer #4 Data Table and 

Analysis

The tables below summarize the results of the task Indirect-Fire Missions analysis by 

Critical Billet (Low Angle Missions). Table H-14 compares means across metrics and 

integration levels. Table H-15 presents ANOVA and Tukey test results, bringing into 

focus those metrics that resulted in statistical significance along with their percentage 

differences

Table H-14. Indirect-Fire Mission Results (Descriptive Statistics by critical billet)

Metric

Integra

tion 

Level

Sampl

e Size Mean SD 

3-Round Low-Angle HE; 

Indiv. Subsequent 

Rounds

(average seconds per 

round)*

M 111 27.8

9 

10.3

3 

F 22 32.3

9 9.57

9-Round Low-Angle HE; 

Indiv. Subsequent 

Rounds

(average seconds per 

round)*

M 107 24.3

4 6.27

F 21 27.7

1 5.90
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3-Round Low-Angle 

WP; Indiv. Subsequent 

Rounds

(average seconds per 

round)†

M 105 24.6

6 6.98

F 20 26.5

0 5.63

3-Round Low-Angle HE 

from FP 2; Indiv. 

Subsequent Rounds

(average seconds per 

round)*

M 100 21.3

7 5.77

F 21 27.3

8 

11.3

6 

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

†Indicates contradicting statistical significance results between ANOVA and a nonparametric equivalent test.

Table H-15. Indirect-Fire Missions ANOVA and T-test Results 

Metric

F 

statistic 

(df) 

F 

Test

Pvalue

Comparison Difference % 

Difference

2-sided 

P-Value 

1-sided PValue 80% LCB

3-Round Low-Angle HE; 

Indiv. Subsequent Rounds

(average seconds per 

round)

3.41

(1, 131) 0.07* F-M 4.50 15.78% 0.06* 0.03*

(0.06*) 1.44

9-Round Low-Angle HE; 

Indiv. Subsequent Rounds

(average seconds per 

round)

5.16

(1, 126) 0.02* F-M 3.37 13.83% 0.02* 0.01*

(0.02*) 1.50

3-Round Low-Angle WP; 

Indiv. Subsequent Rounds

(average seconds per 

round)†

1.23

(1, 123) 0.27 F-M 1.84 7.44% 0.07† 0.03† 0.01†

3-Round Low-Angle HE 

from FP 2; Indiv. 

Subsequent Rounds

(average seconds per 

round)

12.68

(1, 119)

< 

0.01* F-M 6.01 28.11% 0.03* 0.01*

(0.03*) 2.65

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

†Results presented are from a Mann-Whitney non-parametric test due to non-normality.

H.5.3.2.2.3.1 3-Round Low-Angle (HE) by Critical Billet—Cannoneer #4

The M group data is not normally distributed as evidenced by the Shapiro-Wilk Test that 

results in a p-value of < 0.01, but the F group data is normally distributed with a p-value 

of 0.02. We proceed with presenting ANOVA results because they were confirmed by a 

Mann-Whitney Test with a p-value of 0.01. In addition, group standard deviations are 

sufficiently similar to satisfy the equal variance assumption for ANOVA

The tables above show that, on average, the M group had a mean time of 27.89

seconds per round, while the F group had a mean time of 32.39 seconds per round. On 
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average, the F group was 15.78% slower than the M group, and the difference is 

statistically significant in one-sided and two-sided hypothesis tests

H.5.3.2.2.3.2 9-Round Low-Angle (HE) by Critical Billet—Cannoneer #4

The M group data is not normally distributed as evidenced by the Shapiro-Wilk Test that 

results in a p-value of < 0.01, but the F group data is normally distributed with a p-value 

of 0.03. We proceed with presenting ANOVA results because they were confirmed by a 

Mann-Whitney Test with a p-value of < 0.01. In addition, group standard deviations are 

sufficiently similar to satisfy the equal variance assumption for ANOVA

The tables above show that, on average, the M group had a mean time of 24.34 

seconds per round. The F group had a mean time of 27.71 seconds per round. On 

average, the F group was 13.83% slower than the M group, and the difference is 

statistically significant in one-sided and two-sided hypothesis tests. 

H.5.3.2.2.3.3 3-Round Low-Angle (WP) by Critical Billet—Cannoneer #4

The M group data is not normally distributed as evidenced by the Shapiro-Wilk Test that 

results in a p-value of < 0.01, but the F group data is normally distributed with a p-value 

of 0.23. Because of a lack of normality, we recommend using the Mann-Whitney test 

results because they disagree with ANOVA test results. 

The tables above show that, on average, the M group had a mean time of 24.66

seconds per round. The F group had a mean time of 26.50 seconds per round. On 

average, the F group was 7.44% slower than the M group, and the difference is not 

statistically significant.

H.5.3.2.2.3.4 3-Round Low-Angle (HE) from FP2 by Critical Billet—Cannoneer #4

The M group and F group data are not normally distributed as evidenced by the 

Shapiro-Wilk Test that results in p-values of < 0.01. We proceed with presenting 

ANOVA results because they were confirmed by a Mann-Whitney Test with a p-value of 

< 0.01.

The tables above show that, on average, the M group had a mean time of 21.37

seconds per round. The F group had a mean time of 27.38 seconds per round. On 

average, the F group was 28.11% slower than the M group, and the difference is 

statistically significant in one-sided and two-sided hypothesis tests. 

H.5.3.2.2.4 High-Angle Fire Mission by Critical Billet—Cannoneers #1 and #4

One out of the five fire missions is a High-Angle fire mission. High-Angle fire missions 

are analyzed below by two critical billets—Cannoneer #1 and Cannoneer #4. The only 

High-Angle fire mission is the 3-round high-angle (WP) fire mission.
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H.5.3.2.2.5 High-Angle Fire Mission by Critical Billet—Cannoneer #1 and #4 Scatterplot

The scatterplot in Figure H-21 displays the data used in the analysis of the results. All 

data points shown in the scatterplots were determined to be valid and used in the 

analysis and modeling. 

Figure H-21. 3-Round High-Angle WP; Indiv. Subsequent Rounds by Critical Billet

H.5.3.2.2.6 High-Angle Fire Mission by Critical Billet—Cannoneer #1 and #4 Data Table 

and Analysis

The tables below summarize the results of the task Indirect-Fire Missions analysis by 

Critical Billet (High-Angle Mission). Table H-16 compares means across metrics and 

integration levels. Table H-17 presents ANOVA and Tukey test results, bringing into 

focus those metrics that resulted in statistical significance along with their percentage 

differences. 

Table H-16. High-Angle Fire Mission Results by critical billet

Metric Integration 

Level

Sample

Size Mean SD

3-Round High-Angle WP; Indiv. Subsequent 

Rounds

(average seconds per round)

MM 86 52.39 13.81

MF 19 66.65 15.76

FM 23 59.54 19.73
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FF 4 58.75 18.46

Table H-17. Indirect-Fire Missions by Critical Billet ANOVA and Tukey Test 

Metric

F 

Statistic

(df)

F

Test 

PValue

Comparison Difference % 

Difference

PValue80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

3-Round 

High-Angle 

WP; Indiv. 

Subsequent 

Rounds

(average 

second per 

round)

5.07

(3, 128)

< 

0.01*

MF-MM 14.27 27.24% < 

0.01* 6.65 21.99 5.24 23.29

FM-MM 7.16 13.66% 0.20 0.00 14.31 -1.20 15.51

FF-MM 6.36 12.15% 0.85 -9.23 21.96 -

11.84 24.57

MF-FM 7.11 11.94% 0.45 -2.34 16.56 -3.93 18.14

FF-MF -7.90 -11.86% 0.79 -

24.67 8.87 -27.48 11.68

FF-FM -0.79 -1.33% 1.00 -

17.31 15.72 -20.08 18.49

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

H.5.3.2.2.6.1 3-Round High-Angle (WP) by Critical Billet—Cannoneer #1 and Cannoneer 

#4

The MM group data is not normally distributed as evidenced by the Shapiro-Wilk Test 

that results in a p-value of < 0.01, but the FF, FM, and MF groups’ data are normally 

distributed with p-values of 0.81, 0.08, and 0.01. We proceed with presenting ANOVA 

results because they were confirmed by a Kruskal-Wallis Test with a p-value of < 0.01.

In addition, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA

For the High-Angle critical billet analysis, the #1 Cannoneer and #4 Cannoneer were 

used to calculate the following average times. For the 3-Round High-Angle WP Indiv. 

Subsequent Rounds, the MM group had a mean time of 52.39 seconds per round; the 

MF group, 66.65 seconds per round; the FM group, 59.54 seconds per round; and the 

FF group, 58.75 seconds per round. On average, the MF group was 27.24% slower 

than the MM group, and the difference between the MF and MM groups is statistically 

significant. On average, the FM was 13.66% slower than the MM group, and the 

difference between the FM and MM groups is not statistically significant. On average, 

the FF group was 12.15% slower than the MM group, and the difference between the 

FF and MM groups is not statistically significant. 
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H.5.3.3 Indirect-Fire Missions Contextual Comments

The Fire Mission is the crux of Marine Artillery. The timely delivery of fires in support of 

maneuver units is top priority for every Artillery Unit, and all efforts inevitably lead to the 

pursuit of increased responsiveness and accuracy of fire support. Fire missions come 

in many varieties, from planned fires to immediate suppression. In kinetic operations, 

presuming the safe operation of the howitzer, speed is paramount, delays 

unacceptable, and missed timelines abject failures. The specific disparities between the 

times listed in the above tables are important, but less so than the disparities in the 

context of aggregate effect. One would expect the difference in responsiveness to 

become more pronounced as time and fatigue increase, particularly over the course of a 

deployment. Further, given the often reactionary nature of fires, any degradation of fire 

responsiveness is a detriment to the supported Marines.

H.5.4 Out-of-Traverse Limits Overview

When providing fire support in a sprawling battle space, it is not a guarantee that the 

enemy target will always be in line with the azimuth of fire. FDCs will routinely shift 

howitzers while battle tracking troops in contact. Aligning the howitzer on a potential 

target, known as “laying,” allows the section to get a head start if a fire mission is 

requested. Otherwise, and more often than not, the fire mission response will take as 

long as it takes the howitzer section to shift onto the target. The speed shift in the 

experiment’s scheme of maneuver was the latter, tied to a fire mission. The time at 

which the howitzer could initially respond to the target was dependent on how fast the 

howitzer could shift. 

The out-of-traverse task, also known as a speed shift, happened in conjunction with the 

3-round low-angle smoke mission. The FDC initiates the fire mission by passing the fire 

commands to the howitzer sections. Once the FDC stated “do not load, azimuth...,” the 

crew began pumping the suspension and uprooting the spades. Once the crew was 

balancing the howitzer on its wheels, the gunner gave the direction to shift. One of the 

wheels had its brake released, and the crew pushed the cannon tube in the direction the 

gunner stated. When the gunner was aligned with the new azimuth, he halted the crew 

and dropped the howitzer into position. A second speed shift was triggered after end of 

mission was given by the FDC. The calculations below show the elapsed time from the 

FDC start until the gunner’s command to drop the howitzer. Because terrain could 

sometimes require the Section Chief to reposition his gun, the calculations are 

computed based on the first drop. 

This task is performed by all six Cannoneers. However, the two most physically 

demanding positions (and the critical billets) are the numbers 1 and 2 Cannoneers, 

doctrinally responsible for pumping the howitzer’s suspension. The remaining crew 
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members are responsible for providing leverage to dislodge the spades and pushing the 

gun to the new azimuth.

The data collected from the out-of -traverse task was analyzed in two separate ways. 

The first method of comparison examined performance differences between the control 

group (C), the low-density group (LD), and a high-density group (HD). The second

method compared performance differences between gun crews grouped by the gender 

of the critical billets, regardless of the crew composition. The critical billets identified for 

the out-of-traverse mission were the #1 and # 2 Cannoneers. 

H.5.4.1 Out-of-Traverse by Integration Level Scatterplots

The scatterplots in figures H-22 and H-23 display the data used in the analysis of the 

results. All data points shown in the scatterplots were determined to be valid and used 

in the analysis and modeling. 

Figure H-22. Speed Shift #1; First Drop by Integration Level
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Figure H-23. Speed Shift #2; First Drop by Integration Level

H.5.4.2 Out of Traverse by Integration Level Data Table and Analysis

The tables below summarize the results of the task Out-of-Traverse analysis by 

Integration Level. Table H-18 compares means across metrics and integration levels. 

Table H-19 presents ANOVA and Tukey test results bringing to focus those metrics that 

resulted in statistical significance along with their percentage differences.

Table H-18. Speed Shift by Integration Level

Metric Integration 

Level

Sample

Size Mean SD

Speed Shift #1; First Drop

(minutes)

C 42 3.53 1.08

LD 43 3.74 1.25

HD 54 3.46 1.05

Speed Shift #2; First Drop

(minutes)

C 41 3.24 0.96

LD 42 3.17 0.99

HD 49 3.16 0.98
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Speed Shift #2; First Drop [Excluding 

Influential Points]

(minutes)

C 41 3.24 0.96

LD 42 3.17 0.99

HD 48 3.07 0.76

Table H-19. Speed Shift by Integration Level ANOVA and Tukey Test 

Metric

F 

Statistic

(df)

F 

Test 

PValue

Comparison Difference % 

Difference

PValue80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Speed Shift 

#1; First 

Drop

(minutes)

0.78

(2, 136)

0.46

LD-C 0.21 5.97% 0.66 -0.21 0.63 -

0.29 0.72

HD-C -0.07 -1.97% 0.95 -0.47 0.33 -

0.55 0.41

HD-LD -0.28 -7.49% 0.44 -0.68 0.12 -

0.76 0.20

Speed Shift 

#2; First 

Drop

(minutes)

0.08

(2, 129)

0.92

LD-C -0.07 -2.10% 0.95 -0.44 0.30 -

0.51 0.38

HD-C -0.08 -2.41% 0.92 -0.43 0.28 -

0.51 0.35

HD-LD -0.01 -0.32% 1.00 -0.36 0.34 -

0.43 0.41

Speed Shift 

#2; First 

Drop 

[Excluding 

Influential 

Points]

(minutes)

0.39

(2, 128)

0.68

LD-C -0.07 -2.14% 0.94 -0.41 0.27 -

0.48 0.27

HD-C -0.17 -5.14% 0.66 -0.50 0.16 -

0.56 0.16

HD-LD -0.10 -3.11% 0.86 -0.43 0.23 -

0.49 0.23

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

H.5.4.2.1 Out of Traverse by Integration Level

For Speed Shift #1, the C and HD groups’ data are not normally distributed as 

evidenced by the Shapiro-Wilk Test that results in p-values of < 0.01, but the LD group’s 

data is normally distributed with a p-value of 0.02. We proceed with presenting ANOVA 

results because sample sizes are sufficiently large (n > 30) to satisfy the normality 
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assumption for ANOVA. In addition, group standard deviations are sufficiently similar to 

satisfy the equal variance assumption for ANOVA

For Speed Shift #1, the C group had a mean time of 3.53 minutes; the LD group, 3.74 

minutes, and the HD group, 3.46 minutes. No comparison is statistically significant. 

For Speed Shift #2, the C and HD groups’ data are not normally distributed as 

evidenced by the Shapiro-Wilk Test that results in p-values of < 0.01, but the LD group’s 

data is normally distributed with a p-value of 0.01. We proceed with presenting ANOVA 

results because sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA. In addition, group standard deviations are sufficiently similar to 

satisfy the equal variance assumption for ANOVA

For Speed Shift #2, the C group had a mean time of 3.24 minutes; the LD group, 3.17 

minutes; and the HD group, 3.16 minutes. No comparison is statistically significant. 

For Speed Shift #2 [Excluding Influential Points], the C group had a mean time of 3.24 

minutes; the LD group, 3.17 minutes; and the HD group 3.07 minutes. No comparison 

is statistically significant. 

H.5.4.3 Speed Shift by Critical Billet—#1 and #2 Cannoneers

This second method of comparison for the Out-of-Traverse task examines performance 

differences between gun crews grouped only by the gender of the Marines serving in 

two critical billets. In this analysis, the first critical billet is the Cannoneer #1, and it is 

denoted by either a (M) for male or a (F) for female. The second critical billet is the 

Cannoneer #2 and, again, is also depicted by a (M) or (F) to denote the gender of the 

Marine. The tables below display the Cannoneer #1 and #2 billets as a two-letter 

representation, where the first letter represents the gender of the Marine occupying the 

Cannoneer #1 billet and the second letter represents the gender of the Marine 

occupying the Cannoneer #2 billet.

H.5.4.4 Speed Shift by Critical Billet—#1 and #2 Cannoneer Scatterplots

The scatterplots in figures H-24 and H-25 display the data used in the analysis of the 

results. All data points shown in the scatterplots were determined to be valid and used 

in the analysis and modeling. 

 
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Figure H-24. Speed Shift #1; First Drop by Critical Billet
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Figure H-25. Speed Shift #2; First by Critical Billet

H.5.4.5 Speed Shift by Critical Billet—#1 and #2 Cannoneers Data Table Analysis

The tables below summarize the results of the task Out-of-Traverse analysis by Critical 

Billets. Table H-20 compares means across metrics and integration levels. Table H-21

presents ANOVA and Tukey test results bringing into focus those metrics that resulted 

in statistical significance along with their percentage differences.

Table H-20. Speed Shift Results by Critical Billet

Metric Integration 

Level

Sample

Size Mean SD

Speed Shift #1; First Drop

(minutes)

MM 86 3.41 1.06

MF 24 3.99 1.14

FM 24 3.39 0.93

FF 5 4.98 1.70

Speed Shift #2; First Drop

(minutes)

MM 82 3.03 0.92

MF 21 3.52 1.00
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FM 24 3.22 0.64

FF 5 4.22 1.93

Speed Shift #2; First Drop [Excluding 

Influential Points]

(minutes)

MM 82 3.03 0.92

MF 21 3.52 1.00

FM 24 3.22 0.64

FF 4 3.42 0.85

Table H-21. Speed Shift by Critical Billet ANOVA and Tukey Test 

ANOVA and 

Tukey Test 

ResultsMetric

F 

Statistic

(df)

F 

Test 

PValue

Comparison Difference % 

Difference

PValue

80 

% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Speed Shift 

#1; First 

Drop

(minutes)

4.92

(3, 135)

< 

0.01*

MF-MM 0.58 17.03% 0.10* 0.09 1.07 0.01 1.16

FM-MM -0.02 -0.60% 1.00 -

0.51 0.47 -0.60 0.56

FF-MM 1.57 46.00% 0.01* 0.59 2.55 0.42 2.72

MF-FM 0.60 17.74% 0.22 -

0.02 1.22 -0.12 1.32

FF-MF 0.99 24.76% 0.25 -

0.06 2.04 -0.24 2.21

FF-FM 1.9 46.89% 0.02* 0.54 2.64 0.36 2.82

Speed Shift 

#2; First 

Drop

(minutes)††

7.45 0.06*

MF-MM 0.49 16.23% 0.05 0.18 0.81 0.08 0.90

FM-MM 0.19 6.31% 0.25 -

0.02 0.41 -0.09 0.47

FF-MM 1.19 39.17% 0.24 -

0.14 2.52 -0.65 3.03

MF-FM 0.30 9.34% 0.25 -

0.03 0.63 -0.13 0.73

FF-MF 0.70 19.73% 0.47 -

0.64 2.03 -1.14 2.54
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FF-FM 1.00 30.91% 0.32 -

0.33 2.33 -0.84 2.84

Speed Shift 

#2; First 

Drop

[Excluding 

Influential 

Points]

(minutes)

1.90

(3, 127)

0.13

MF-MM 0.49 16.23% 0.11 0.06 0.92 -

0.01 1.00

FM-MM 0.19 6.31% 0.79 -

0.22 0.60 -0.29 0.67

FF-MM 0.39 12.81% 0.83 -

0.51 1.29 -0.67 1.44

MF-FM 0.30 9.34% 0.67 -

0.23 0.83 -0.31 0.92

FF-MF -0.10 -2.94% 1.00 -

1.07 0.86 -1.23 1.02

FF-FM 0.20 6.12% 0.98 -

0.75 1.15 -0.91 1.31

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

††Indicates results presented are from Robust ANOVA and Welch’s t-tests with p-values compared to 

0.0167 for Bonferroni adjustment. F-statistics is a Chi-square statistic from Robust ANOVA, and the F-test 

Pp-value is from a Robust ANOVA. The P-values are two-sided p-values from Welch’s t-tests and the CIs 

are from Welch’s t-tests

H.5.4.5.1 Out of Traverse by Critical Billet—#1 and #2 Cannoneers 

For Speed Shift #1, the MM group data is not normally distributed as evidenced by the 

Shapiro-Wilk Test that results in a p-value of < 0.01, but the FF, FM, and MF groups’ 

data are normally distributed with p-values of 0.42, 0.38, and 0.03. We proceed with 

presenting ANOVA results because they were confirmed by a Kruskal-Wallis Test with a 

p-value of < 0.01. In addition, group standard deviations are sufficiently similar to satisfy 

the equal variance assumption for ANOVA

For Speed Shift #1, the tables above show that, on average, the MM group had a mean 

time of 3.41 minutes. The MF group had a mean time of 3.99 minutes (17.03% slower 

than the MM group), and the difference is statistically significant. The FM group had a 

mean time of 3.39 minutes (0.60% faster than the MM group), and the difference is not 

statistically significant. The FF group had a mean time of 4.98 minutes (46.00% slower 

than the MM group), and the difference is statistically significant.

For Speed Shift #2, the MM group data is not normally distributed as evidenced by the 

Shapiro-Wilk Test that results in a p-value of < 0.01, but the FF, FM, and MF groups’ 

data are normally distributed with p-values of 0.33, 0.31, and 0. 83. In addition, the FF 
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group standard deviation is more than twice that of the FM group. As such, we 

recommend using the robust ANOVA results shown above. We proceed with presenting

robust ANOVA results because they were confirmed by a Kruskal-Wallis Test with a pvalue of 0.02.

For Speed Shift #2, the tables above show that, on average, the MM group had a mean 

time of 3.03 minutes. The MF group had a mean time of 3.52 minutes (16.23% slower 

than the MM group), and the difference between is not statistically significant. The FM 

group had a mean time of 3.22 minutes (6.31% slower than the MM group), and the 

difference is not statistically significant. The FF group had a mean time of 4.22 minutes

(39.17% slower than the MM group), and the difference is statistically significant. 

Although the data seem to indicate that it matters who is in the #1 position as compared 

to #2 (MF vs FM), it is important to note that these billets are essentially mirror images 

of each other. There is no advantage to dominant hand or bodily positioning in relation 

to the lever. In both cases, the Marine is operating a suspension lever (a second-class 

lever) with the fulcrum near the bottom of the howitzer and the effort approximately 4.5 

feet off the deck.

For Speed Shift #2, if the Influential Points are excluded, the FF group’s mean time 

drops significantly, averaging 3.42 minutes. The MM and FF group comparison is no 

longer statistically significant and drops to a 12.81% difference. 

H.5.4.5.2 Out-of-Traverse Limits Contextual Comments

It is important to note that, when the Out-of-Traverse task was analyzed by integration 

level, there was no statistical significance between the three groups. However, when 

the task is analyzed by critical billet, there was a statistical difference between the MF 

and the FF groups. 

This task is particularly vulnerable to the impacts of two individual Marines. The task 

itself does not lend itself to compensation or adaptation, as all Marines tend to be 

completely occupied with individual and group responsibilities. This is highlighted by

the disparities in results between integration level and critical billet makeup.

H.5.5 Displacement by Integration Level 

Two displacements were captured during each trial. The first displacement began at 

fire position one and required the volunteers to upload ammunition and retrieve the crew 

serve weapon in addition to displacing the howitzer. The second displacement was 

located at fire position two and required the volunteers to displace only the howitzer. 

The first displacement time hacks were complicated by the additional tasks. Therefore, 

the second displacement, also known as the final displacement, was chosen for primary 

analysis because it was purely the displacement task without additional subtasks 

embedded.
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The actions completed by the howitzer section included the #1 Cannoneer engaging the 

traverse lock; #4 Cannoneer inserting the trident bar into the lunette assembly; and #1 

and #2 Cannoneers pumping the suspension to ride height, attaching the howitzer to 

the prime mover, stowing the trail arms, and finally climbing into the back of the prime 

mover. The time for this task started when the Section Chief gave the order to begin 

and finished when the last volunteer was seated in the back of the truck. The results for 

total displacement time for the final displacement are shown below. See the Artillery 

Appendix for the first displacement, trident bar, and trail arm calculations. 

H.5.6 Displacement by Integration Level Scatterplot

The scatterplot in Figure H-26 displays the data used in the analysis of the results. All 

data points shown were determined to be valid and used in the analysis and modeling. 

Figure H-26. Final Displacement of Howitzer; Total Displacement by Integration Level

H.5.7 Displacement by Integration Level Data Table and Analysis

The tables below summarize the results of the task Displacement. Table H-22

compares means across metrics and integration levels. Table H-23 presents ANOVA 
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and Tukey test results, bringing into focus those metrics that resulted in statistical 

significance along with their percentage differences.

Table H-22. Displacement by Integration Level

Metric Integration 

Level

Sample

Size Mean SD

Final Displacement of Howitzer; Total 

Displacement

(minutes)

C 35 3.36 0.62

LD 38 3.49 0.71

HD 48 3.88 0.84

Table H-23. Displacement by Integration Level ANOVA and Tukey Test 

Metric

F 

Statistic

(df)

F 

Test 

PValue

Comparison Difference % 

Difference

PValue

80 

% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Final 

Displacement 

of Howitzer; 

Total 

Displacement

(minutes)

5.63

(2, 118)

< 

0.01*

LD-C 0.12 3.71% 0.76 -

0.18 0.43 -0.24 0.49

HD-C 0.52 15.43% < 

0.01* 0.23 0.80 0.18 0.86

HD-LD 0.39 11.30% 0.04* 0.11 0.67 0.06 0.73

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a non-parametric equivalent test.

The C, LD, and HD groups’ data are normally distributed as evidenced by the ShapiroWilk Test that results in p-values of 0.87, 0.02, and 0.33. In addition, group standard 

deviations are sufficiently similar to satisfy the equal variance assumption for ANOVA

The tables above show that, on average, the C group had a mean time of 3.36 minutes; 

the LD group, 3.49 minutes; and the HD group, 3.88 minutes. On average, the LD 

group was 3.71% slower than the C group, and the difference between the LD and C 

group is not statistically significant in a Tukey test. On average, the HD group was 

15.43% slower than the C group, and the difference between the HD and C group is 

statistically significant. 

H.5.7.1 Displacement by Integration Level Contextual Comments

The displacement of the howitzer is critical to the survivability of the battery and 

maintaining responsive fires. During battle against an opponent capable of counter-
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battery fire, the ability to execute a fire mission and displace in a timely manner is vital. 

Furthermore, in a fluid battlespace with evolving friendly and enemy situations, the 

requirement to move the battery occurs often. The speed at which the battery can 

emplace and displace is directly tied to firing capability and responsiveness. 

H.6 Modeling Results

H.6.1 Statistical Modeling Results

H.6.1.1 Statistical Modeling Results Overview

The previous section discussed results only as they pertain to differences due to 

integration level and gender in critical billets. The goal of statistical modeling as applied 

here is to estimate, simultaneously, the effect of gender integration levels and other 

relevant variables on crew performance. This section describes all significant variables 

in the model and their positive or negative correlation with the result. A negative 

correlation indicates that an increase in a particular variable will result in a decrease in 

the response variable, which is a desired outcome for elapsed time for some tasks. 

Refer to the Methodology Annex for a broad overview of the analysis plan and the 

variables used in the models.

The descriptive statistics section above covers a total of 16 tasks. This section presents 

an overview of the analysis and modeling results for 11 out of the 16 tasks. The 11

selected modeled tasks were identified as necessary to inform the time-sensitive 

decision by Marine Corps leadership. 

Table H-24. Patch Numbers and Billet Titles for the Section

Patch Number Billet Title

1 Cannoneer #1 / A-Gunner

2 Cannoneer #2

3 Cannoneer #3

4 Cannoneer #4/5

5 Recorder

6 Driver

H.6.1.2 0811 Selected Tasks Method of Analysis

Due to the large number of personnel variables that need to be included in the model 

(six covariates, per variable), a mixed-effects model with all volunteer section members 

and all types of personnel data could not be run. Thus, we model each personnel 
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variable with integration level separately with a random effect for who filled each 

position within the section. For example, age for each volunteer member of the section

(six variables) and integration level are modeled with the result (elapsed time) as the 

response variable. Where maximum likelihood estimation converged, AIC was used for 

variable selection. Otherwise, we comment on the significance of individual variables in 

the full model. Variables reported as significant are concluded to be significant based 

on at least a one-sided test.

H.6.1.3 Selected Tasks Overall Modeling Results

There are no personnel data variables that are both statistically significant and have a 

practical impact to the model. Each time personnel data variables are statistically 

significant in a model, their effects are practically negligible, conflicting, and/or 

incomplete for the section. 

Integration level appears in most of the tasks where a critical billet is statistically 

significant, and its effect is clear, causal, and practical. Therefore, integration level is 

the best variable to describe performance for most of these tasks. CFT Maneuver 

Under Fire also appears to be common for certain billets in certain tasks. Refer to the 

descriptive statistics section for the ANOVA summary for each of the 0811 tasks 

mentioned below .

H.6.1.3.1 First Emplacement Ammo Truck Offload

We model elapsed time for the First Emplacement’s Ammo Truck Offload as a function 

of each personnel variable and integration level in a separate mixed model. The 

covariates in each model are the values of each personnel variable for each patch 

number, integration level, and a random effect of who filled each volunteer position on 

the section. For each model, we report statistically significant positive and negative 

correlations and whether we observe any patterns.

Gender integration levels are significant and positively correlated with the First 

Emplacement Truck Offload time for the models that include the following personnel 

variables:

• None

Gender integration levels are significant and negatively correlated with the First 

Emplacement Truck Offload time for the models that include the following personnel 

variables:

• None

The following personnel variables are significant in their respective models and are 

positively correlated with the First Emplacement Truck Offload time:
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• Height of the Recorder

• CFT Maneuver under Fire time for Cannoneer #1

The following personnel variables are significant in their respective models and are 

negatively correlated with the First Emplacement Truck Offload time:

• AFQT Score of Cannoneer #4, Driver, and Recorder

• Weight of Cannoneer #3 and Cannoneer #4

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, our final model includes only the intercept, meaning that we 

could not determine a mixed model that fits the data well. We recommend referring 

back to ANOVA results in Table X for differences between integration groups.

**Cannoneers #3 and 4 have no involvement in this task and have no impact on its 

completion.

H.6.1.3.2 Ammo Resupply: Ammo Movement

We model elapsed time for the Ammo Resupply as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and 

a random effect of who filled each volunteer position on the section. For each model, 

we report statistically significant positive and negative correlations and whether we 

observe any patterns.

Gender integration levels are significant and positively correlated with the Ammo 

Resupply time for the models that include the following personnel variables:

• None

Gender integration levels are significant and negatively correlated with the Ammo 

Resupply time for the models that include the following personnel variables:

• None

The following personnel variables are significant in their respective models and are 

positively correlated with the First Emplacement Truck Offload time:

• CFT Maneuver Under Fire Time of Cannoneer #1, Cannoneer #4, and Recorder

• PFT: Run of Cannoneer #3

• Rifle Score of the Driver. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the First Emplacement Truck Offload time:

• AFQT Score of the Driver
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• CFT Maneuver Under Fire Time of Cannoneer #2

• PFT: Crunches of Cannoneer #4. 

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, our final model includes only the intercept, meaning that we 

could not determine a mixed model that fits the data well. We recommend referring 

back to ANOVA results in Table X for differences between integration groups.

**This event involved the Marines moving rounds independently, and the time is only 

representative of the slowest Marine.

H.6.1.3.3 Ammo Truck Upload

We model elapsed time for the Ammo Truck Upload as a function of each personnel 

variable and integration level in one single mixed model. The covariates in the model 

are the values of each personnel variable for each patch number, integration level, and 

a random effect of who filled each volunteer position on the section. For the model, we 

report statistically significant positive and negative correlations and whether we observe 

any patterns.

In the overall model, gender integration levels were significant and positively correlated 

with Ammo Truck Upload time. 

The following personnel variables are significant in the overall model and are positively 

correlated with the Ammo Truck Upload time:

• GCT Score of Cannoneer #1 and Cannoneer #2

• CFT Movement to Contact of Cannoneer #1

• CFT Maneuver under Fire Times of Cannoneer #2, Cannoneer #4, and Recorder

• PFT: Crunches of Cannoneer #2 and Driver

• Physical Fitness Run Time of the Driver

• AFQT Score of Cannoneer #4

• Height of Cannoneer #4

• Age of the Recorder.

The following personnel variables are significant in the overall model and are negatively 

correlated with the Ammo Truck Upload time:

• AFQT Score of Cannoneer #1 and Cannoneer #2 

• Weight of Cannoneer #1 and Cannoneer #2

• Physical Fitness Run Time of Cannoneer #1 and Cannoneer #4

• Rifle Score of Cannoneer #2, Cannoneer #3, Recorder, and Cannoneer #4

• Height of Cannoneer #3

• Age of Cannoneer #4

• GCT Score of Cannoneer #4

• PFT: Crunches of the Recorder.
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Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, our final model includes only gender integration levels. 

Holding all other variables constant, HD groups are expected to perform this task 0.26 

minute slower than C groups, while LD groups are expected to perform this task 0.35 

minute slower than C groups. 

**Cannoneer #3 and 4 had no involvement in this task and had no impact on its 

completion.

H.6.1.3.4 Final Displacement of Howitzer; Total Displacement

We model elapsed time for the Final Displacement of Howitzer as a function of each 

personnel variable and integration level in one single mixed model. The covariates in 

the model are the values of each personnel variable for each patch number, integration 

level, and a random effect of who filled each volunteer position on the section. For the 

model, we report statistically significant positive and negative correlations and whether 

we observe any patterns.

Gender integration levels were selected by the AIC into the final model of elapsed time 

to displace the howitzer. 

The following personnel variables are significant in their respective models and are 

positively correlated with the First Emplacement Truck Offload time:

• None.

The following personnel variables are significant in their respective models and are 

negatively correlated with the First Emplacement Truck Offload time:

• Weight of Cannoneer #2 and Cannoneer #3

• CFT Maneuver Under Fire Time of Cannoneer #2

• PFT: Crunches of Cannoneer #2 and Cannoneer #4

• Rifle Score of the Recorder. 

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, our final model includes only gender integration levels. 

Based on the model, although all other variables remain constant, a low-density 

integration is expected to result in displacement happening approximately 0.24 minute 

faster, on average, than would be done by the non-integrated group. The model 

indicates that, although all other variables remain constant, a high-density integration is 

expected to result in displacement happening approximately 0.24 minute slower, on 

average, than would be done by the non-integrated group. 
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H.6.1.3.5 3-Round High-Angle WP; Indiv. Subsequent Rounds

We model elapsed time for the 3-Round High-Angle WP task as a function of each 

personnel variable and integration level in a separate mixed model. The covariates in 

each model are the values of each personnel variable for each patch number, 

integration level, and a random effect of who filled each volunteer position on the 

section. For each model, we report statistically significant positive and negative 

correlations and whether we observe any patterns.

The critical billet MM integration level is significant and positively correlated for the 

models that include the following variables: 

• None

The critical billet MM integration level is significant and negatively correlated for the 

models that include the following variables: 

• Age

• AFQT Score

• GCT Score

• Weight

• Physical Fitness Test: Crunches. 

The following personnel variables are significant in their respective models and are 

positively correlated with the First Emplacement Truck Offload time:

• Age of Cannoneer #2

• AFQT Score of Cannoneer #2 and Cannoneer #3

• GCT Score of Cannoneer #2

• CFT Maneuver under Fire Time of Cannoneer #2 and Cannoneer #4

• Physical Fitness Run Time of Cannoneer #2 and Cannoneer #4. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the First Emplacement Truck Offload time:

• AFQT Score of the Driver

• Height of Cannoneer #2. 

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, our final model includes only Critical Billet. Based on the 

model, although all other variables remain constant, a MM critical billet is expected to 

perform this task approximately 0.19 minute faster, on average, than would be done by 

a FF critical billet. The FM and MF levels of critical billet are insignificantly different from 

the FF level. 
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H.6.1.3.6 3-Round Low-Angle HE; Indiv. Subsequent Rounds

We model elapsed time for the 3-Round Low-Angle HE task as a function of each 

personnel variable and integration level in a separate mixed model. The covariates in 

each model are the values of each personnel variable for each patch number, 

integration level, and a random effect of who filled each volunteer position on the 

section. For each model, we report statistically significant positive and negative 

correlations and whether we observe any patterns.

 

The critical billet was significant and positively correlated with males for the models that 

include that following variables: 

• None

The critical billet was significant and negatively correlated with males for the models that 

include that following variables: 

• Age

• Weight

• Physical Fitness Test: Crunches

• Rifle Score. 

The following personnel variables are significant in their respective models and are 

positively correlated with the First Emplacement Truck Offload time:

• Age of Cannoneer #2

• Physical Fitness Run Time of Cannoneer #4. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the First Emplacement Truck Offload time:

• AFQT Score of Cannoneer #3 and Driver

• HEIGHT of Cannoneer #2, Cannoneer #3, and Cannoneer #4

• Weight of Cannoneer #3

• CFT Maneuver under Fire Time of the Driver

• PFT: Crunches of Cannoneer #4 and Driver. 

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, our final model includes only Critical Billet. Based on the 

model, although all other variables remain constant, a male is expected to perform this 

task approximately 0.11 minute faster, on average, than would be done by a female. 

**Recorder’s physical condition has no impact on this activity, as this Marine is sitting for 

the entire evolution.
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H.6.1.3.7 9-Round Low-Angle HE; Indiv. Subsequent Rounds

We model elapsed time for the 9-Round Low-Angle HE task as a function of each 

personnel variable and integration level in a separate mixed model. The covariates in 

each model are the values of each personnel variable for each patch number, 

integration level, and a random effect of who filled each volunteer position on the 

section. For each model, we report statistically significant positive and negative 

correlations and whether we observe any patterns.

The critical billet M level is significant and positively correlated for the models that 

include the following variables: 

• None

The critical billet M level is significant and negatively correlated for the models that 

include the following variables: 

• Age

• AFQT Score

• GCT Score

• Physical Fitness Test: Crunches

• Physical Fitness Test: Run Time

• Rifle score. 

The following personnel variables are significant in their respective models and are 

positively correlated with the First Emplacement Truck Offload time:

• Age of Cannoneer #1

• CFT Maneuver under Fire Time of Cannoneer #2 and Cannoneer #4

• Physical Fitness Run Time of Cannoneer #2. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the First Emplacement Truck Offload time:

• AFQT Score of Cannoneer #4

• GCT Score of Cannoneer #4

• Height of Cannoneer #2 and Cannoneer #4

• Weight of Cannoneer #4

• CFT Maneuver under Fire Time of the Driver. 

Because we did not identify any discernable patterns in the effects of the personnel 

variables, and because their effects are often negligible, our final model includes only 

Critical Billet. Based on the model, although all other variables remain constant, a male 

is expected to perform this task approximately 0.08 minute faster, on average, than 

would be done by a female. 
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H.6.1.3.8 3-Round Low-Angle WP; Indiv. Subsequent Rounds

We model elapsed time for the 3-Round Low-Angle WP task as a function of each 

personnel variable and integration level in a separate mixed model. The covariates in 

each model are the values of each personnel variable for each patch number, 

integration level, and a random effect of who filled each volunteer position on the 

section. For each model, we report statistically significant positive and negative 

correlations and whether we observe any patterns.

The M Critical Billet level is significant and positively correlated for the models that 

include the following variable:

 

• None

The M Critical Billet level is significant and negatively correlated for the models that 

include the following variable: 

• None

The following personnel variables are significant in their respective models and are 

positively correlated with the First Emplacement Truck Offload time:

• AFQT Score of Cannoneer #2

• GCT Score of Cannoneer #1 and Cannoneer #2

• Height of the Recorder

• CFT Maneuver under Fire Time of Cannoneer #4. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the First Emplacement Truck Offload time:

• Weight of Cannoneer #4

• Rifle Score of the Driver. 

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, our final model includes only Critical Billet. Based on the 

model, although all other variables remain constant, a male is expected to perform this 

task approximately 0.04 minute faster, on average, than would be done by a female. 

H.6.1.3.9 3-Round Low-Angle HE from FP2; Indiv. Subsequent Rounds

We model elapsed time for the 3-Round Low-Angle HE from FP2 task as a function of 

each personnel variable and integration level in a separate mixed model. The 

covariates in each model are the values of each personnel variable for each patch 

number, integration level, and a random effect of who filled each volunteer position on 

the section. For each model, we report statistically significant positive and negative 

correlations and whether we observe any patterns.
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The critical billet M level is significant and positively correlated for the models that 

include the following variables: 

• None

The critical billet M level is significant and negatively correlated for the models that 

include the following variables: 

• Age

• AFQT Score

• GCT Score

• Height

• Weight

• Physical Fitness Test: Crunches

• Physical Fitness Test: Run Time

• Rifle Score. 

The following personnel variables are significant in their respective models and are 

positively correlated with the First Emplacement Truck Offload time:

• Age of Cannoneer #3 and Cannoneer #4

• AFQT Score of Cannoneer #3

• GCT Score of Cannoneer #3

• Weight of the Recorder

• CFT Maneuver under Fire Time of Cannoneer #3 and Cannoneer #4

• PFT: Crunches of Cannoneer #3. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the First Emplacement Truck Offload time:

• AFQT Score of the Recorder

• GCT Score of the Recorder

• Height of Cannoneer #3

• Weight of Cannoneer #3

• PFT: Crunches of the Driver

• Physical Fitness Run Time of Cannoneer #1. 

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, our final model includes only Critical Billet. Based on the 

model, although all other variables remain constant, a male is expected to perform this 

task approximately 0.09 minute faster, on average, than would be done by a female. 
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H.6.1.3.10 Speed Shift #1; First Drop

We model elapsed time for the Speed Shift #1; First Drop as a function of each 

personnel variable and integration level in one single mixed model. The covariates in 

the model are the values of each personnel variable for each patch number, integration 

level, and a random effect of who filled each volunteer position on the section. For the 

model, we report statistically significant positive and negative correlations and whether 

we observe any patterns.

Critical Billet levels were selected by the AIC into the final model for the elapsed time of 

Speed Shift 1. 

The following personnel variables are significant in their respective models and are 

positively correlated with the First Emplacement Truck Offload time:

• Age of Cannoneer #2 

• GCT Score of Cannoneer #2

• CFT Maneuver Under Fire Time of Cannoneer #3. 

The following personnel variables are significant in their respective models and are 

negatively correlated with the First Emplacement Truck Offload time:

• Height of Cannoneer #4

• PFT: Run Time of Cannoneer #1. 

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, our final model includes only Critical Billet levels. Based on 

the model, although all other variables remain constant, a FM group is expected to 

perform this task approximately 1.62 minutes faster, on average, than would be done by 

the FF group. Again holding all other variables constant, a MF group is expected to 

perform this task approximately 1.02 minutes faster, on average, than would be done by 

the FF group. Again holding all other variables constant, a MM group is expected to 

perform this task approximately 1.58 minutes faster, on average, than would be done by 

the FF group. 

H.6.1.3.11 Speed Shift #2; First Drop

We model elapsed time for the Speed Shift #2; First Drop as a function of each 

personnel variable and integration level in one single mixed model. The covariates in 

the model are the values of each personnel variable for each patch number, integration 

level, and a random effect of who filled each volunteer position on the section. For the 

model, we report statistically significant positive and negative correlations and whether 

we observe any patterns.

Critical Billet levels were selected by the AIC into the final model for the elapsed time of 

Speed Shift 1. 
GCEITF EAR ANNEX H

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AUGUST 2015 H-74

Critical Billet levels were selected by the AIC into the final model for the elapsed time of

Speed Shift 2. 

The following personnel variables are significant in their respective models and are 

positively correlated with the First Emplacement Truck Offload time:

• GCT Score of Cannoneer #3

• CFT Maneuver Under Fire Time of Cannoneer #1 and Cannoneer #3

• PFT: Run of the Recorder. 

The following personnel variable is significant in its respective models and is negatively 

correlated with the First Emplacement Truck Offload time:

• PFT: Crunches of Cannoneer #1. 

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, our final model includes only Critical Billet levels. Based on 

the model, although all other variables remain constant, a FM group is expected to 

perform this task approximately 1.03 minutes faster, on average, than would be done by 

the FF group. Again holding all other variables constant, a MF group is expected to 

perform this task approximately 0.74 minute faster, on average, than would be done by 

the FF group. Again holding all other variables constant, a MM group is expected to 

perform this task approximately 1.15 minutes faster, on average, than would be done by 

the FF group.
GCEITF EAR ANNEX H

FOR OFFICIAL USE ONLY 

H-75 AUGUST 2015

Appendix to Annex H 

0811 Supplemental Information

This appendix provides supplemental information for the 0811 portion of the GCEITF

experiment. It provides information regarding additional descriptive and basic inferential 

statistics not described in Annex H. 

Section 1: Additional Tasks Basic and Inferential Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

This section presents results for additional 0811 tasks. Annex H contains the 

descriptive statistics for the remainder of the 0811 tasks. The words “metric” and “task” 

are used interchangeably throughout this Appendix; They both refer to the experimental 

task. 

The tables in this appendix display results for the additional 0811 metrics, to include 

metrics and integration levels with their respective sample sizes, means, standard 

deviations, and percent difference between integration levels, and ANOVA results, 

including metrics and integration levels, and p-values suggesting statistical significance. 

For each task, an ANOVA and t-test were conducted to compare groups. If p-values 

are less than the a-priori determined significance level of 0.10, we conclude there is 

statistical evidence that the response for the LD and HD groups are different from that in 

the C group.

Section 2: Additional Task Results

Emplacement of Howitzer: 

Emplacing Howitzer; Dismount (seconds) - The C group had a mean of 31.73 

seconds with a SD of 6.99 seconds. The LD group had a mean of 40.64 seconds with a 

SD of 18.25 seconds. The HD group had a mean of 37.41 seconds with a SD of 15.57 

seconds. The LD group was 28.06% slower than the C group. The HD group was 

17.9% slower than the C group. The HD group was 7.94% faster than the LD group. 

Emplacing Howitzer; Trident Bar Drop (seconds) - The C group had a mean of 6.27 

seconds with a SD of 3.3 seconds. The LD group had a mean of 6.96 seconds with a 

SD of 4.93 seconds. The HD group had a mean of 6.71 seconds with a SD of 4.65 

seconds. The LD group was 10.85% slower than the C group. The HD group was 

6.96% slower than the C group. The HD group was 3.51% faster than the LD group. 

Emplacing Howitzer; Trident Bar Drop Excluding Influential Points (seconds)- The 

C group had a mean of 6.27 seconds with a SD of 3.3 seconds. The LD group had a 

mean of 6.48 seconds with a SD of 3.79 seconds. The HD group had a mean of 6.33 
GCEITF EAR ANNEX H

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AUGUST 2015 H-76

seconds with a SD of 3.81 seconds. The LD group was 3.22% slower than the C group. 

The HD group was 0.93% slower than the C group. The HD group was 2.22% faster 

than the LD group. 

Hasty Emplacement of Howitzer; Dismount (seconds) - The C group had a mean of 

34.59 seconds with a SD of 17.28 seconds. The LD group had a mean of 41.26 

seconds with a SD of 25.13 seconds. The HD group had a mean of 38.43 seconds with 

a SD of 22.79 seconds. The LD group was 19.3% slower than the C group. The HD 

group was 11.13% slower than the C group. The HD group was 6.85% faster than the 

LD group. 

Hasty Emplacement of Howitzer; Trident Bar Drop (seconds) - The C group had a 

mean of 8.33 seconds with a SD of 7.45 seconds. The LD group had a mean of 8.37 

seconds with a SD of 5.75 seconds. The HD group had a mean of 8.25 seconds with a 

SD of 8.52 seconds. The LD group was 0.43% slower than the C group. The HD group 

was 1.06% faster than the C group. The HD group was 1.48% faster than the LD 

group. 

Hasty Emplacement of Howitzer; Trident Bar Drop Excluding Influential Points 

(seconds) - The C group had a mean of 7.51 seconds with a SD of 5.28 seconds. The 

LD group had a mean of 8.37 seconds with a SD of 5.75 seconds. The HD group had a 

mean of 7.35 seconds with a SD of 5.5 seconds. The LD group was 11.41% slower 

than the C group. The HD group was 2.21% faster than the C group. The HD group 

was 12.23% faster than the LD group. 

Emplacing Howitzer; Trident Bar Drop (seconds) - The M group had a mean of 6.11 

seconds with a SD of 3.64 seconds. The F group had a mean of 9.43 seconds with a 

SD of 6.4 seconds. The F group was 54.54% slower than the M group. 

Emplacing Howitzer; Trident Bar Drop Excluding Influential Points (seconds) -

The M group had a mean of 5.91 seconds with a SD of 3.01 seconds. The F group had 

a mean of 8.68 seconds with a SD of 5.41 seconds. The F group was 46.86% slower 

than the M group. 

Hasty Emplacement of Howitzer; Trident Bar Drop (seconds) - The M group had a 

mean of 7.68 seconds with a SD of 6.08 seconds. The F group had a mean of 11.42 

seconds with a SD of 11.36 seconds. The F group was 48.75% slower than the M 

group. 

Hasty Emplacement of Howitzer; Trident Bar Drop Excluding Influential Points 

(seconds) - The M group had a mean of 7.38 seconds with a SD of 5.19 seconds. The 

F group had a mean of 9.52 seconds with a SD of 6.69 seconds. The F group was 

29.03% slower than the M group. 
GCEITF EAR ANNEX H

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Table H A - Emplacement Results (Descriptive Statistics by Integration Level)

Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference 

(LD-C)

% 

Difference 

(HD-C)

% 

Difference 

(HD-LD)

Emplacing Howitzer; 

Dismount (seconds)

C 41 31.73 6.99

LD 44 40.64 18.25 28.06% 17.9% -7.94%

HD 51 37.41 15.57

Emplacing Howitzer; 

Trident Bar Drop 

(seconds)

C 40 6.27 3.3

LD 45 6.96 4.93 10.85% 6.96% -3.51%

HD 52 6.71 4.65

Emplacing Howitzer; 

Trident Bar Drop 

Excluding Influential 

Points (seconds)

C 40 6.27 3.3

LD 44 6.48 3.79 3.22% 0.93% -2.22%

HD 51 6.33 3.81

Hasty Emplacement of 

Howitzer; Dismount 

(seconds) 

C 41 34.59 17.28

LD 42 41.26 25.13 19.3% 11.13% -6.85%

HD 53 38.43 22.79

Hasty Emplacement of 

Howitzer; Trident Bar 

Drop (seconds) 

C 42 8.33 7.45

LD 46 8.37 5.75 0.43% -1.06% -1.48%

HD 53 8.25 8.52

Hasty Emplacement of 

Howitzer; Trident Bar 

Drop Excluding 

Influential Points 

(seconds)

C 41 7.51 5.28

11.41% -2.21% -12.23%

LD 46 8.37 5.75

HD 52 7.35 5.5

Table H B - Emplacement Results (Descriptive Statistics by critical billet) 

Metric

Integra

tion 

Level

Sampl

e Size Mean SD 

% 

Differenc

e from 

control

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Emplacing Howitzer; 

Trident Bar Drop

(seconds)

M 114 6.11 3.64

F 23 9.43 6.40 54.54% 1.52 5.14 0.98 5.68

Emplacing Howitzer; 

Trident Bar Drop 

Excluding Influential 

Points

(seconds)

M 113 5.91 3.01

F 22 8.68 5.41 46.86% 1.20 4.34 0.74 4.80
GCEITF EAR ANNEX H

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Metric

Integra

tion 

Level

Sampl

e Size Mean SD 

% 

Differenc

e from 

control

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Hasty Emplacement of 

Howitzer; Trident Bar 

Drop

(seconds)

M 117 7.68 6.08

F 24 11.4

2 

11.3

6 48.75% 0.60 6.88 -0.33 7.81

Hasty Emplacement of 

Howitzer; Trident Bar 

Drop 

Excluding Influential 

Points

(seconds)

M 116 7.38 5.19

F 23 9.52 6.69 29.03% 0.21 4.08 -0.37 4.65

Indirect Fire Missions: 

3-Round Low-Angle HE; Total Fire Mission (minutes) - The C group had a mean of 

1.89 minutes with a SD of 0.38 minutes. The LD group had a mean of 2.01 minutes 

with a SD of 0.46 minutes. The HD group had a mean of 2.1 minutes with a SD of 0.47 

minutes. The LD group was 6.51% slower than the C group. The HD group was 

11.27% slower than the C group. The HD group was 4.47% slower than the LD group. 

3-Round Low-Angle HE; 1st Round Response (minutes) - The C group had a mean 

of 1.06 minutes with a SD of 0.28 minutes. The LD group had a mean of 1.12 minutes 

with a SD of 0.28 minutes. The HD group had a mean of 1.16 minutes with a SD of 

0.39 minutes. The LD group was 6.13% slower than the C group. The HD group was 

9.74% slower than the C group. The HD group was 3.4% slower than the LD group. 

3-Round Low-Angle HE; 1st Round Response Excluding Influential Points - The C 

group had a mean of 1.06 seconds with a SD of 0.28 seconds. The LD group had a 

mean of 1.12 seconds with a SD of 0.28 seconds. The HD group had a mean of 1.13 

seconds with a SD of 0.34 seconds. The LD group was 6.13% slower than the C group. 

The HD group was 7.02% slower than the C group. The HD group was 0.84% slower 

than the LD group. 

3-Round High-Angle WP; Total Fire Mission (minutes) - The C group had a mean of 

3.34 minutes with a SD of 0.48 minutes. The LD group had a mean of 3.5 minutes with 

a SD of 0.63 minutes. The HD group had a mean of 3.65 minutes with a SD of 0.84 

minutes. The LD group was 4.81% slower than the C group. The HD group was 9.25% 

slower than the C group. The HD group was 4.24% slower than the LD group. 
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3-Round High-Angle WP; 1st Round Response (minutes) - The C group had a mean 

of 1.68 minutes with a SD of 0.37 minutes. The LD group had a mean of 1.77 minutes 

with a SD of 0.33 minutes. The HD group had a mean of 1.63 minutes with a SD of 

0.33 minutes. The LD group was 5.45% slower than the C group. The HD group was 

2.68% faster than the C group. The HD group was 7.71% faster than the LD group. 

3-Round High-Angle WP; 1st Round Response Excluding Influential Points - The 

C group had a mean of 1.64 seconds with a SD of 0.27 seconds. The LD group had a 

mean of 1.75 seconds with a SD of 0.3 seconds. The HD group had a mean of 1.63 

seconds with a SD of 0.33 seconds. The LD group was 6.73% slower than the C group. 

The HD group was 0.17% faster than the C group. The HD group was 6.46% faster 

than the LD group. 

9-Round Low-Angle HE; Total Fire Mission (minutes) - The C group had a mean of 

4.15 minutes with a SD of 0.6 minutes. The LD group had a mean of 4.28 minutes with 

a SD of 1.01 minutes. The HD group had a mean of 4.31 minutes with a SD of 0.63 

minutes. The LD group was 3.12% slower than the C group. The HD group was 4.02% 

slower than the C group. The HD group was 0.88% slower than the LD group. 

9-Round Low-Angle HE; 1st Round Response (minutes) - The C group had a mean 

of 1.12 minutes with a SD of 0.27 minutes. The LD group had a mean of 1.05 minutes 

with a SD of 0.31 minutes. The HD group had a mean of 1.06 minutes with a SD of 

0.21 minutes. The LD group was 6.27% faster than the C group. The HD group was 

5.3% faster than the C group. The HD group was 1.03% slower than the LD group. 

9-Round Low-Angle HE; 1st Round Response Excluding Influential Points - The C 

group had a mean of 1.12 seconds with a SD of 0.27 seconds. The LD group had a 

mean of 1.02 seconds with a SD of 0.27 seconds. The HD group had a mean of 1.06 

seconds with a SD of 0.21 seconds. The LD group was 8.6% faster than the C group. 

The HD group was 5.3% faster than the C group. The HD group was 3.61% slower 

than the LD group. 

3-Round Low-Angle WP; Total Fire Mission (minutes) - The C group had a mean of 

1.48 minutes with a SD of 0.29 minutes. The LD group had a mean of 1.54 minutes 

with a SD of 0.34 minutes. The HD group had a mean of 1.58 minutes with a SD of 

0.32 minutes. The LD group was 4.17% slower than the C group. The HD group was 

7.24% slower than the C group. The HD group was 2.95% slower than the LD group. 

3-Round Low-Angle WP; 1st Round Response (seconds) - The C group had a mean 

of 43.29 seconds with a SD of 11.64 seconds. The LD group had a mean of 46.45 

seconds with a SD of 18.31 seconds. The HD group had a mean of 42.36 seconds with 

a SD of 13.86 seconds. The LD group was 7.29% slower than the C group. The HD 

group was 2.16% faster than the C group. The HD group was 8.81% faster than the LD 

group. 
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3-Round Low-Angle WP; 1st Round Response Excluding Influential Points - The 

C group had a mean of 43.29 seconds with a SD of 11.64 seconds. The LD group had 

a mean of 44.73 seconds with a SD of 15.15 seconds. The HD group had a mean of 

41.32 seconds with a SD of 12.12 seconds. The LD group was 3.33% slower than the 

C group. The HD group was 4.55% faster than the C group. The HD group was 7.63% 

faster than the LD group. 

3-Round Low-Angle HE from FP2; Total Fire Mission (minutes) - The C group had a 

mean of 1.67 minutes with a SD of 0.32 minutes. The LD group had a mean of 1.69 

minutes with a SD of 0.3 minutes. The HD group had a mean of 1.7 minutes with a SD 

of 0.33 minutes. The LD group was 1.6% slower than the C group. The HD group was 

2.23% slower than the C group. The HD group was 0.62% slower than the LD group. 

3-Round Low-Angle HE from FP2; 1st Round Response (seconds) - The C group 

had a mean of 58.75 seconds with a SD of 15.89 seconds. The LD group had a mean 

of 57.36 seconds with a SD of 12.65 seconds. The HD group had a mean of 57.32 

seconds with a SD of 13.68 seconds. The LD group was 2.36% faster than the C 

group. The HD group was 2.43% faster than the C group. The HD group was 0.07% 

faster than the LD group. 

3-Round Low-Angle HE from FP2; 1st Round Response Excluding Influential 

Points - The C group had a mean of 57.03 seconds with a SD of 12.78 seconds. The 

LD group had a mean of 57.36 seconds with a SD of 12.65 seconds. The HD group 

had a mean of 57.32 seconds with a SD of 13.68 seconds. The LD group was 0.58% 

slower than the C group. The HD group was 0.51% slower than the C group. The HD 

group was 0.07% faster than the LD group. 

3-Round High-Angle WP; Total Fire Mission (minutes) - The MM group had a mean 

of 3.42 minutes with a SD of 0.59 minutes. The MF group had a mean of 3.86 minutes 

with a SD of 0.98 minutes. The FM group had a mean of 3.6 minutes with a SD of 0.76 

minutes. The FF group had a mean of 3.59 minutes with a SD of 0.61 minutes. The 

MF group was 12.64% slower than the MM group. The FM group was 5.26% slower 

than the MM group. The FF group was 4.91% slower than the MM group. The MF 

group was 7.01% slower than the FM group. The FF group was 6.86% faster than the 

MF group. The FF group was 0.34% faster than the FM group. 

3-Round High-Angle WP; 1st Round Response (minutes) - The MM group had a 

mean of 1.68 minutes with a SD of 0.34 minutes. The MF group had a mean of 1.79 

minutes with a SD of 0.45 minutes. The FM group had a mean of 1.66 minutes with a 

SD of 0.27 minutes. The FF group had a mean of 1.63 minutes with a SD of 0.13 

minutes. The MF group was 6.62% slower than the MM group. The FM group was 

1.01% faster than the MM group. The FF group was 2.8% faster than the MM group. 

The MF group was 7.71% slower than the FM group. The FF group was 8.84% faster 

than the MF group. The FF group was 1.81% faster than the FM group. 
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3-Round High-Angle WP; 1st Round Response Excluding Influential Points - The 

MM group had a mean of 1.66 seconds with a SD of 0.31 seconds. The MF group had 

a mean of 1.73 seconds with a SD of 0.45 seconds. The FM group had a mean of 1.66 

seconds with a SD of 0.27 seconds. The FF group had a mean of 1.63 seconds with a 

SD of 0.13 seconds. The MF group was 4.26% slower than the MM group. The FM 

group was 0.06% slower than the MM group. The FF group was 1.75% faster than the 

MM group. The MF group was 4.2% slower than the FM group. The FF group was 

5.77% faster than the MF group. The FF group was 1.81% faster than the FM group. 

Table H C - Indirect Fire Mission Results (Descriptive Statistics by integration level)

Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference 

(LD-C)

% 

Difference 

(HD-C)

% 

Difference 

(HD-LD)

3-Round Low-Angle HE; 

Total Fire Mission 

(minutes) 

C 37 1.89 0.38

LD 38 2.01 0.46 6.51% 11.27% 4.47%

HD 44 2.1 0.47

3-Round Low-Angle HE; 

1st Round Response 

(minutes) 

C 37 1.06 0.28

LD 38 1.12 0.28 6.13% 9.74% 3.4%

HD 46 1.16 0.39

3-Round Low-Angle HE; 

1st Round Response 

Excluding Influential 

Points (minutes)

C 37 1.06 0.28

6.13% 7.02% 0.84% LD 38 1.12 0.28

HD 45 1.13 0.34

3-Round High-Angle 

WP; Total Fire Mission 

(minutes) 

C 35 3.34 0.48

LD 39 3.5 0.63 4.81% 9.25% 4.24%

HD 49 3.65 0.84

3-Round High-Angle 

WP; 1st Round 

Response (minutes) 

C 35 1.68 0.37

LD 39 1.77 0.33 5.45% -2.68% -7.71%

HD 48 1.63 0.33

3-Round High-Angle 

WP; 1st Round 

Response Excluding 

Influential Points 

(minutes)

C 34 1.64 0.27

6.73% -0.17% -6.46%

LD 38 1.75 0.3

HD 48 1.63 0.33

9-Round Low-Angle HE; 

Total Fire Mission 

(minutes) 

C 31 4.15 0.6

LD 34 4.28 1.01 3.12% 4.02% 0.88%

HD 39 4.31 0.63

9-Round Low-Angle HE; 

1st Round Response 

(minutes) 

C 33 1.12 0.27

LD 35 1.05 0.31 -6.27% -5.3% 1.03%

HD 42 1.06 0.21

9-Round Low-Angle HE; 

1st Round Response 

C 33 1.12 0.27 -8.60% -5.3% 3.61%

LD 34 1.02 0.27
GCEITF EAR ANNEX H

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Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference 

(LD-C)

% 

Difference 

(HD-C)

% 

Difference 

(HD-LD)

Excluding Influential 

Points (minutes) HD 42 1.06 0.21

3-Round Low-Angle 

WP; Total Fire Mission 

(minutes) 

C 38 1.48 0.29

LD 37 1.54 0.34 4.17% 7.24% 2.95%

HD 44 1.58 0.32

3-Round Low-Angle 

WP; 1st Round 

Response (seconds) 

C 38 43.29 11.64

LD 38 46.45 18.31 7.29% -2.16% -8.81%

HD 45 42.36 13.86

3-Round Low-Angle 

WP; 1st Round 

Response Excluding 

Influential Points 

(seconds)

C 38 43.29 11.64

3.33% -4.55% -7.63%

LD 37 44.73 15.15

HD 44 41.32 12.12

3-Round Low-Angle HE 

from FP2; Total Fire 

Mission (minutes) 

C 31 1.67 0.32

LD 33 1.69 0.3 1.60% 2.23% 0.62%

HD 38 1.7 0.33

3-Round Low-Angle HE 

from FP2; 1st Round 

Response (seconds) 

C 32 58.75 15.89

LD 33 57.36 12.65 -2.36% -2.43% -0.07%

HD 40 57.32 13.68

3-Round Low-Angle HE 

from FP2; 1st Round 

Response Excluding 

Influential Points 

(seconds)

C 31 57.03 12.78

0.58% 0.51% -0.07%

LD 33 57.36 12.65

HD 40 57.32 13.68

Table H D - Indirect Fire Mission Results (Descriptive Statistics by critical billet)

Metric

Integr

ation 

Level

Samp

le

Size

Mea

n 

SD

% 

Differen

ce from 

control

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

3-Round Low-Angle HE; 

Total Fire Mission

(minutes)

M 101 1.97 0.40

F 18 2.19 0.60 11.38% 0.03 0.42 -0.03 0.48

3-Round Low-Angle HE; 

1st Round Response

(minutes)

M 103 1.10 0.33

F 18 1.20 0.30 9.34% 0.00 0.21 -0.03 0.24

3-Round Low-Angle HE; 

1st Round Response

Excluding Influential Point

(minutes)

M 102 1.09 0.30

F 18 1.20 0.30 10.68% 0.01 0.22 -0.02 0.25
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Metric

Integr

ation 

Level

Samp

le

Size

Mea

n 

SD

% 

Differen

ce from 

control

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

9-Round Low-Angle HE; 

Total Fire Mission

(minutes)

M 85 4.18 0.72

F 19 4.55 0.90 8.85% 0.08 0.66 -0.01 0.75

9-Round Low-Angle HE; 

1st Round Response

(minutes)

M 90 1.07 0.24

F 20 1.10 0.34 3.47% -0.07 0.14 -0.10 0.17

9-Round Low-Angle HE; 

1st Round Response

Excluding Influential Points

(minutes)

M 90 1.07 0.24

F 19 1.06 0.28 -0.64% -0.10 0.08 -0.13 0.11

3-Round Low-Angle WP; 

Total Fire Mission

(minutes)

M 100 1.51 0.33

F 19 1.65 0.23 9.15% 0.06 0.22 0.03 0.24

3-Round Low-Angle WP; 

1st Round Response

(seconds)

M 102 43.61 15.34

F 19 45.68 11.59 4.76% -1.93 6.09 -3.12 7.27

3-Round Low-Angle WP; 

1st Round Response

Excluding Influential Points

(seconds)

M 100 42.50 13.20

F 19 45.68 11.59 7.49 -0.71 7.08 -1.87 8.24

3-Round Low-Angle HE 

from FP2; Total Fire 

Mission

(minutes)

M 84 1.66 0.30

F 18 1.84 0.35 10.72% 0.06 0.29 0.03 0.33

3-Round Low-Angle HE 

from FP2; 1st Round 

Response

(seconds)

M 86 56.62 13.86

F 19 63.00 13.63 11.28% 1.83 10.94 0.48 12.29

3-Round Low-Angle HE 

from FP2; 1st Round 

Response 

Excluding Influential Points

(seconds)

M 85 55.96 12.54

F 19 60.00 13.63 12.57% 2.55 11.52 1.21 12.86
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Table H E - Indirect Fire Mission Results (Descriptive Statistics by critical billet) 

Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference 

(MF-MM)

% 

Difference 

(FM-MM

% 

Difference 

(FF-MM)

% 

Difference 

(MF-FM)

% 

Difference 

(FF-MF)

% 

Difference 

(FF-FM)

3-Round High-Angle 

WP; Total Fire Mission 

(minutes) 

MM 81 3.42 0.59

12.64% 5.26% 4.91% 7.01% -6.86% -0.34%

MF 16 3.86 0.98

FM 22 3.6 0.76

FF 4 3.59 0.61

3-Round High-Angle 

WP; 1st Round 

Response (minutes) 

MM 81 1.68 0.34

6.62% -1.01% -2.8% 7.71% -8.84% -1.81%

MF 16 1.79 0.45

FM 21 1.66 0.27

FF 4 1.63 0.13

3-Round High-Angle 

WP; 1st Round 

Response Excluding 

Influential Points 

(minutes)

MM 80 1.66 0.31

4.26% 0.06% -1.75% 4.2% -5.77% -1.81%

MF 15 1.73 0.45

FM 21 1.66 0.27

FF 4 1.63 0.13
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Gun Nets: 

Gun Nets (minutes) - The C group had a mean of 13.03 with a SD of 2.79. The LD 

group had a mean of 13.78 with a SD of 3.2. The HD group had a mean of 13.75 with a 

SD of 2.92. The LD group was 5.7% slower than the C group. The HD group was 

5.54% slower than the C group. The HD group was 0.15% faster than the LD group. 

Strike Nets (minutes) - The C group had a mean of 9.27 with a SD of 2.14. The LD 

group had a mean of 9.12 with a SD of 1.84. The HD group had a mean of 9.1 with a 

SD of 2.03. The LD group was 1.64% faster than the C group. The HD group was 

1.82% faster than the C group. The HD group was 0.18% faster than the LD group. 

Table H F - Gun Nets Results (Descriptive Statistics by integration level)

Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference 

(LD-C)

% 

Difference 

(HD-C)

% 

Difference 

(HD-LD)

Gun Nets (minutes) 

C 43 13.03 2.79

LD 44 13.78 3.2 5.70% 5.54% -0.15%

HD 52 13.75 2.92

Strike Nets (minutes) 

C 42 9.27 2.14

LD 42 9.12 1.84 -1.64% -1.82% -0.18%

HD 52 9.1 2.03

Displacement: 

Displacement of Howitzer; Total Displacement (minutes) - The C group had a mean 

of 5.11 with a SD of 0.82. The LD group had a mean of 5.08 with a SD of 1.83. The HD 

group had a mean of 5.32 with a SD of 1.45. The LD group was 0.71% faster than the 

C group. The HD group was 3.94% slower than the C group. The HD group was 

4.68% slower than the LD group. 

Displacement of Howitzer; Trident Bar (seconds) - The C group had a mean of 19

with a SD of 8.5. The LD group had a mean of 23.71 with a SD of 15.32. The HD 

group had a mean of 19.67 with a SD of 8.42. The LD group was 24.81% slower than 

the C group. The HD group was 3.51% slower than the C group. The HD group was 

17.07% faster than the LD group. 

Displacement of Howitzer; Trident Bar Excluding Influential Points - The C group 

had a mean of 19 with a SD of 8.5. The LD group had a mean of 22.27 with a SD of 

12.27. The HD group had a mean of 19.67 with a SD of 8.42. The LD group was 

17.2% slower than the C group. The HD group was 3.51% slower than the C group. 

The HD group was 11.68% faster than the LD group. 
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Displacement of Howitzer; Trail Arms (seconds) - The C group had a mean of 14.02

with a SD of 5.32. The LD group had a mean of 14.72 with a SD of 5.95. The HD 

group had a mean of 14.4 with a SD of 5.57. The LD group was 4.97% slower than the 

C group. The HD group was 2.65% slower than the C group. The HD group was 

2.21% faster than the LD group. 

Final Displacement of Howitzer; Trident Bar (seconds) - The C group had a mean of 

18.95 with a SD of 8.26. The LD group had a mean of 17.19 with a SD of 8.43. The HD 

group had a mean of 19.94 with a SD of 10.39. The LD group was 9.31% faster than 

the C group. The HD group was 5.22% slower than the C group. The HD group was 

16.02% slower than the LD group. 

Final Displacement of Howitzer; Trident Bar Excluding Influential Points - The C 

group had a mean of 18.95 with a SD of 8.26. The LD group had a mean of 17.19 with

a SD of 8.43. The HD group had a mean of 19.31 with a SD of 9.47. The LD group 

was 9.31% faster than the C group. The HD group was 1.88% slower than the C group. 

The HD group was 12.34% slower than the LD group. 

Final Displacement of Howitzer; Trail Arms (seconds) - The C group had a mean of 

16.41 with a SD of 8.42. The LD group had a mean of 17.78 with a SD of 6.71. The HD 

group had a mean of 17.16 with a SD of 9.57. The LD group was 8.35% slower than 

the C group. The HD group was 4.55% slower than the C group. The HD group was 

3.51% faster than the LD group. 

Final Displacement of Howitzer; Trail Arms Excluding Influential Points - The C 

group had a mean of 15.53 with a SD of 6.45. The LD group had a mean of 17.78 with

a SD of 6.71. The HD group had a mean of 16.3 with a SD of 7.43. The LD group was 

14.52% slower than the C group. The HD group was 4.98% slower than the C group. 

The HD group was 8.33% faster than the LD group. 

Final Displacement of Howitzer; Mount Prime Mover (minutes) - The C group had a 

mean of 1.05 with a SD of 0.63. The LD group had a mean of 1.08 with a SD of 0.59. 

The HD group had a mean of 1.02 with a SD of 0.52. The LD group was 3.27% slower 

than the C group. The HD group was 6.9% slower than the C group. The HD group 

was 3.52% slower than the LD group. 

Displacement of Howitzer; Trident Bar (seconds) - The M group had a mean of 

19.81 seconds with a SD of 9.52 seconds. The F group had a mean of 22.29 seconds 

with a SD of 10.93 seconds. The F group was 9.42% slower than the M group.

Displacement of Howitzer; Trident Bar Excluding Influential Points (seconds) - 

The M group had a mean of 19.81 seconds with a SD of 9.52 seconds. The F group 

had a mean of 22.29 seconds with a SD of 10.93 seconds. The F group was 12.51% 

slower than the M group. 
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Final Displacement of Howitzer; Trident Bar (seconds) - The M group had a mean of 

18.04 seconds with a SD of 8.44 seconds. The F group had a mean of 22.8 seconds 

with a SD of 12.01 seconds. The F group was 26.42% slower than the M group. 

Final Displacement of Howitzer; Trident Bar Excluding Influential Points 

(seconds) - The M group had a mean of 17.74 seconds with a SD of 7.87 seconds. 

The F group had a mean of 22.8 seconds with a SD of 12.01 seconds. The F group 

was 28.52% slower than the M group. 

Displacement of Howitzer; Trail Arms (seconds) - The MM group had a mean of 

14.75 seconds with a SD of 5.53 seconds. The MF group had a mean of 12.62 seconds 

with a SD of 4.57 seconds. The FM group had a mean of 13.67 seconds with a SD of 

5.11 seconds. The FF group had a mean of 23 seconds with a SD of 15.56 seconds. 

The MF group was 14.43% faster than the MM group. The FM group was 7.33% faster 

than the MM group. The FF group was 55.96% slower than the MM group. The MF 

group was 7.67% faster than the FM group. The FF group was 82.26% slower than the 

MF group. The FF group was 68.29% slower than the FM group. 

Final Displacement of Howitzer; Trail Arms (seconds) - The MM group had a mean 

of 17.33 seconds with a SD of 7.83 seconds. The MF group had a mean of 13.65 

seconds with a SD of 4.65 seconds. The FM group had a mean of 21.62 seconds with 

a SD of 12.94 seconds. The FF group had a mean of 12 seconds with a SD of 2.83 

seconds. The MF group was 21.24% faster than the MM group. The FM group was 

24.76% slower than the MM group. The FF group was 30.77% faster than the MM 

group. The MF group was 36.87% faster than the FM group. The FF group was 12.1% 

faster than the MF group. The FF group was 44.51% faster than the FM group. 

Final Displacement of Howitzer; Trail Arms Excluding Influential Points - The MM 

group had a mean of 16.97 seconds with a SD of 7.06 seconds. The MF group had a 

mean of 13.65 seconds with a SD of 4.65 seconds. The FM group had a mean of 19.07 

seconds with a SD of 8.2 seconds. The FF group had a mean of 12 seconds with a SD 

of 2.83 seconds. The MF group was 19.53% faster than the MM group. The FM group 

was 12.38% slower than the MM group. The FF group was 29.27% faster than the MM 

group. The MF group was 28.4% faster than the FM group. The FF group was 12.1% 

faster than the MF group. The FF group was 37.06% faster than the FM group. 

Table H G - Displacement Results by Integration Level

Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference 

(LD-C)

% 

Difference 

(HD-C)

% 

Difference 

(HD-LD)

Displacement of 

Howitzer; Total 

Displacement (minutes) 

C 39 5.11 0.82

LD 40 5.08 1.83 -0.71% 3.94% 4.68%

HD 46 5.32 1.45
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Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference 

(LD-C)

% 

Difference 

(HD-C)

% 

Difference 

(HD-LD)

Displacement of 

Howitzer; Trident Bar 

(seconds) 

C 41 19 8.5

LD 42 23.71 15.32 24.81% 3.51% -17.07%

HD 54 19.67 8.42

Displacement of 

Howitzer; Trident Bar 

Excluding Influential 

Points (seconds)

C 41 19 8.5

17.20% 3.51% -11.68% LD 41 22.27 12.27

HD 54 19.67 8.42

Displacement of 

Howitzer; Trail Arms 

(seconds) 

C 41 14.02 5.32

LD 43 14.72 5.95 4.97% 2.65% -2.21%

HD 48 14.4 5.57

Final Displacement of 

Howitzer; Trident Bar 

(seconds) 

C 40 18.95 8.26

LD 43 17.19 8.43 -9.31% 5.22% 16.02%

HD 50 19.94 10.39

Final Displacement of 

Howitzer; Trident Bar 

Excluding Influential 

Points (seconds)

C 40 18.95 8.26

LD 43 17.19 8.43 -9.31% 1.88% 12.34%

HD 49 19.31 9.47

Final Displacement of 

Howitzer; Trail Arms 

(seconds) 

C 39 16.41 8.42

LD 41 17.78 6.71 8.35% 4.55% -3.51%

HD 51 17.16 9.57

Final Displacement of 

Howitzer; Trail Arms 

Excluding Influential 

Points (seconds)

C 38 15.53 6.45

14.52% 4.98% -8.33% LD 41 17.78 6.71

HD 50 16.3 7.43

Final Displacement of 

Howitzer; Mount Prime 

Mover (minutes) 

C 31 1.05 0.63

LD 33 1.08 0.59 3.27% 6.9% 3.52%

HD 40 1.02 0.52

Table H H - Displacement Results (Descriptive Statistics by critical billet) 

Metric

Integra

tion 

Level

Sampl

e Size Mean SD

% 

Difference 

from 

control

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Displacement of Howitzer; 

Trident Bar

(seconds)

M 113 20.37 11.18

F 24 22.29 10.93 9.42% -1.30 5.14 -2.25 6.09

Displacement of Howitzer; 

Trident Bar 

Excluding Influential Points

(seconds)

M 112 19.81 9.52

F 24 22.29 10.93 12.51% -0.67 5.63 -1.60 6.56
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Metric

Integra

tion 

Level

Sampl

e Size Mean SD

% 

Difference 

from 

control

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Final Displacement of 

Howitzer; Trident Bar

(seconds)

M 113 18.04 8.44

F 20 22.80 12.01 26.42% 1.07 8.46 -0.04 9.57

Final Displacement of 

Howitzer; Trident Bar

Excluding Influential Points

(seconds)

M 112 17.74 7.87

F 20 22.80 12.01 28.52% 1.38 8.74 0.27 9.84
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Table H I - Displacement Results (Descriptive Statistics by critical billet) 

Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference 

(MF-MM)

% 

Difference 

(FM-MM

% 

Difference 

(FF-MM)

% 

Difference 

(MF-FM)

% 

Difference 

(FF-MF)

% 

Difference 

(FF-FM)

Displacement of Howitzer; 

Trail Arms (seconds) 

MM 91 14.75 5.53

-14.43% -7.33% 55.96% -7.67% 82.26% 68.29%

MF 21 12.62 4.57

FM 18 13.67 5.11

FF 2 23 15.56

Final Displacement of 

Howitzer; Trail Arms 

(seconds) 

MM 90 17.33 7.83

-21.24% 24.76% -30.77% -36.87% -12.1% -44.51%

MF 23 13.65 4.65

FM 16 21.62 12.94

FF 2 12 2.83

Final Displacement of 

Howitzer; Trail Arms 

Excluding Influential Points 

(seconds)

MM 89 16.97 7.06

-19.53% 12.38% -29.27% -28.4% -12.1% -37.06%

MF 23 13.65 4.65

FM 15 19.07 8.2

FF 2 12 2.83
FOR OFFICIAL USE ONLY 

Annex I. 

M1A1 TANK CREWMAN (MOS 1812) 

This annex details the M1A1 Tank Crewman (MOS 1812) portion of the Ground Combat 

Element Integrated Task Force (GCEITF) experiment executed from 3 March to 

16 April 2015 at Range 500, aboard the Marine Corps Air-Ground Combat Center

(MCAGCC), Twentynine Palms, CA. The sections below outline the Tank Crewman 

Scheme of Maneuver, Limitations, Deviations, Dataset Description, Descriptive and 

Basic Inferential Statistics, and Modeling Results. 

I.1 Scheme of Maneuver

I.1.1 Experimental Cycle Overview

The Tank Crewmen (MOS 1812) were assessed in a field environment aboard 

MCAGCC, Twentynine Palms, CA. The tank experiment consisted of 3-day cycles 

divided into 2 pilot trial cycles and 12 record trial cycles, conducted over the course of a 

45-day assessment. The experimental unit received 1 rest day after completing 4 

cycles, resulting in an operational tempo of 12 days on and 1 day off. The day off was 

used as a range maintenance day to allow contractor support to conduct range and 

targetry upkeep. Sixty-four record trial cycles were planned, but 72 trials were 

conducted. All trials took place at the Range 500 training area aboard the MCAGCC, 

Twentynine Palms, CA. 

Volunteers filled the Driver, Loader, and Gunner billets on each tank crew. The Tank 

Commander billets were filled by experienced noncommissioned officers, staff 

noncommissioned officers, and a lieutenant assigned through the normal orders 

process. The three volunteer billets were further divided into rotating and nonrotating 

billets. Due to safety considerations, the Gunner billets were designated as nonrotating 

billets and filled by the male volunteers with the greatest level of MOS experience. The 

Tank Commanders and Gunners who completed Tank Table VI gunnery qualifications 

together during the workup phase remained paired throughout the experiment. The 

remaining volunteers were randomly assigned to a different Driver or Loader billet each 

trial cycle.

I.1.2 Experimental Details

The Tank experiment trials’ 3-day cycles consisted of a maintenance day, a non-live-fire 

day, and a live-fire day. Day 1 of the cycle (Maintenance) consisted of a standard 

series of preventive maintenance procedures, along with vehicle repairs conducted as 

required. Although not evaluated, these events ensured the unit’s vehicles and 

equipment remained fully operational. Day 2 (Non-Live-Fire) consisted of seven 
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individual and crew-level non-live-fire tasks. The day began with a crew-level 

maintenance task, followed by three crew-station-specific individual tasks, a crew 

evacuation, a CASEVAC, and a disabled-vehicle recovery task. Day 3 (Live Fire) 

consisted of six crew-level live-fire tasks conducted in two phases. Phase 1 consisted 

of uploading and transferring ammunition at the field ammunition-supply point. Phase 2 

consisted of four live-fire engagements conducted on the Range 500 firing line. The 

live-fire evolution progressed from defense to offense, and included main gun and 

machinegun engagements. At the conclusion of the Day 3, the unit reorganized into 

new tank crews in preparation for the next cycle. Initial Fatigue surveys were given to 

each volunteer at the beginning of each experimental day, followed by a final Fatigue 

survey at the completion of that particular day’s tasks. Workload surveys were 

administered immediately following certain specified tasks. Finally, volunteers 

completed cohesion surveys at the end of each trial cycle. For survey instruments, see 

the GCEITF EAP Annexes D and M.

Objective and subjective measures of performance were captured for each task. The 

objective measures of performance included the time required to perform the task and 

the heart rate of volunteers while performing the task (reported separately). Subjective 

measures of performance and ability included Fatigue, Workload, and Cohesion 

surveys conducted at various times during each trial cycle. 

I.1.3 Additional Context

The assessment was conducted in a simulated tactical environment. During each cycle, 

the unit operated from a tactical assembly area; bivouacked on their vehicles at night, 

maintaining a 15% security posture; and subsisted on field rations. All trials were 

conducted wearing body armor and other personal protective equipment (PPE) 

appropriate for tank crewmen. These conditions were established to introduce the 

minimal level of cumulative fatigue that Marines would realistically experience in an 

operating environment with an enemy threat. It is important to note that sustained 

combat operations in an expeditionary environment would likely involve much longer 

workdays, less time for rest and recovery, and a corresponding increase in cumulative 

fatigue. 

On average, the volunteers spent between 4 and 6 hours each day performing the 

experiment tasks. In addition, the volunteers performed various required maintenance 

procedures on their vehicles, including approximately 2 hours of preventive 

maintenance, checks, and services performed on each tank after the day’s trials were 

complete. Equipment failures often required additional work to troubleshoot and repair 

disabled vehicles. Performing daily preventive maintenance and repair work maintained

the tanks at the high level of operational readiness required for the experiment. 

Performing several hours of preventive maintenance or repairs each day is operationally 

realistic and an indispensable part of every tank crewman’s job in the operating forces. 
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Fatigue surveys were designed to capture the volunteers’ cumulative fatigue level at the 

beginning and end of each day’s trials. The data collected provide additional insight into 

apparent aberrations in the performance level of a given volunteer on a specific day. It 

allows for outside fatigue-related factors (minor illness, lack of sleep the night before, 

etc.) to be accounted for in the analysis of the performance data. Workload surveys 

collected the volunteer’s perceived average and maximal level of exertion during the 

performance-specified tasks. Cohesion surveys provided a method of collecting 

subjective data relating to each tank crew’s ability to work as a team and its members’ 

overall perspective on the cohesiveness of the crew.

I.1.4 Experimental Tasks

All of the tasks selected for this experiment were based on NAVMC 3500.121 Tank 

Training and Readiness (T&R) Manual; FM 3-20.21: Heavy Brigade Combat Team 

Gunnery Manual; MCWP 3-12: Marine Corps Tank Employment; M1A1 Technical 

Manual 08953A-10/1-3; and guidance from MOS senior leadership at Plans, Policies, 

and Operations (PP&O), Training and Education Command (TECOM), and Fleet Marine 

Force units. In addition, the tasks selected for the experiment were deemed physically 

demanding, repeatable, and frequently performed under time-constrained conditions in 

both training and combat environments. 

A description of each task is given below. The tasks are listed in the order in which they 

were performed during each trial cycle. 

I.1.4.1 Perform Maintenance Actions

Tank crewmen in the operating forces typically spend a significant percentage of 

available man-hours performing routine maintenance. The work is often very physically 

demanding, because the parts, tools, and equipment organic to a tank unit are large 

and heavy. A proficient and effective tank crewman will be capable of performing 

multiple hours of preventative maintenance or repairs each day. This is operationally 

realistic and an indispensable part of every tank crewman’s job. A specific experiment 

task was developed to evaluate a tank crew’s ability to perform common maintenance 

procedures. The task involved separating the track, removing and replacing a track 

section, and reinstalling the track. This task was chosen because it is physically 

demanding, repeatable, and commonly performed under time-constrained conditions in 

a combat environment. An initial Fatigue survey was given to each volunteer prior to 

this task. A Workload survey was administered immediately following this task to 

measure the average and maximum workload experienced by each volunteer. 

I.1.4.2 Reload Main Gun

In this task, the loader removed a round weighing 52.8 lb from a stowage compartment 

approximately 3 to 5 feet off the ground, flipped the round over, and loaded it into the 
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breach while balancing inside a moving vehicle. All main gun engagements in the 

assessment used the 52.8-lb M831A, a training replica of the M830 High-Explosive AntiTank (HEAT) multipurpose round. Although this task is the loader’s responsibility, all 

crewmembers must be able to perform the task. Doctrinal standards prescribed by 

FM 3-20.21 require each crewmember to demonstrate the ability to reload the main gun 

in 7 seconds or less. The rate of fire is limited by the speed at which the loader can 

manually reload the main gun, so reloading speed has a significant impact on the crew’s 

effectiveness and survivability in combat operations. A Workload survey was 

administered immediately following this task to measure the average and maximum 

workload experienced by the volunteer.

I.1.4.3 Manually Manipulate Turret and Main Gun

In this task, each volunteer manually traversed the turret 180 degrees to the left, 

lowered and raised the main gun to its minimum and maximum elevation, then 

traversed the turret 180 degrees back to the right. The turret and main gun of the M1A1 

operate by electric and hydraulic systems. As a backup, the turret and main gun can be 

operated using crank handles located in the gunner’s station. The manual manipulation 

of the turret and main gun is a real-world action performed in the event of a hydraulic or 

electrical malfunction. The speed at which the gunner can manually scan for targets 

and place the main gun on target has a direct impact on combat effectiveness and 

survivability. A Workload survey was administered immediately following this task to

capture the average and maximum workload experienced by the volunteer.

I.1.4.4 Prepare Commander’s Weapons Station

In this task, volunteers lifted the M48 .50-caliber machinegun from the ground to the top 

of the tank, mounted the weapon in the cradle, set the headspace and timing, and 

performed a function check. The tank commander’s station is the most physically 

challenging station to set up. All crewmembers must be capable of performing this 

procedure to be assigned as a tank commander. FM 3-20.21 requires each 

crewmember to demonstrate proficiency in assembling, setting headspace and timing, 

and performing a function check on the M48. The ability to assemble and install the 

weapon is necessary to prepare the tank for operations and to troubleshoot weapons 

malfunctions during operations. A Workload survey was administered immediately 

following this task to capture the average and maximum workload experienced by the 

volunteer. 

I.1.4.5 Conduct Crew Evacuation

The crew evacuation task was performed with all crewmembers starting at crew stations 

with safety guards installed and hatches closed and locked. Upon receiving the 

command to evacuate, the crew exited their stations and moved to a rally point 
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50 meters behind the vehicle. Opening the crew hatches required lifting a 40- to 65-lb 

hinged door in an upward motion, away from the crewman. A combat-loaded M1A1 

contains several hundred gallons of flammable fuel and hydraulic fluid, and several 

hundred pounds of HE ordinance. In the event of a fire or other emergency, the 

survivability of the crew depends on a quick evacuation of the tank. All crewmen (Tank 

Commander, Gunner, Driver, and Loader) exited the vehicle safely and moved as a 

crew to the rally point 25 meters away. Marines wore fighting loads and carried 

individual weapons, as would be expected when evacuating a vehicle in a tactical 

environment. Although the crew evacuation subtask is not as physically demanding as 

extracting a casualty from the tank, a quick vehicle evacuation is vital in the event of a 

vehicle fire or other life-threatening issue. A Workload survey was administered 

immediately following this task to capture the average and maximum workload 

experienced by the volunteer. 

I.1.4.6 Evacuate Wounded Crewmember 

This task measured a tank crew’s response time and its ability to evacuate an 

incapacitated crewman to a rally point 50 meters away. To set up the task, a 205-lb

casualty dummy (wearing full PPE) was staged in the gunner’s station. The gunner’s 

station within a tank is the most difficult location from which to evacuate a Marine 

because of its inaccessibility and limited workspace. To perform the CASEVAC, the 

crew lifted the dummy out the loader’s hatch on the roof of the turret, and carried the

casualty to a rally point 50 meters behind the vehicle. In the event that a crewmember 

is injured or otherwise incapacitated, the remaining three crewmembers are responsible 

for evacuating the wounded Marine. Performing this task quickly enables the casualty 

to receive medical attention as soon as possible. A Workload survey was administered 

immediately following this task to capture the average and maximum workload 

experienced by the volunteer. 

I.1.4.7 Conduct Vehicle Recovery 

To perform the recovery task, crewmembers from each tank dismounted from the 

vehicles, removed the tow bars from the stowage position on the operational tank, 

mounted them on the front of the disabled tank, and then held the tow bars in place 

(approximately 3 feet off the ground) while the operational tank maneuvered into 

position. In a combat environment, a quick recovery of a disabled vehicle denies the 

enemy the opportunity to maneuver or employ fires against a stationary tank. In the 

event that a tank becomes disabled, tank sections are equipped and trained to perform 

self-recovery. Recovering a disabled tank is a physically demanding task because the 

tow bars weighs 300 lb and must be moved by hand. A Workload survey was 

administered immediately following this task to capture the average and maximum 

workload experienced by the volunteer. 
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I.1.4.8 Conduct Ammunition Resupply 

This task was designed to evaluate the tank crew’s performance uploading a full 

complement of ammunition onto the vehicle from a field ammunition-supply point. A 

crewman removed the main gun rounds from the stowage containers, transported them 

approximately 20 meters to the tank, and lifted the rounds up to the crewmen standing 

on the tank. After each round was delivered to the tank the remaining crewmen took

the round and stowed it inside the turret. A Workload survey was administered 

immediately following this task to capture the average and maximum workload 

experienced by the volunteer.

I.1.4.9 Transfer Ammunition 

The M1A1 has two useable stowage compartments for main gun ammunition: the 

ready ammunition stowage compartment from which the rounds are withdrawn to be 

fired, and the semi-ready ammunition stowage compartment, which is used to carry 

additional rounds but is less accessible. When the ready ammunition stowage 

compartment is low on ammunition, the crew transfers ammunition into it from the semiready ammunition stowage compartment. Performance of this task was evaluated by 

measuring the total time required for the crew to transfer 16 main gun rounds between 

stowage compartments. The measure of performance for this task is time. In a combat 

situation, the speed with which the crew can perform this task determines how quickly 

the crew can resume engaging targets. A Workload survey was administered 

immediately following this task to capture the average and maximum workload 

experienced by the volunteer.

I.1.4.10 Engage Main Gun Targets – Defense 

This task was the first of four live-fire engagements. The tank crew engaged a series of 

five main gun targets from a defensive fighting position. To calculate the elapsed time 

for each reload, time was recorded each time a round was fired and each time the 

loader completed the procedure to reload the gun. To minimize the rest time for the 

loader between reloads, targets were chosen at close ranges and azimuths that 

facilitated quick acquisition and engagement of subsequent targets. 

Employing the main gun is a physically strenuous task for the loader (see section 2.2 

Reload Main Gun). In contrast, the tank commander and gunner use fine motor skills 

and hand-eye coordination to identify targets, aim, and fire the weapons. Quick loading

and reloading of the main gun has a direct effect on the crew’s rate of fire and combat 

effectiveness.

I.1.4.11 Employ Loaders Weapons System

The loader’s weapons system is a M240 medium machinegun pintle-mounted, adjacent 

to the loader’s hatch. This task required the loader to engage a group of four man-sized 
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targets approximately 250 m from a defensive fighting position. Three metrics were 

evaluated during this engagement: the percentage of engagements resulting in effects 

on target, the time to first effects on target, and the time required to reload the weapon. 

The time to first effects on target was calculated by collecting time hacks when the 

targets first appeared and when the target recorded the first hit. The reload time was 

calculated by collecting time hacks when the loader reported having expended all 

ammunition and when the loader resumed engaging the target. The targets were set to 

continuously reappear so that the loader would run out of ammunition and be forced to 

conduct the reloading portion of the task. 

I.1.4.12 Reload Commander’s Weapon Station

The third engagement took place in a defensive fighting position. The loader reloaded

the commander’s M48 heavy machinegun overhead with minimal exposure outside the 

protective armor of the tank. The task began with the tank commander engaging a 

target with his weapons station. A starting time hack was recorded when the weapon 

ran out of ammunition, and an ending time hack was recorded when the reload was 

complete and the tank commander resumed engaging the target. Performance 

evaluation was based on the total time required to conduct the reload.

I.1.4.13 Engage Main Gun Targets – Offense 

In the final live-fire task, the tank crew engaged a series of four main-gun targets while 

in the offense, similar to the Engage Defensive Targets task, except that the tank was 

maneuvering downrange while engaging the targets rather than engaging targets from a 

stationary defensive fighting position. To calculate the elapsed time for each reload, 

time hacks were captured each time a round was fired and each time the loader 

completed the procedure to reload the gun. To minimize the rest time for the loader 

between reloads, targets were chosen at close ranges and azimuths that facilitated 

quick acquisition and engagement of subsequent targets. 

I.1.5 Loading Events

Eighteen of the 19 volunteers participated in experiment trials each cycle. To provide 

equivalent loading for the one extra volunteer not participating in trials during that cycle, 

the extra Marine was assigned similar duties to perform. On maintenance and non-livefire days, the extra Marine assisted tank crews and the unit’s mechanics perform nontrial-specific preventive maintenance and repairs. On the live-fire day, the extra Marine 

worked at the FASP. Tasks at the FASP included downloading ammunition from the 

tanks between and after trials, staging ammunition for trials, and sorting dunnage. 

These loading tasks were physically similar to the experimental trials, involving similar 

levels of physical exertion, used the same basic muscle groups, and were performed for

a similar duration as the experimental trials. 
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I.1.6 Scheme of Maneuver Summary

The 1812 experiment’s 3-day cycles consisted of a maintenance day, a non-live-fire 

day, and a live-fire day. The maintenance day consisted of standard non-evaluated 

preventive maintenance and any necessary repair work. 

The non-live-fire day consisted of seven individual and crew-level tasks common to 

mission preparation and rehearsal. The day began with a crew-level maintenance task, 

followed by three crew-station-specific individual tasks, a crew evacuation, a 

CASEVAC, and a disabled-vehicle recovery task. 

The live-fire day consisted of six crew tasks conducted in two phases. Phase 1 involved 

uploading and transferring ammunition at the FASP. Phase 2 included a series of four 

live-fire engagements progressing from the defense to the offense and incorporating 

main gun and machinegun engagements. At the conclusion of the live-fire day, the unit 

reorganized into new tank crews in preparation for the next cycle. 

I.2 Limitations

I.2.1 Limitations Overview 

The GCEITF experiment was designed to allow operationally relevant tasks to occur as 

naturally as possible, while gathering unbiased measurements. Most tasks were 

performed in a similar manner to those in an operational environment. However, under 

certain situations, artificial limitations or interruptions were introduced that changed or 

altered the way a task would normally be performed. While these limitations represent 

a degree of artificiality, they do not detract significantly from our abilities to generalize 

the conclusions of this experiment to the performance of Marines in a field environment. 

The following limitations were observed for the 1812 assessment.

I.2.1.1 Number of Volunteer Participants

For the Tank experiment, 17 male and 3 female volunteers began the experiment, and 

16 male and 3 female volunteers completed the experiment. The results presented in 

this annex are based on the performance of 20 Marines. For population analysis (by 

gender and MOS), which examines the volunteer population and the comparative 

overall Marine Corps population, see Population Analysis, Annex Q. 

I.2.1.2 Limitations on Cumulative Loading Effect

The members of the M1A1 Tank Crewman assessment executed a variety of subtasks 

over the course of a 3-day trial cycle meant to encompass, as accurately as possible, 

the demands placed on a Tank Crewman MOS during an administrative field training 

environment. The evaluated subtasks within the cycle were considered the most 

physically demanding and operationally relevant tasks that a junior tank crewman would 

perform on a recurring basis. These subtasks were executed as they would normally be 
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performed; however, due to time constraints, data collection requirements, and other 

factors, limitations and artificialities existed in the assessment. These limitations had 

little to no effect on data collection, but impacted the cumulative loading effects and 

fatigue of the volunteers. The cumulative workload experienced by the volunteers 

during this assessment is most comparable to an administrative field training exercise

such as semiannual gunnery qualifications, or the initial phases of an Integrated Tactical 

Exercise. The experiment was not designed to replicate the 20-hour work days, multiday missions, or physical and mental hardships encountered during prolonged combat 

operations in an expeditionary environment. 

I.2.1.3 Low MOS School Graduation Rate

Eight female Marine volunteers were recruited for assignment to the 1812 MOSproducing Marine Armor Crewman Course and follow-on assignment to the GCEITF

tank platoon. Three of the 8 volunteers met all MOS school graduation requirements, 

while two more met the graduation requirements after participating in a remediation 

program not normally offered. Three of the recruited volunteers failed to meet the 

course requirements and were dis-enrolled. Of the five volunteers who graduated and 

received follow-on assignments to the GCEITF, two withdrew from the experiment 

voluntarily before the unit began workup training for the experiment. The remaining 

three Marines completed the entire research program. This limitation highlights that the 

inferences of results and conclusions to be applied to future physical, physiological, and 

performance standards for the 1812 MOS community are based on a smaller-thanplanned sample size of females conducting the GCEITF experiment.

I.2.1.4 Omitted High-Concentration Group

The 1812 experiment included two comparison groups—a control group consisting of an 

all-male tank crew, and a low–female density group consisting of one female Marine 

integrated into an otherwise male tank crew. This assessment intended to include an 

additional high–female density group consisting of tank crews with two female Marines, 

but the low number of qualified female volunteers led the research team to eliminate this 

group. 

I.2.1.5 Experience Disparities

Volunteers enrolled in the research program came from a variety of Marine Corps 

backgrounds and had varying levels of experience in the 1812 MOS. All male 

volunteers were recruited from active duty or reserve tank battalions, and possessed 

varying levels of operational experience. In contrast, female volunteers had no 

experience in the 1812 MOS before participating in the program. Prior to arriving at the 

test unit, female volunteers were sent to the 1812 MOS-producing Marine Armor 

Crewman Course. 
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The unit’s pre-experiment workup at Camp Lejeune was designed to bring all volunteers 

to the minimum level of proficiency necessary to execute the experiment, and to provide 

an equivalent level of experience in performing the experiment-specific tasks. Unit 

workup training prior to the assessment consisted of approximately 20 weeks of crewlevel training at Marine Corps Base Camp Lejeune, NC. The unit completed multiple 

non-live-fire field training exercises, Gunnery Skills Test qualifications for each 

crewman, and Tank Table VI crew gunnery qualifications. Each volunteer designated to 

rotate crew positions received extensive training in the Driver and Loader crew 

positions, including live-fire gunnery training in each position. 

I.2.1.6 Change in SOPs Influenced Accurate Measurement of Ammunition 

Resupply Task

The task to conduct an ammunition resupply was designed to evaluate a tank crew’s 

performance uploading a full complement of ammunition onto the vehicle from a FASP. 

During the experiment, the unit developed an SOP that required the gunner (a 

nonrotating, male volunteer) to perform the majority of the physical work. The gunner 

was responsible for removing the main gun rounds from the stowage containers, 

transporting them approximately 20 meters to the tank, and lifting the rounds up to the 

crewmen standing on the tank. After the gunner delivered each round to the tank, the

driver and loader were responsible for taking the round and stowing it inside the turret. 

In addition to the gunner performing the most challenging components of the task, this 

method prevented the loader and driver from working continuously. Because the 

gunner’s role in the retrieval and stowage of each round took the greatest amount of 

time, the elapsed time measures the gunner’s performance and was not influenced by 

the performance of the other crewmen. For these reasons, this report cannot provide a

meaningful performance comparison of all-male and integrated crews in completing the 

task of conducting an Ammunition Resupply. 

I.2.1.7 Limitations Summary

The Tank Crewman assessment sought to replicate the realities of field conditions and 

loading Marines experience during field training and combat operations. The 

assessment team balanced these demands with the necessity of collecting equitable 

and uniform data throughout the assessment’s duration and across participants. This 

led to artificialities that departed from normal operations but did not affect the validity of 

data collection or the assessment as a whole. Limitations were presented due to the 

lack of volunteers caused by low graduation rates at the MOS-producing school.
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I.3 Deviations

I.3.1 Experimental Groups

The M1A1 Tank Crewman experiment was designed to include three experimental 

groups for comparison: a control group (all-male tank crew), a low-concentration group 

(one female crewmember per tank), and a high-concentration group (two female 

crewmembers per tank). The limited number of female participants caused the highconcentration group to be eliminated. This deviation from the EAP changed the number 

of total trials required to conduct the analysis.

I.3.2 Conduct Ammunition Resupply

This task was originally designed to evaluate the tank crew’s performance in uploading 

a full complement of ammunition onto the vehicle from a field ammunition supply point. 

During the experiment, the unit developed a standard operating procedure that required 

the Gunner (a non-rotating, male volunteer) to perform the vast majority of the physical 

work. The Gunner was responsible for removing the main gun rounds from their storage 

containers, transporting them approximately 20 meters to the tank, and lifting the rounds 

up to the other crewmen standing on the tank. After the Gunner delivered each round to 

the tank, the driver and loader were responsible for taking the round and storing it inside 

the turret. In addition to the gunner performing the most challenging components of the 

task, this method also prevented the loader and driver from working continuously. 

Because the gunner’s role in the retrieval and storage of each round took the greatest 

amount of time, the elapsed time primarily measures the gunner’s performance and was 

not influenced by the performance of the other crewmen. For these reasons, this report 

cannot provide a meaningful comparison of the performance of all-male and integrated 

crews in completing this task. 

I.4 Data Set Description

I.4.1 Data Set Overview

The 1812 portion of the experiment consisted of 2 pilot trial cycles and 12 record trial 

cycles. The pilot trial cycles were conducted from 3 March through 8 March 2015. Pilot 

data were not used in analysis due to variations in the conduct of the experimental 

trials. We base all analysis on the 12 record trial cycles executed from 9 March to

16 April 2015. 

I.4.1 Record Test Volunteer Participants 

At the beginning of the first record cycle, there were 17 male and 3 female volunteers. 

There was one Marine who voluntarily withdrew during the execution of the experiment. 

The final number of volunteers was 16 males and 3 females. 
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I.4.2 Planned, Executed, and Analyzed Trials

Table I-1 displays the number of trials planned, executed, and analyzed by task. Sixtyfour record trials were planned, with the option of conducting an additional 12 trials. A 

total of 72 record trials were ultimately conducted. All 72 trials were analyzed with 

respect to the non-live-fire tasks. During two record cycles, abnormalities occurred 

preventing the live-fire tasks from being conducted or recorded. On one particular day, 

data collection error resulted in the loss of all live-fire trials for all six tank crews. On 

another occasion, one tank crew was unable to conduct the live-fire trials due to a drop 

on request (DOR) mid-trial cycle. A total of 65 trials were analyzed with respect to the 

live-fire tasks. 

Table I-1. 1812 Planned, Conducted, and Analyzed Trials

Metric Integration 

Level

Number 

Planned Trials

Number of 

Trials 

Conducted 

Number of 

Trials Used in 

Analysis

Not 

Analyzed

Perform Maintenance 

Actions (minutes)

C 33 36 31 5a

LD 33 36 31 5a

Load and Arm Main Gun 

(seconds)

C 66 72 64 8

a

LD 66 72 66 6a

Manipulate Turret/Main Gun 

(minutes)

C 66 72 66 6

a

LD 66 72 66 6a

Prep Commander’s Weapon 

Station (minutes)

C 66 72 63 9a

LD 66 72 66 6

a

Conduct Crew Evacuation 

(seconds)

C 33 36 32 4

a

LD 33 36 33 3

a

Evacuate Wounded 

Crewmen (minutes)

C 33 36 30 5

a

1b

LD 33 36 33 3

a

Conduct Vehicle Recovery; 

Operational Tank (minutes)

C 33 36 32 4

a

LD 33 36 33 3a

Transfer Ammunition 

(minutes)

C 33 36 34 1

a, 1b

LD 33 36 36 N/A

Engage Main Gun Targets –

Defense (seconds) C 165 175 160 15a

LD 165 180 164 15a, 1b

Employ Loader’s M240; First 

Hit (proportion) C 33 35 35 N/A

LD 33 36 36 N/A

Employ Loader’s M240: First 

Hit (seconds)

C 33 35 22 13a

LD 33 36 26 10a

Employ Loader’s M240: 

Reload (seconds)

C 33 35 32 3

a

LD 33 36 33 3

a

Reload Commander’s 

Weapon Station (M48) 

(minutes)

C 33 35 32 3

a

LD 33 36 32 3

a

, 1b
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Metric Integration 

Level

Number 

Planned Trials

Number of 

Trials 

Conducted 

Number of 

Trials Used in 

Analysis

Not 

Analyzed

Engage Main Gun Targets – 

Offense (seconds)

C 132 140 127 12a

, 1b

LD 132 144 132 12a

a. Data Collection Error: data was not captured or captured incorrectly due to Data Collector (human) error or data processing 

(equipment) error. b. Trial was identified as an outlier using box plot analysis, as described in the Methodology Annex. 

I.5 Descriptive and Basic Inferential Statistics 

I.5.1 Descriptive Statistics Overview

Performance metrics were measured during the conduct of 13 common Tank Crewman 

tasks and were indicative of crew-level proficiency in core MOS skills. Performance in 

these critical MOS tasks provides a good indication of the efficiency, survivability, and 

lethality of a tank crew. To further understand the descriptive statistics analysis, a brief

explanation of tank crew billets and how the crews were organized for comparison of 

integration levels and individual performance is provided below. 

This report describes the performance of various tank crew combinations when 

integrating MOS-qualified female Marines with MOS-qualified male Marines. It is 

important to quantify the billets within a tank crew, and to understand which billets the 

volunteers filled during the experiment. A tank crew consists of the four Marines who 

operate an M1A1 main battle tank. The crew positions include the Driver, the Loader, 

the Gunner, and the Tank Commander; these billets will be mentioned throughout this 

Annex. In a typical crew, the driver is the most junior and least-experienced Marine, 

followed by the loader. Both of these crew positions are normally filled by Marines in 

grades E-1 to E-3. The gunner is typically an E-4 or E-5, with a minimum of several 

years of experience in the MOS. The crew is led by the Tank Commander, a senior 

noncommissioned officer or staff noncommissioned officer who is the most experienced 

Marine on the crew. 

The majority of the volunteers rotated between driver and loader billets by random 

selection without regard to MOS knowledge or experience. The gunner billets were filled 

by six nonrotating male volunteers with extensive MOS experience. The tank 

commanders were all direct-assignment male Marines, also with extensive MOS 

experience. The Marines assigned as gunners and tank commanders did not rotate 

because of the requirement for gunners and tank commanders to perform workup 

training and qualify together prior to conducting live fire (FM 3-20.21). For the safety of 

the volunteers, it was necessary to avoid assigning inexperienced crewmen to perform 

the gunner or tank commander’s responsibilities, and to avoid conducting trials with 

gunner–tank commander combinations that had not previously qualified together. 
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This report refers to various concentrations of vehicle crews in terms of integration 

levels. A control (C) group refers to an all-male crew, and is representative of the tank 

community as it currently exists. The low-density (LD) group refers to a genderintegrated crew consisting of three male Marines and one female Marine. If a task is 

performed by the entire crew, the comparison is between the performance of the C and 

LD groups. 

Due to the individual nature of some tasks, the gender of the Marine in a critical billet 

matters more than the total integration level of the crew. If a task is individual in nature, 

the comparison is between the performance of male (M) volunteers and female (F) 

volunteers. If a task is performed at the crew level, but disproportionally influenced by 

the performance of one individual, both methods of comparison are used. 

Special caution should be taken when comparing similar tasks executed by different 

MOSs across the GCEITF experiment. Comparative analysis may be misleading due to 

differing factors between MOS tasks, such as distances, techniques, leadership, load 

carried, group size, and group composition.

I.5.2 Selected Tasks Descriptive Statistics Results

Table I-2 and Table I-3 display descriptive statistics results for six selected 1812 tasks 

that were also modeled using personnel variables (see Modeling Results Section I.6). 

The remaining tasks are included in Appendix I M1A1 Tank Crewman (MOS 1812). 

Table I-2 displays the metrics and integration levels with respect to sample sizes, 

means, and standard deviations. Table I-3 displays analysis of variance (ANOVA) and 

Welch’s test results. The ANOVA table includes metrics and integration levels, p-values 

indicating statistical significance, integration-level elapsed-time and percent differences, 

and the upper and lower confidence bounds. In addition to conducting an ANOVA, a 

Welch’s t-test was performed to examine the variances. P-values less than the

significance level of 0.10 identify statistical significance. The words “metric” and “task” 

are used interchangeably throughout this Annex; both refer to the experimental task. 

Table I-2. 1812 Selected Tasks Results

Metric Integration Level Sample 

Size Mean SD 

Perform Maintenance Actions (minutes) * C 31 77.92 22.07

LD 31 86.64 22.52

Manipulate Turret/Main Gun (minutes) * M 100 8.14 2.48

F 32 8.97 3.08

Evacuate Wounded Crewmen (minutes)

C 30 3.97 1.33

LD 33 4.12 1.07

Conduct Vehicle Recovery; Operational 

Tank (minutes)

C 32 8.26 2.14

LD 33 8.50 2.59

Engage Main Gun Targets – Defense* C 160 11.57 6.23
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Metric Integration Level Sample 

Size Mean SD 

(seconds) LD 164 14.07 8.01

M 234 12.42 7.97

F 90 13.92 4.97

Engage Main Gun Targets – Offense * 

(seconds)

C 127 8.84 3.50

LD 132 9.53 3.20

M 187 8.99 3.46

F 72 9.72 3.05

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the metric’s mean 

values for the Integration Level.

Table I-3. Analysis of Variance (ANOVA) and Welch’s t-test

Metric

F 

statistic 

(df) 

F 

Test

Pvalue

Comp

arison Diff % Diff. 1-Sidedp-Value

2-Sided 

p-Value

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Perform 

Maintenance 

Actions 

(minutes)*

2.37 

(1, 60) 0.13 LD - C 8.72 11.19% 0.06* 0.13 1.38 16.06 -0.74 18.18

Manipulate 

Turret/Main 

Gun*

2.41 

(1, 130) 0.12 F - M 0.83 10.21% 0.09* 0.17 0.05 1.61 -0.18 1.84

Evacuate 

Wounded 

Crewmen

0.22 

(1, 61) 0.64 LD - C 0.15 3.57% 0.32 0.64 -0.61 0.39 -0.75 0.53

Conduct 

Vehicle 

Recovery

0.16 

(1, 63) 0.69 LD - C 0.24 2.86% 0.34 0.69 -0.53 1.00 -0.75 1.22

Engage Main 

Gun Targets – 

Defense*

9.74 

(1, 322)

< 

0.01* LD - C 2.5 21.53% < 0.01* <0.01* 1.47 3.51 1.18 3.81

2.79

(1, 322) 0.10* F - M 1.5 12.11% 0.02* 0.04* 0.55 2.45 0.28 2.72

Engage Main 

Gun Targets – 

Offense*

2.73 

(1, 257) 0.10* LD - C 0.69 7.78% 0.05* 0.10* 0.15 1.22 0.00 1.38

2.48

(1, 257) 0.12 F - M 0.73 8.15% 0.05* 0.10* 0.17 1.30 0.01 1.46

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the metric’s mean 

values for the Integration Level.

The conditions and performance steps for each selected task will be described, along 

with scatterplots depicting the results of each trial conducted for that task. In each 

scatterplot, the solid blue dots represent the control (C) or male group, and the red 

circles represent the low-density (LD) integration or female group. Outliers excluded 

from analysis are identified by a solid black circle placed around the data point. 

Contextual comments and additional insights may be presented with each experimental 

task to help familiarize readers with the nature and importance of each task in a combat 

environment.
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I.5.3 Perform Maintenance Actions Overview

Tank crewmen in the operating forces typically spend a significant percentage of 

available man-hours performing routine maintenance. This work is often very physically 

demanding because the parts, tools, and equipment organic to a tank unit are large and 

heavy. A proficient and effective tank crewman will be capable of performing multiple

hours of preventative maintenance or repairs each day. This is operationally realistic 

and an indispensable part of every tank crewman’s job. There were two integration 

levels assessed for this task—a control (C) group of all male Marines, and a low-density 

(LD) group with one female in the tank crew.

A specific experiment task was developed to evaluate a tank crew’s ability to perform 

common maintenance procedures. The task involved separating the track, removing 

and replacing a track section, and reinstalling the track. This task was chosen because 

it is physically demanding, repeatable, and commonly performed under timeconstrained conditions in a combat environment. The time for this task started when the 

tank commander gave the order to begin, and finished when the task was complete with 

all crewmen back in their stations. 

I.5.3.1 Performance Maintenance Action 

For this task, sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA.

On average, the C crew performed 11.19% faster than a LD crew. The C group 

performed the task in a mean time of 77.92 minutes while the LD group had a mean 

time of 86.64 minutes, which results in a statistically significant p-value of 0.06. 

Figure I-1 (scatterplot) displays data used in the analysis of the results. 
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Figure I-1. Perform Maintenance

I.5.3.2 Performance Maintenance Action Contextual Comments

Maintenance tasks similar to this one are commonly required to repair damage 

sustained during operations. When a tank sustains damage to its track or suspension 

during a mission, the crew will be required to perform repairs encompassing some or all 

of the performance steps required for this task. In a combat environment, it is critical to 

perform repairs and regain mobility quickly, denying the enemy the opportunity to attack 

a stationary target. 

I.5.3.3 Performance Maintenance Action Additional Insights

In relation to performing preventative maintenance or repairs in a garrison environment, 

if we extend the result of this task out to an average maintenance workday, we can 

expect that an integrated crew would require approximately 10 hours to perform the 

work that a non-integrated crew would perform in 9 hours. In real-world operations, this 

difference translates into increased times required to prepare for a mission or perform 

maintenance after an operation.

I.5.4 Manually Manipulate Turret and Main Gun Overview

The turret and main gun of the M1A1 are operated primarily by electric and hydraulic 

systems. As a backup, they can be manipulated manually using crank handles located 

in the gunner’s station. These backups provide a way for the crew to continue the fight 

in the event of a hydraulic or electrical malfunction. This task required each volunteer to 
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manually traverse the turret 180 degrees to the left, raise the main gun to its maximum 

elevation, lower the main gun to its minimum elevation, then traverse the turret 180 

degrees back to the right. This task is an individual event; other crewmembers were 

unable to influence the performance of the task. The data collected from this task were 

analyzed according to the gender of the Marine performing the task rather than the 

integration level of the crew. Time started when the tank commander gave the 

command to begin, and ended when the Marine completed the course of movement. 

I.5.4.1 Manually Manipulate Turret and Main Gun 

For this task, sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA.

Males (M) performed the task in a mean time of 8.14 minutes, while females (F) 

performed the task in a mean time of 8.97 minutes. The results of the data analysis 

show that the male crewman performed this task an average of 10.21% faster than the 

female crewman. These results are statistically significant, as identified by a p-value of 

0.09. The male group performed the task an average of 49.8 seconds faster than the 

female group. 

Figure I-2 (scatterplot) displays data used in the analysis of the results. 

Figure I-2. Manually Manipulate Turret and Main Gun

Critical Billet Gender
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I.5.4.2 Manually Manipulate Turret and Main Gun Contextual Comments

Similar to the reloading speed task, the ability to acquire and engage targets faster than 

an adversary provides a competitive advantage in a combat environment. The manual 

traverse and elevation mechanisms are backup systems that allow the M1A1 to remain 

operational when degraded. Mechanical failures in the primary system can be expected 

to occur in time. Tank crewmen are also required to manually traverse the turret as a 

component of several routine maintenance procedures. 

I.5.5 Evacuate Wounded Crewmen Overview

This task measured each tank crew’s ability to evacuate an incapacitated crewman to a 

simulated landing zone (LZ) 50 meters away. A 205-lb dummy served as a simulated 

casualty, staged in the gunner’s station and equipped with full personal protective 

equipment. The gunner’s station is the most difficult location from which to evacuate a 

Marine because of its inaccessibility and limited workspace. The task involved lifting the 

dummy out the loader’s hatch and onto the roof of the turret, followed by carrying the 

casualty to a simulated LZ 50 meters behind the vehicle. The time for this task started 

when the crew was given the command to evacuate the casualty, and finished when all 

crewmen (including the dummy) reached the LZ. 

I.5.5.1 Evacuate Wounded Crewmen 

For this task, sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA.

On average, the C group performed the task 3.57% faster than the LD group. The C 

group performed the task in a mean time of 3.97 minutes while the LD group had a 

mean time of 4.12 minutes. Based on a p-value of 0.32 in a single-sided t-test, there is 

no statistically significant difference between the C and LD groups. 

Figure I-3 (scatterplot) displays data used in the analysis of the results. 
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Figure I-3. Evacuate Wounded Crewman

I.5.5.2 Evacuate Wounded Crewmen Contextual Comments

Performing a CASEVAC quickly enables the casualty to receive immediate medical 

attention. In situations such as a fire, it may be necessary to evacuate a casualty from a 

damaged tank before the sympathetic detonation of onboard fuel or high-explosive 

rounds create additional casualties. In this type of situation, evacuation speed directly 

impacts the crew’s chances of survival. 

I.5.6 Conduct Vehicle Recovery Overview

Tank sections are equipped and trained to perform self-recovery in the event that a tank 

becomes disabled. Performing tank recovery involves crewmembers from each tank 

dismounting from their vehicles, removing the 300-lb. tow bars from the stowage 

position on the operational tank, mounting the tow bars on the front of the disabled tank, 

and then holding the tow bars in place approximately 3 feet off the ground while the 

operational tank maneuvers into position to connect the tow bar’s lunette eye to a pintle 

hitch. The task begins and ends with all crewmen in their assigned stations. The time 

started when the section leader gave the command to “conduct recovery” and stopped 

when both vehicles were rigged and ready to tow. 

I.5.6.1 Conduct Vehicle Recovery 

For this task, sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA.
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On average, the all-male control group was 2.86% faster than the low-density integrated 

group. The C group performed the task in a mean time of 8.26 minutes. The LD group 

performed the task in a mean time of 8.50 minutes. Based on a p-value of 0.34 in a 

single-sided t-test, there is no statistically significant difference between the C and LD 

groups. 

Figure I-4 (scatterplot) displays data used in the analysis of the results. 

Figure I-4. Conduct Vehicle Recovery

I.5.6.2 Conduct Vehicle Recovery Contextual Comments

In a combat environment, it is desirable to recover a disabled vehicle quickly, denying 

the enemy the opportunity to maneuver or employ fires against a stationary tank. A time 

difference of approximately 30 seconds may or may not have a significant operational 

impact, depending on the specific circumstances of the situation. 

I.5.7 Engage Main Gun Targets – Defense Overview

This task was the first of four live-fire engagements. The tank crew engaged a series of 

five main-gun targets from a defensive fighting position. The engagements were similar 

to those conducted during semiannual crew and section gunnery qualifications. 

Employing the main gun is a physically strenuous task for the loader (see 1.2 Reload 

Main Gun). Although other crewmembers were not directly involved in reloading the 

main gun, the performance of the driver can have a significant effect on the loader’s 
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performance. Erratic acceleration and braking by the driver while moving up and down 

a defensive fighting position made the loader’s job more difficult to perform. 

To calculate the elapsed time for each reload, time hacks were captured each time a 

round was fired and each time the loader completed the procedure to reload and arm 

the gun. To minimize the rest time for the loader between reloads, targets were chosen 

at close ranges and azimuths that facilitated quick acquisition and engagement of 

targets by the gunner. 

I.5.7.1 Engage Main Gun Targets – Defense 

For this task, sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA.

Data collected from this task were analyzed in two separate ways. The first comparison 

looked for performance differences between the control (C) group and the low-density 

(LD) group, a crew with a female in the driver or loader position. Loaders in the control 

group crews reloaded the main gun in an average time of 11.57 seconds, while the lowdensity crew had an average reload time of 14.07 seconds. The 21.53% difference 

between the means is statistically significant. An all-male crew can be expected to 

outperform a low-density integrated crew by an average 2.5 seconds on each of the five 

reloads. 

The second comparison looked for performance differences between crews grouped 

only by the gender of the loader (regardless of the crew composition). Any crew with a 

male loader would be considered part of the control group using this method. The male 

loaders (M) reloaded the main gun in an average time of 12.42 seconds, while the 

female loaders (F) had an average reload time of 13.92 seconds. The 12.11% 

difference between the means is statistically significant. A male loader can be expected 

to outperform a female loader by an average of 1.5 seconds. 
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Figure I-5. Engage Main Gun Targets – Defensive

Figure I-6. Engage Main Gun Targets – Defensive

Critical Billet Gender
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I.5.7.2 Engage Main Gun Targets – Defense Contextual Comments

In combat operations, faster reload times are highly desirable. Because the rate of fire 

is primarily limited by the speed at which the loader can manually reload the main gun,

reloading speed has a significant impact on the crew’s combat effectiveness and 

survivability. The ability to reload the main gun rapidly is absolutely critical when reengaging a target or engaging multiple targets. Although this task is primarily the 

loader’s responsibility, the potential for combat losses requires all crewmen to be 

capable of performing the task. 

I.5.8 Engage Main Gun Targets – Offense Overview

In the fourth and final live-fire task, the tank crews engaged a series of four main-gun 

targets while in the offense. This task is similar to the Engage Main Gun Targets – 

Defense task described in section 1.10, except that the crews engaged targets while 

maneuvering downrange, instead of shooting from a defensive fighting position. To 

calculate the elapsed time for each reload, time hacks were captured each time a round 

was fired and each time the loader completed the procedure to reload the gun. To 

minimize the rest time for the loader between reloads, targets were chosen at close 

ranges and azimuths that facilitated quick acquisition and engagement of subsequent 

targets. As with the Engage Defensive Targets task, data collected from this task were

analyzed by crew composition and by gender of the loader. Because the performance of 

the driver had a much smaller effect on the loader in the offense than in the defense, 

the second gender-based method (as identified in the following sections) should be 

considered the primary measure for analyzing the results of this task. 

I.5.8.1 Engage Main Gun Targets – Offense 

For this task, sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA.

The first comparison looked for performance differences between the control (C) group 

and the low-density (LD) group. Loaders in the control group crews reloaded the main 

gun in an average time of 8.84 seconds, while the low-density crew had an average 

reload time of 9.53 seconds. The 7.78% difference between the means is statistically 

significant, yielding a p-value of 0.05. 

The second comparison looked for performance differences between crews grouped 

only by the gender of the loader (regardless of crew composition). Male (M) loaders 

reloaded the main gun in an average time of 8.99 seconds, while female (F) loaders had 

an average reload time of 9.72 seconds. The 8.15% difference between the means is 

statistically significant. A double-sided t-test produces a p-value of 0.10, and a singlesided t-test produces a p-value of 0.05. 

Figure I-7 and Figure I-8 (scatterplots) depict the results of each trial conducted. 
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Figure I-7. Engage Offensive Targets

Figure I-8. Engage Offensive Targets 

Critical Billet Gender
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I.5.8.2 Engage Main Gun Targets – Offense Contextual Comments

In combat operations, faster reload times are highly desirable. Because the rate of fire 

is primarily limited by the speed at which the loader can manually reload the main gun, 

reloading speed has a significant impact on the crew’s combat effectiveness and 

survivability. The ability to reload the main gun rapidly is absolutely critical when reengaging a target or engaging multiple targets. Although this task is primarily the 

loader’s responsibility, the potential for combat losses requires all crewmen to be 

capable of performing the task. 

I.6 Statistical Modeling Results

I.6.1 Statistical Modeling Results Overview

The previous section discussed results only as they pertain to differences due to 

integration level alone. The goal of statistical modeling, as applied here, is to estimate 

simultaneously the effect of gender-integration levels and other relevant variables on 

tank crew performance. (Refer to the Methodology Annex for a broad overview of the 

analysis plan and the variables used in the models.) 

For the selected tasks described in the previous section, this section presents an 

overview of the analysis and results, and then presents the modeling results for each 

task. 

For each task, we describe the significant variables in the model, and whether these 

variables are either positively or negatively correlated with the result. A negative 

correlation indicates that the increase in that variable will result in a decrease in the 

response variable, which is a desired outcome for elapsed time. 

I.6.2 Selected Tasks Method of Analysis

A mixed-effects model with all crew members and all types of personnel data does not 

work for the Tank dataset. Thus we model each personnel variable with integration 

level separately with a random effect for who filled each position in the Tank crew. For 

example, age for each member of the Tank crew (three variables), a random-effect for 

who filled each billet, and integration level are modeled with the result (response time) 

as the response variable. For tasks that had critical billets (i.e., only one or two Marines 

were performing the task without help from others), only their personnel data and 

gender were included in the model. Where maximum likelihood estimation converged, 

AIC was used for variable selection. Otherwise, we comment on the significance of 

individual variables in the full model. Variables reported as significant are concluded to 

be significant based on at least a one-sided test.
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I.6.3 Selected Tasks Overall Modeling Results

There are no personnel data variables that are both statistically significant and have a 

practical impact in the model. Each time personnel data variables are statistically 

significant in a model, their effects are practically negligible, conflicting, and/or 

incomplete for the tank crew (i.e., there are no tasks for which a variable is significant 

for all or even most members of the tank crew). 

Integration level consistently appears as statistically significant in each task, and its 

effect is clear, causal, and practical; integration level is the best variable to describe 

performance for each task. (Refer to section I.5.2 Descriptive Statistics Results for the 

ANOVA summary for each of the below-mentioned tasks.) 

I.6.3.1 Perform Maintenance Actions

We modeled elapsed time for maintenance actions as a function of each personnel 

variable for each crewmember and integration level in a mixed-effects model with a 

random effect for who filled each position. The covariates in each model are the values 

of each personnel variable for each volunteer member in the tank crew. We report 

statistically significant positive and negative correlations, and whether we observe any 

patterns.

The crew composition is significant and positively correlated with performing 

maintenance actions, indicating that integrated crews perform this task slower than allmale crews. 

The models for the following variables do not run due to missing values:

• None.

The LD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Age 

• AFQT

• GCT 

• Height 

• Weight 

• CFT MTC 

• CFT MANUF

• PFT Run Score 

• Rifle Score. 
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The LD integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with performing maintenance actions: 

• PFT Crunch score of the Driver. 

The following personnel variables are significant in their respective models and are 

negatively correlated with performing maintenance actions: 

• GCT Score of the Loader

• CFT MANUF of the Gunner. 

The following personnel variables have no significant variables in their respective 

models:

• None. 

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, our final model includes integration level only, where LD has 

a difference of 10.33 minutes when compared to a C group. The comparison is 

statistically significant. This difference is an increase from the 8.72-minute difference 

identified in the descriptive statistics, which is an 18.46% change.

I.6.3.2 Manually Manipulate Turret and Main Gun; Driver

We modeled elapsed time for manually manipulating the turret and main gun by the 

critical billet (Driver) as a function of the personnel variables and gender of the Marine 

performing the task in a mixed-effects model with a random effect for who filled each 

position. The covariates in each model are the values of each personnel variable for 

each volunteer member in the tank crew. We report statistically significant positive and 

negative correlations.

The gender of the Driver was not significant and ultimately not selected into the final 

model for elapsed time for manually manipulating the turret, indicating that Driver 

gender is not a good predictor of time to execute this task. 

The models for the following variables do not run due to missing values:

• None.

The LD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• None.
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The LD integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables:

• None.

The following Driver variables are significant in the model and are positively correlated 

with manually manipulating the turret: 

• PFT Crunch Score. 

The following Driver variables are significant in the model and are negatively correlated 

with manually manipulating the turret: 

• Height. 

There are no patterns for any Driver variables for manually manipulating the turret and 

main gun. 

Because integration level is not significant in the final model, there is no final mixed 

effects model for this task. (Refer to the section I.5.2 for this task to see the ANOVA 

results.) 

I.6.3.3 Manually Manipulate Turret and Main Gun; Loader

We modeled elapsed time for manually manipulating the turret and main gun by the 

critical billet (Loader) as a function of the personnel variables and gender of the Marine 

performing the task in a mixed-effects model with a random effect for who filled each 

position. The covariates in each model are the values of each personnel variable for 

each volunteer member in the tank crew. We report statistically significant positive and 

negative correlations.

The gender (male) Loader is significant and negatively correlated with manually 

manipulating the turret, indicating that males perform this task faster than females. 

The LD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• None.

The LD integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables:

• None.

The following Loader variables are significant in the model and are positively correlated 

with manually manipulating the turret: 

• None. 
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The following Loader variables are significant in the model and are negatively correlated 

with manually manipulating the turret: 

• Gender

• Age. 

Because the effects of the personnel variables do not have any patterns and their 

effects are often negligible, our final model includes critical billet gender only, where 

females have a difference of 1.98 minutes when compared to males. The comparison is 

statistically significant.

I.6.3.4 Evacuate Wounded Crewman

We modeled elapsed time for evacuating a wounded crewman as a function of each 

personnel variable for each crew member and integration level in a mixed-effects model 

with a random effect for who filled each position. The covariates in each model are the 

values of each personnel variable for each volunteer member in the tank crew. We 

report statistically significant positive and negative correlations, and whether we 

observe any patterns.

Gender integration levels were not selected by the AIC into the final model of elapsed 

time to evacuate a wounded crewman, indicating that integration level is not a good 

predictor of time to evacuate a wounded crewman.

The models for the following variables do not run due to missing values:

• None.

The LD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• None.

The LD integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables:

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with evacuating a wounded crewman: 

• PFT Crunch Score of the Driver. 

The following personnel variables are significant in their respective models and are 

negatively correlated with evacuating a wounded crewman: 

• Rifle Score of the Gunner. 
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The following personnel variables have no significant variables in their respective 

models:

• Age 

• AFQT 

• GCT 

• Height 

• Weight 

• CFT MTC 

• CFT MANUF 

• PFT Run. 

There are no patterns for any personnel variables for evacuating a wounded crewman.

Because integration level is not significant in the final model and there are no variables 

that are significant for the crew, there is no final mixed-effects model for this task. 

(Refer to the section I.5.2 for this task to see the ANOVA results.) 

I.6.3.5 Conduct Vehicle Recovery

We modeled elapsed time for conducting a vehicle recovery as a function of each 

personnel variable for each crewmember and integration level in a mixed-effects model 

with a random effect for who filled each position. The covariates in each model are the 

values of each personnel variable for each volunteer member in the tank crew. We 

report statistically significant positive and negative correlations, and whether we 

observe any patterns.

The models for the following variables do not run due to missing values:

• None.

The LD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables:

• None.

The LD integration level is significant and negatively correlated with the response for the 

models that include the following personnel variables:

• None.

The following personnel variables are significant in their respective models and are 

positively correlated with conducting a vehicle recovery: 
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• None. 

The following personnel variables are significant in their respective models and are 

negatively correlated with conducting a vehicle recovery: 

• CFT MTC of the Loader

• CFT MANUF of the Loader

• PFT Run score of the Loader. 

The following personnel variables have no significant variables in their respective 

models:

• Age 

• AFQT 

• GCT 

• Height 

• Weight 

• PFT Crunch 

• Rifle Score. 

There are no patterns for any personnel variables for conducting a vehicle recovery. 

Because integration level is not significant in the final model and there are no variables 

that are significant for the crew, there is no final mixed-effects model for this task. 

(Refer to the section I.5.2 for this task to see the ANOVA results.) 

I.6.3.6 Engage Main Gun Targets – Defense 

We modeled elapsed time for a defensive engagement with the main gun as a function 

of each personnel variable for each crew member and integration level in a mixedeffects model with a random effect for who filled each position. The covariates in each 

model are the values of each personnel variable for each volunteer member in the tank 

crew. We report statistically significant positive and negative correlations, and whether 

we observe any patterns.

The gender of the Loader was not significant and ultimately not selected into the final 

model for elapsed time for a defensive engagement with the main gun, indicating that 

the Loader gender is not a good predictor of time to execute this task. 

The models for the following variables do not run due to missing values:

• None.
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The following Loader variables are significant in the model and are positively correlated 

with defensive engagements with the main gun: 

• GCT Score

• CFT MTC. 

The following Loader variables are significant in the model and are negatively correlated 

with defensive engagements with the main gun: 

• Height

• CFT MANUF

• PFT Crunch Score

• PFT Run Score. 

There are no patterns for any personnel variables for defensively engaging main gun 

targets. (Refer to the section I.5.2 for this task to see the ANOVA results.)

I.6.3.7 Engage Main Gun Targets – Offense 

We modeled elapsed time for an offensive engagement with the main gun as a function 

of each personnel variable for each crew member and integration level in a mixedeffects model with a random effect for who filled each position. The covariates in each 

model are the values of each personnel variable for each volunteer member in the tank 

crew. We report statistically significant positive and negative correlations, and whether 

we observe any patterns.

The gender of the Loader was not significant and ultimately not selected into the final 

model for elapsed time for an offensive engagement with the main gun, indicating that 

the Loader gender is not a good predictor of time to execute this task. 

The following Loader variables are significant in the model and are positively correlated 

with offensive engagements with the main gun: 

• GCT Score

• Weight. 

The following Loader variables are significant in the model and are negatively correlated 

with offensive engagements with the main gun: 

• AFQT Score

• Height

• CFT MANUF

• PFT Crunch Score
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• PFT Run Score. 

There are no patterns for any personnel variables for offensively engaging main gun 

targets. (Refer to the section I.5.2 for this task to see the ANOVA results.)
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Appendix to Annex I

1812 Supplemental Information

This appendix provides supplemental information for the 1812 portion of the GCEITF

experiment. It provides additional descriptive and basic inferential statistics not 

described in Annex I. 

Section 1: Additional Task Basic and Inferential Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. The experiment included a number of tasks and associated metrics 

conducted to enhance operational realism and maintain consistent application of the 

experimental process. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

This section presents results for additional 1812 tasks. Annex I contains the descriptive 

statistics for the remainder of the 1812 tasks. The words “metric” and “task” are used 

interchangeably throughout this Appendix. They both refer to the experimental task. 

Table I A displays the metrics and integration levels with their respective sample sizes, 

means, standard deviations, and percent difference between integration levels. 

Table I B displays ANOVA results, including metrics and integration levels, and p-values 

suggesting statistical significance. For each task, an ANOVA and t-test were conducted 

to compare the groups. If p-values are less than the a-priori determined significance 

level of 0.10, we conclude that there is statistical evidence that the response for the LD 

group is different from that in the C group. 

Table I A - 1812 Additional Tasks Results

Task and Metric Integration 

Level

Sample 

Size Mean SD % Difference

Load and Arm Main Gun (seconds)

M 97 6.45 1.39

F – M 15.51%

F 33 7.45 1.97

Prep Commander’s Weapon Station 

(minutes)

M 97 4.59 1.48

F – M 11.56%

F 32 5.12 2.07

Conduct Crew Evacuation (seconds)

C 32 37.03 5.49

LD - C -2.38%

LD 33 36.15 4.51

Transfer Ammunition (minutes)

M 53 8.04 2.60

F – M 14.80%

F 18 9.23 2.74

Employ Loader’s M240; First Hit 

(proportion)

M 35 0.78 N/A F – M -8.33%

F 13 0.72 N/A

Employ Loader’s M240: First Hit (seconds)

M 35 20.74 19.75

F – M 67.99%

F 13 34.85 28.42

Employ Loader’s M240: Reload (seconds)

M 47 45.43 16.40

F – M -13.17%

F 18 39.44 15.11

Reload Commander’s Weapon Station M 46 1.30 0.57 F – M 21.60%
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Task and Metric Integration 

Level

Sample 

Size Mean SD % Difference

(M48) (minutes) F 18 1.58 0.92

Table I B - Analysis of Variance and Welch’s T-test

Task and Metric F statistic 

(df)

F Test

P-value Comparison Difference % Diff.

T-Test 

P-Value

one-sided

(two-sided) 

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Load and Arm Main Gun 10.18

(1, 128)

< 

0.01* F - M 1.00 15.51% < 0.01*

(0.01*) 0.52 1.48 0.38 1.62

Prep Commander’s Weapon 

Station

0.00

(1, 127) 0.98 F - M 0.53 11.56% 0.49

(0.98) 0.02 1.04 -0.13 1.20

Conduct Crew Evacuation 0.50

(1, 63) 0.48 LD - C -0.88 -2.38% 0.24

(0.48) -2.50 0.74 -2.97 1.21

Transfer Ammunition 2.73

(1, 69) 0.10 F - M 1.19 14.80 0.06*

(0.12) 0.22 2.16 -0.07 2.45

Employ Loader’s M240: 

First Hit† 

3.78

(1, 46) 0.06* F - M 14.11 67.99% 0.09* 

(0.17) † 0.00† 26.00† -1.00† 33.00†

Employ Loader’s M240: 

Reload 

1.80

(1, 63) 0.18 F - M -5.99 -13.17 0.09*

(0.17) -11.59 -0.37 -13.24 1.28

Reload Commander’s 

Weapon Station (M2) 

2.17

(1, 62) 0.15 F - M 0.28 21.60% 0.12

(0.24) -0.03 0.59 -0.12 0.68

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the metric’s mean values for 

the Integration Level according to ANOVA or an equivalent nonparametric test. 

†Due to lack of normality, p-values and confidence intervals have been replaced with Mann-Whitney Test results.

Section 2: Additional Task Results:

Load and Arm Main Gun. An essential skill for all tank crewmen is the ability to rapidly 

reload the tank’s main gun. During this task, the Tank Loader was required to retrieve a

53 pound dummy round from a storage compartment approximately three to five feet off 

the ground, flip the round over, and loading it into the breach on a stationary vehicle. 

The dummy rounds used in this task were inert rubber and steel training replicas of the 

120mm M830 High-Explosive Anti-Tank (HEAT) multipurpose round. The dummy 

rounds are identical in size, shape, weight, and weight distribution to service 

ammunition rounds. Due to the individual nature of this task the method of comparison 

looked at performance differences between crews grouped by the gender of the Marine

performing the task. Data collectors began recording time when the loader received the 

command to reload and stopped when the round was loaded and the main gun armed. 

For this task, group sample sizes are sufficiently large (n ≥ 30) to satisfy normality 

assumptions for ANOVA. Additionally, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA. Male loaders performed the task in 

a mean time of 6.45 seconds compared to female loaders with a mean time of 7.45 

seconds. On average, the male loaders executed the task 15.51% faster than the 
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female loaders. A two-sided t-test yields a p-value of 0.01, meaning the performance 

difference between genders is statistically significant. Males performed the task an 

average of 1 second faster than females. 

• Contextual Comments. Combat operations faster reload times (even measured 

in fractions of a second) are highly desirable. Because the rate of fire is primarily 

limited by the speed at which the loader can manually reload the main gun, 

reloading speed has a significant impact on the crew’s combat effectiveness and 

survivability. Although this task is primarily the loader’s responsibility, the 

potential for combat losses requires all crewmen to be capable of performing the 

task. Doctrinal standards prescribed by FM 3-20.21, the Heavy Brigade Combat 

Team Gunnery Manual, require each crewmember to demonstrate the ability to 

reload the main gun in 7.00 seconds or less on a stationary vehicle. On average, 

the female loaders did not meet the standard established by the reference. 

Numerous near-peer competitor platforms utilize autoloading systems that offer 

ever increasing reload speeds. With the service life of the M1A1 projected to 

extend to 2050, selecting tank crewmen who are able to quickly reload the main 

gun plays a significant role in maintaining the competitiveness of the platform.

Prepare Commander’s Weapon Station. The most physically challenging crew 

station to set up is the tank commander’s weapon station. This task requires the 

crewman to lift the M48 .50 caliber machine gun from the ground up to the top of the 

tank, mount the weapon in the cradle, set the headspace and timing, and perform a 

functions check on the weapon. All crewmembers must be capable of performing this 

procedure to be assigned as a tank commander. Additionally, FM 3-20.21 requires each 

crewmember to demonstrate proficiency in assembling, setting headspace and timing, 

and performing a functions check on the M48. The time starts when the crewman 

performing the task is given the command to begin and stops when the installation is 

complete. This task is an individual event; the other crewmembers are unable to 

influence the performance of the task. For this reason, the data collected from this task 

was analyzed according to the gender of the Marine performing the task rather than 

according the to the integration level of the crew.

For this task, group sample sizes are sufficiently large (n ≥ 30) to satisfy normality 

assumptions for ANOVA. Additionally, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA. The Males (M) performed the task 

in a mean time of 4.59 minutes, while females (F) had a mean time of 5.12 minutes. On 

average males executed the task 11.56% faster than females, with a statistically 

significant p-value of 0.09. The male group performed the task an average of 31.8 

seconds faster than the female group.

• Contextual Comments. This task, as scripted for the experiment, is unlikely to 

be performed while in contact with the enemy because it is by nature a 
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preparatory task. However, various components of this task could be required to 

troubleshoot and correct a malfunction that occurs while employing the weapon 

in a combat situation. Additionally, removing/installing and 

disassembling/assembling the weapon for cleaning and inspection are required 

components of before and after operations maintenance procedures.

Crew Evacuation. The crew evacuation task required the entire crew to rapidly exit 

their stations and move to a rally point 50 meters behind the vehicle. It was performed 

with all crewmembers starting in their crew stations with safety guards installed and 

hatches closed and locked. The physically demanding aspects of this task include lifting

a 40 to 65 pound crew compartment hatch up and away from the crewmen on a hinge, 

climbing down off the tank, and sprinting 50 meters. The time starts when the Tank 

Commander gives the command to evacuate and stops when the last crewman reaches

the rally point. 

For this task, group sample sizes are sufficiently large (n ≥ 30) to satisfy normality 

assumptions for ANOVA. Additionally, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA. On average, the C group 

performed the task 2.38% slower than an integrated crew. The C group performed the 

task in a mean time of 37.03 seconds, while the LD group had a mean time of 36.15 

seconds. No statistical significant difference is present between the C and LD groups. 

• Contextual Comments. A combat loaded M1A1 contains over five hundred 

gallons of highly flammable fuel and hydraulic fluid, and over two thousand 

pounds of explosive ordinance. In the event of a fire or similar emergency, the 

survivability of the crew is dependent on their ability to evacuate the tank quickly. 

Conduct Ammunition Resupply Overview. This task was originally designed to 

evaluate the tank crew’s performance in uploading a full complement of ammunition 

onto the vehicle from a field ammunition supply point. Unfortunately, the way that the 

task was performed did not present a meaningful opportunity to determine whether a 

performance difference exists between the C and LD groups. 

The standard operating procedure developed by the test unit required the Gunner (a 

non-rotating, male volunteer) to perform the vast majority of the physical work. The 

Gunner was responsible for removing the main gun rounds from their storage 

containers, carrying them approximately 20 meters to the tank, and lifting the rounds up 

to the other crewmen onboard the tank. After the Gunner delivered each round to the 

tank, the driver and loader were responsible for storing it inside the turret. In addition to 

the gunner performing the most challenging components of the task, this method also 

prevented the loader and driver from working continuously. Because the gunner’s role in 

the retrieval and storage of each round took the greatest amount of time, the elapsed 

time primarily measures the gunner’s performance and was not significantly influenced 

by the performance of the other crewmen. For these reasons, this report cannot provide 
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a meaningful comparison of the performance of all-male and integrated crews in 

completing this task. 

Transfer Ammunition. The M1A1 has two useable storage compartments for main 

gun ammunition: the ready ammunition storage compartment from which the rounds are 

withdrawn to be fired, and the semi-ready ammunition storage compartment which 

stores additional rounds but is much less accessible. When the ready ammunition 

storage compartment is low on ammunition the crew transfers more ammunition into it 

from the semi-ready ammunition storage compartment. This task evaluated the crew’s 

ability to perform this procedure by measuring the total time required for the crew to 

transfer 16 main gun rounds between storage compartments. The time started when the 

tank commander gave the order to begin and ended when all 16 rounds had been 

transferred and both storage compartment doors were secured. All of the main gun 

engagements in the assessment utilized the 52.8 pound M831A, a training replica of the 

M830 High-Explosive Anti-Tank (HEAT) multipurpose round. This task was performed 

entirely by the loader and tank commander without assistance from the other two 

crewmen. All the tank commanders in the experiment were direct assignment male 

Marines. For this reason, the data collected from this task was analyzed according to 

the gender of the Marine serving as the loader. 

For this task, the M group data are not normally distributed as evidenced by a ShapiroWilk Test p-value of less than 0.01, while the F group data are normally distributed with 

Shapiro-Wilk p-value of 0.04. We recommending using the ANOVA results presented 

above which are confirmed by a Mann-Whitney Test (p-value = 0.10). Additionally, 

group standard deviations are sufficiently similar to satisfy the equal variance 

assumption for ANOVA.

Male loaders (M) performed the task in a mean time of 8.04 minutes while female 

loaders (F) performed it in a mean time of 9.23 minutes. On average, a male loader is 

14.80% faster than a female loader in performing this task. Male loaders performed this 

task an average of one minute and eleven seconds faster than female loaders.

• Contextual Comments. In a combat situation, a tank crew is required to 

perform this task after expending approximately half of their stored ammunition. 

The amount of time required to transfer ammunition determines how quickly the 

crew can resume engaging targets. Additionally, this task provides insight into 

similar tasks ammunition handling tasks that are common to the 1812 MOS. 

Uploading ammunition onto the tank and redistributing ammunition between 

tanks are common tasks which place similar physical demands on the tank 

crewmen. These tasks may, or may not, be performed under time critical 

conditions. Whether the performance difference between groups is operationally 

significant is entirely dependent on the specific tactical situation.
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Employ Loader’s M240. This was the second live-fire engagement. The loader’s 

weapons system was a M240 medium machine-gun pintle-mounted adjacent to the 

loader’s hatch. The Loader’s M240 is primarily used for close defense of the tank. This 

task required the loader to engage a group of four man-sized targets at a range of 250 

meters, pausing to reload the weapon during the engagement. The targets were set to 

continuously reappear so that the loader would run out of ammunition and be forced to 

conduct the reloading portion of the task. Three metrics were evaluated during this 

engagement: the number of trials in which the loader was able to achieve effects on 

target, the time to first effects on target (if effects occurred), and the time required to 

reload the weapon. The time to first effects on target was calculated by collecting time 

hacks when the targets first appeared and when a target recorded the first hit. The 

reload time was based on time hacks recorded when the loader ran out of ammunition 

and again when the loader resumed engaging the target. 

The task was performed as an individual event; the loader’s performance on this task 

was in no way dependent on other crewmembers. For this reason, performance 

comparisons are made based on the gender of the loader rather than by crew 

integration level. In assessing effects on target, males (M) achieved a hit 78% of the 

time, while females (F) hit the target 72% of the time. 

For time to first hit, the M group data are not normally distributed as evidenced by a 

Shapiro-Wilk Test p-value of less than 0.01, while the F group data are normally 

distributed with Shapiro-Wilk p-value of 0.02. Additionally, group standard deviations are 

sufficiently similar to satisfy the equal variance assumption for ANOVA, however, due to 

lack of normality, we recommend using the results of the Mann-Whitney Test presented 

in Table I-B. 

Regarding the length of time required hitting the target (with the sample size only 

including those trials where a hit did occur), male loaders (M) hit the target in a mean 

time of 20.74 seconds, while female loaders (F) hit the target in a mean time of 34.85 

seconds. On average, males were 67.99% faster than females. A one-sided t-test for 

this task yields a p-value of 0.06. A male loader can be expected to achieve effects on 

target an average of 14.11 seconds faster than a female loader. 

For time to reload, the M group data are not normally distributed as evidenced by a 

Shapiro-Wilk Test p-value of less than 0.01, while the F group data are normally 

distributed with Shapiro-Wilk p-value of 0.26. We recommending using the ANOVA 

results presented above which are confirmed by a Mann-Whitney Test (p-value = 0.30). 

Additionally, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA.

In assessing the third component of this task, reloading the M240, male loaders (M) 

performed the task in a mean time of 45.43 seconds while female loaders (F) had a 

mean time of 39.44 seconds. On average, females were 13.17%, or 5.99 seconds, 
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faster than males in reloading the M240. A one-sided t-test for this task yields a p-value 

of 0.09, and a two-sided t-test yields a p-value of 0.17. A female loader can be 

expected to reload the M240 an average of 5.99 seconds faster than a male loader. 

• Contextual Comments. The loader’s M240 is primarily used to provide close 

range defense of the tank against lightly armored or dismounted threats such as 

an anti-tank missile team or a vehicle-borne improvised explosive device. In this 

context, it is extremely important for the loader to quickly achieve effects on 

target. 

Additionally, it is important to note that the loader’s M240 on a M1A1 takes a 

great deal of physical strength to employ accurately. Unlike the common M240B 

variant, the loader’s M240 has duel spade grips and a butterfly trigger instead of 

a buttstock and pistol grip. It is also pintle-mounted on a skate ring with no bipods 

for support. While these modifications greatly increase the quick maneuverability 

of the weapon and enable the loader to cover a 180 degree sector of fire, they 

also necessitate the application of a significant amount of force to keep the 

weapon on target while firing. A loader unable to apply sufficient force to the 

weapon during employment will have difficulty hitting the target. 

Reload Commander’s Weapon Station. The third engagement took place from a 

stationary position and required the loader to reload the commander’s M48 heavy 

machine gun overhead with minimal exposure outside the protective armor of the tank. 

Performance evaluation was based on the total time required to conduct the reload. 

The task began when the tank commander ran out of ammunition while engaging a 

target. The loader removed the empty ammunition can, locked a full ammunition can in 

place, and fed the rounds into the weapon. A starting time hack was recorded when the 

tank commander gave the order to “reload” and an ending time hack was recorded 

when the tank commander resumed engaging the target. The task was performed as 

an individual event; the loader’s performance on this task was in no way dependent on 

other crewmember’s performance. For this reason, performance comparison was made 

by gender rather than by crew integration level. 

For this task, both the M and F group data are not normally distributed as evidenced by 

Shapiro-Wilk Test p-values of less than 0.01. We recommending using the ANOVA 

results presented above which are confirmed by a Mann-Whitney Test (p-value = 0.62). 

Additionally, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA.

Male loaders (M) performed the task in a mean time of 1.30 minutes while female 

loaders (F) performed the task in a mean time of 1.58 minutes. On average, male 

loaders were 21.60% faster than female loaders. Due to the high degree of variance in 
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the data produced by each group, the results cannot be considered statistically 

significant. 

• Contextual Comments. Although the commander weapon station is fired from 

inside the crew compartment, the weapon itself is mounted on top of the tank 

without any armor protection. In order to reload the weapon, the Loader must 

lean out the loaders hatch exposing part of the body (normally the head, 

shoulders, and arms) outside the protective armor of the tank. Because this is 

inherently dangerous in a combat environment, the challenge is to perform the 

task while keeping as much of the body inside the tank as possible. This means 

lifting the 30-lb ammunition can overhead to feed the rounds and lock it in place. 
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Annex J. 

AAV Crewman (MOS 1833) 

This annex details the Assault Amphibious Vehicle (AAV) Crewman (MOS 1833) portion 

of the Ground Combat Element Integrated Task Force (GCEITF) experiment executed 

from 3 March – 26 April 2015 at Range 500, aboard the Marine Corps Air Ground 

Combat Center (MCAGCC), Twentynine Palms, CA. The sections outline the AAV 

Crewman Scheme of Maneuver, Limitations, Deviations, Data Set Description, 

Descriptive and Basic Inferential Statistics, and Modeling Results. 

J.1 Scheme of Maneuver

J.1.1 Experimental Cycle Overview

The AAV portion of the GCEITF Experiment was executed from 3 March to 26 April 

2015 at Range 500, aboard the MCAGCC, Twentynine Palms, CA. The second portion 

of the experiment for AAVs took place from 9 May to 18 May 2015 at Assault Craft Unit 

FIVE (ACU-5) and Training Area Red Beach aboard CAMPEN, CA. The AAV 

experiment was originally scheduled to commence record trials on 9 March 2015 and 

continue until 1 May 2015, with makeup days through 11 May 2015 at Range 500. The

amphibious record trials were scheduled to commence on 18 May 2015 and continue 

until 1 June 2015, with makeup days inclusive in those dates. This timeline included 2 

pilot trial cycles, 16 record trial cycles, and 3 makeup trial cycles. The pilot trials at 29 

Palms were conducted as planned from 3-6 March 2015, while 16 record trial cycles 

were conducted from 9 March through 26 April 2015, vice 1 May 2015 as originally 

planned. A range maintenance day was conducted every four cycles (12 days) to allow 

contractor support to conduct range upkeep. This also allowed volunteers to receive 

one recovery day at Camp Wilson. The CAMPEN experimental trials were conducted 

from 9-18 May 2015. Each evaluated subtask in both phases was considered the most 

physically demanding and operationally relevant tasks that an 1833 AAV crewman is 

expected to perform. An 1833 AAV crew is made up of three Marines: a Rear 

Crewman, Driver, and Turret Gunner. 

J.1.2 Experimental Details

The GCEITF volunteers of the AAV experiment executed a variety of subtasks over the 

course of a 3-day trial cycle at the MCAGCC in Twentynine Palms, CA and a 1-day 

cycle at Camp Pendleton (CAMPEN), CA. The first day of the 3-day cycle at the 

MCAGCC consisted of live-fire evaluated subtasks divided into three categories: a 

modified gun table V, combat-simulated interior reload, and a combat-simulated exterior 

reload. The second day of the trial cycle consisted of non-evaluated maintenance tasks 
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meant to keep the vehicles and equipment combat ready executing subsequent trial 

cycles. The third day consisted of non-live-fire evaluated subtasks divided into three 

categories: conducting maintenance actions, loading weapons and ammunition, and 

conducting CASEVACs. The 1-day cycle subtasks at CAMPEN were divided into two 

categories: CASEVACs conducted in an amphibious environment, and water and land 

towing operations. There were no breaks in the record trials at CAMPEN. Initial 

Fatigue surveys were given to each volunteer at the beginning of each experimental 

day, followed by a final Fatigue survey at the completion of that particular day’s tasks. 

Workload surveys were administered at the completion of a particular day’s tasks. 

Lastly, volunteers completed cohesion surveys at the end of each trial cycle. 

J.1.3 Additional Context

Marines wore a standard vehicle fighting load while conducti.ng all subtasks. This 

included a CVC protective suit, an IPC with SAPI plates, a Kevlar or CVC helmet, and 

an M4 Carbine. This gear weighed approximately 35 lb. The Marines bivouacked at a 

platoon position in the vicinity of the AAVs. All volunteers not randomly selected to 

participate on a particular day’s trials conducted tasks outside the assessed events to 

provide realistic loading. These tasks were equivalency tasks to ensure equity between 

individuals participating in a trial cycle and those not chosen via random selection. 

These tasks are discussed in detail in the loading section below. 

Baseline and Post-Trial Fatigue surveys were administered to the volunteers before the 

beginning of the first trial and after the end of the last trial. These surveys were 

designed to capture the volunteers’ cumulative fatigue level at the beginning and end of 

each day’s trials. The data collected provide additional insight into apparent aberrations 

in the performance level of a given volunteer on a specific day. It allows for outside 

fatigue-related factors (minor illness, lack of sleep the night before, etc.) to be 

accounted for in the analysis of the performance data. Additionally, all volunteers 

completed Workload surveys at the completion of each day’s trials. These surveys 

collected the volunteers’ perceived average and maximal level of exertion during the 

performance of the day’s trials. Lastly, all volunteers completed Crew Cohesion 

Surveys at the conclusion of each cycle. These surveys provided a method of collecting 

subjective data relating to each AAV crew’s ability to work as a team.

J.1.4 Scheme of Maneuver Experimental Tasks

J.1.4.1 Conduct Modified Gun Table V and Simulated Reloads

The AAV live-fire trial day consisted of three separate subtasks: conduct a modified 

gun table V, conduct a combat-simulated interior reload, and conduct a combatsimulated exterior reload. Prior to the start of the subtasks, each vehicle crewman 
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completed a baseline fatigue survey. All subtasks were conducted as a crew event, 

with an AAVP7A1 crew of a Driver, Rear Crewman, and Turret Gunner. 

J.1.4.1.1 Conduct a modified Gun Table V

The AAV crews were required to engage multiple targets ranging from 400 to 1500 m 

from their positions, distances and exposure times dictated by the US Army Heavy 

Brigade Combat Team Gunnery Manual. The Marines wore fighting loads and

conducted four separate engagements: one offensive and three defensive, and 

engaged 12 vehicle or troop targets. 

J.1.4.1.2 Conduct Interior Reload

This event required the AAV Turret Gunner and Rear Crewman to conduct a reload of 

200 rounds of .50-caliber ammunition and 64 rounds of 40-mm grenade rounds. The 

Rear Crewman assisted the Turret Gunner by moving boxes of ammunition from the 

appropriate troop-compartment stowage spaces and handing them to the Turret 

Gunner, who sat in the vehicle turret. This task was executed twice during the course of 

fire and simulated the requirement for the Rear Crewman to assist the Turret Gunner 

with the reloading of both weapons systems within the turret of the AAV. 

J.1.4.1.3 Conduct External Reload

This event required the AAV Turret Gunner and Rear Crewman to conduct a reload of 

200 rounds of .50-caliber ammunition and 96 rounds of 40-mm grenade rounds. A 

loaded can of .50-caliber ammunition weighs approximately 35 lb. and a loaded can of 

40-mm grenade rounds weighs approximately 45 lb. The Rear Crewman assisted the 

Turret Gunner by moving boxes of ammunition from the appropriate troop-compartment 

stowage spaces to the top of the vehicle and into the turret from the exterior. This task 

was executed once during the course of fire and simulated the requirement for the Rear 

Crewman to assist the Turret Gunner with the reloading of both weapons systems from 

the exterior of the AAV.

J.1.4.2 Conduct Maintenance Actions

The AAV non-live-fire trial day consisted of three separate subtasks: conduct 

maintenance actions, load weapons and ammunition, and conduct simulated 

CASEVACs. Prior to the start of the subtasks, each vehicle crewman completed a 

baseline fatigue survey. All subtasks were conducted as a crew event, with an 

AAVP7A1 crew of a Driver, Rear Crewman, and Turret Gunner. 

J.1.4.2.1 Break and Reassemble Track

This subtask required the AAV crew to use the vehicle SL-3 and to break track at the 

rear of the vehicle. The crews then moved the vehicle forward until the broken track 
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was at the mid-point of the AAV at the dual support roller. The vehicle was then placed 

in reverse and moved back until the crew was able put the track back together. Upon 

completion of the setup, an AAV Platoon Staff member inspected the vehicle to ensure 

proper reassembly and the crew had followed all necessary safety requirements. Upon 

verification, the crew stowed all materials used and moved the vehicle approximately 20 

meters to a marked point, signaling completion of the subtask. The crew had 90 

minutes to accomplish this task. This task simulated multiple possible suspension and 

vehicle track issues that could arise during the course of operations. An initial Fatigue 

survey was given to each volunteer prior to the beginning of this task.

J.1.4.2.2 Conduct a Manual Ramp Raise

This subtask required the AAV crew to raise the AAV ramp, manually, with a ramp jack. 

The crews did not have responsibilities dictated for this task and were allowed to 

conduct the task as they saw fit until completion. Upon completion, an AAV Platoon 

Staff member inspected the ramp to ensure it had been properly secured. There was 

no maximum time limit for this task. 

J.1.4.3 Load Weapons and Ammunition

The vehicle crew loaded the M2 .50-caliber machine gun, the MK-19 40-mm grenade 

launcher, and a full complement of ammunition (two cans of .50-caliber ammunition and 

three cans of 40-mm grenades) from the lowered ramp of the AAV. The crew was 

required to execute this task from the exterior of the vehicle. An interior loading of the 

fully assembled M2 was authorized. A fully assembled M2 weighs approximately 85 

lbs. and the MK-19 weighs approximately 79 lb. Upon completion, an AAV Platoon 

Staff member inspected to ensure correct installation of the weapons. There was no 

maximum time limit for this task. This task simulated the AAV crew loading weapons 

and ammunition from various positions on the vehicle.

J.1.4.3.1 Conduct Manual Turret Manipulation

This subtask required the AAV Turret Gunner, without assistance, to manually traverse, 

elevate, and depress the vehicle turret. The Turret Gunner used the manual traverse 

and elevation controls within the turret. The Turret Gunner manually maximized

elevate, maximized depress, and then traversed the turret 360 degrees. A data 

collector captured the total elapsed time; there was no maximum time limit. This task 

simulated the requirement of a Turret Gunner to manipulate the turret, manually, 

scanning and engaging targets.

J.1.4.3.2 Conduct CASEVAC of an Incapacitated Turret Gunner

This subtask required the Rear Crewman and Driver to evacuate a simulated casualty 

from the turret of the AAV, externally and internally. The simulated casualty was a 
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dummy wearing the appropriate vehicle crewman fighting load weighing approximately 

205 lb. The Rear Crewman performed each evacuation alone for the first 60 seconds 

while the Driver radioed a simulated CASEVAC 9-line report. If the dummy was not 

evacuated by the 60-second mark, the Driver assisted. The Driver and Rear Crewman 

then attempted to execute the evacuation until the 6-minute mark. The Turret Gunner 

then assisted between the 6-minute mark and the time limit of 9 minutes. Once the 

dummy was placed on top of the vehicle for the exterior evacuation or on the floor of the 

troop compartment for the interior evacuation, the data collector recorded a stop time. 

The data collector was responsible for verifying the dummy had not sustained additional 

head injuries during the evacuation using an accelerometer check light fastened to the 

head of the dummy. The three choices signaled by the check light were green, yellow, 

and red. A red check light meant the casualty sustained significant head injury during 

the casualty evacuation, a yellow light signaled additional head injury but not life 

threatening, and a green light signaled no injury. This task simulated a crew conducting 

a CASEVAC from the turret and is a training and readiness requirement for 1833s. A 

final fatigue survey was conducted at the end of this non-live fire day task. A workload 

survey was also administered immediately following this task to measure the average 

and maximum workload experienced by each volunteer. 

J.1.5 Conduct Amphibious Operations

The AAV Amphibious trials conducted aboard CAMPEN, CA consisted of 1- day cycle 

consisting of three separate subtasks: conduct a secure and unsecure of an AAVP7A1, 

conduct an evacuation of an incapacitated Rear Crewman at sea, and perform recovery 

operations. All subtasks were conducted as a crew event, with an AAVP7A1 crew of a 

Driver, Rear Crewman, and Turret Gunner. 

J.1.5.1 Conduct a Secure and Unsecure of an AAVP7A1

This subtask required the AAV Crew to secure and unsecure an AAV to a Landing 

Craft, Air Cushioned (LCAC). The crew secured the AAV with eight sets of chains and 

dogging brackets, then unsecured the AAV and returned the chains and dogging 

brackets to their appropriate stowage areas. A data collector captured separate start 

and stop times for secure and unsecure. There was no maximum time associated with 

this task. This task simulated an AAV crew securing and unsecuring a vehicle in 

preparation to debark from Navy Amphibious shipping. An initial Fatigue survey was 

given to each volunteer prior to the beginning of this task. 

J.1.5.2 Conduct Water Evacuation of an Incapacitated Rear Crewman

This subtask required the AAV Turret Gunner and Driver to lift a simulated casualty from 

the floor of the troop compartment to the top of the vehicle through the starboard right 

cargo hatch. The casualty was simulated by a 205-lb dummy. The Turret Gunner and 
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Driver had 25 minutes to accomplish this task. This task is a training and readiness 

requirement for 1833s and simulated conducting a CASEVAC from the troop 

compartment of the vehicle.

J.1.5.3 Perform Recovery Operations

This subtask required the AAV crew to conduct a water and land recovery of a 

simulated disabled AAV. The crews of the recovery and disabled AAVs worked 

together for each portion of the recoveries. The water recovery required the Turret 

Gunner and the Rear Crewman from each vehicle to throw water-tow ropes to the 

recovery vehicle or use a boat hook to secure the thrown ropes. The crews then 

connected both vehicles stern-to-stern and towed the disabled vehicle in the water. The 

data collector recorded a stop time upon commencement of the tow. The land tow 

required both crews to manipulate the two vehicles and the land tow bar weighing 

approximately 150 lbs. and attach it to two points on the disabled vehicle. The 

operational vehicle then backed up until the tow pintle seated properly. Once the 

vehicle was attached, both crews loaded into the recovery vehicle and the recovery 

vehicle began to tow. The data collector captured the stop time when the recovery 

vehicle had towed the disabled vehicle 125 ft. up the beach to a designated area. Upon 

completion of each tow, the crews swapped roles and executed the recovery again. 

There was no maximum time limit for this subtask. The water and land tow tasks are 

requirements outlined by the training and readiness manual and are somewhat likely to 

occur during normal operations on land and in the water. A final fatigue survey was 

conducted at the end of this day’s task. A workload survey was also administered 

immediately following this task to measure the average and maximum workload 

experienced by each volunteer. 

J.1.6 Loading Events

Loading events ensured, to the greatest extent possible, equity of physical activity 

amongst all volunteers and attempted to simulate the intense physical and mental 

workload present in combat or in a combat-focused training environment. Loading 

activities included nightly security and observation posts, maintenance actions, and 

execution of all subtasks. The first enduring task was turret watch, held by all Marines 

scheduled to participate in the following days’ trials and consisting of 2 hours of watch. 

This watch only occurred on nights prior to assessing events. Maintenance day, also 

known as PMCS, included maintaining winch cables and resetting any gear stowed 

incorrectly during evaluations. Major maintenance actions were performed during the 

maintenance day. At the end of the established 12-day cycle, crews conducted lube 

orders on their vehicle prior to movement back to Camp Wilson. The day spent at 

Camp Wilson was also a range maintenance day where contractors performed repairs 
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or maintenance on all targets. Weekly maintenance checks and services were 

conducted every other PMCS day.

J.1.7 Loading Challenges

There were multiple challenges enacting a loading plan that effectively simulated the 

physical and mental difficulties of combat or a combat-training environment. The 

foremost problem was the mindset of the volunteers. When executing subtasks during 

loading trials, Marines moved slower or exerted less effort knowing their trial would not 

be a matter of formal data collection efforts. Concerns for troop welfare and morale 

support led to decisions that allowed Marines to bivouac in a covered administrative 

position every maintenance day during a trial rather than maintain a tactical posture on 

their vehicles over the course of multiple trials. This administrative posture alleviated 

the cumulative effect that fatigue has on Marines in a tactical environment. 

J.1.8 Scheme of Maneuver Summary

The AAV Experiment consisted of a 3-day trial cycle consisting of live-fire, maintenance, 

and non-live-fire days in Twentynine Palms and a 1-day trial cycle at CAMPEN. During 

the course of the experiment, the AAV platoon executed 2 pilot trial cycles and 16 

record trial cycles at the MCAGCC, and 1 pilot trial cycle and 9 record trial cycles at 

CAMPEN. During trial execution, Marines wore a standard vehicle fighting load, which 

weighed approximately 35 lbs., while conducting all subtasks. When not participating in 

a trial, Marines executed all subtasks to ensure equivalency loading amongst 

volunteers. Knowing their efforts were not being directly observed and recorded did not 

ensure equivalency of effort by participants. Additional physical loading included watch 

rotations, vehicle maintenance, and a vehicle bivouac site. A rotation into an 

administrative posture every maintenance day alleviated the cumulative effect that 

fatigue has on Marines in a tactical environment. 

J.2 Limitations

J.2.1 Limitations Overview

The GCEITF experiment was designed to allow operationally relevant tasks to occur as 

naturally as possible, while gathering unbiased measurements. Most tasks were 

performed in a similar manner to those in an operational environment; however, artificial 

limitations or interruptions were introduced that changed or altered the normal 

performance of a task. While these limitations represent a degree of artificiality, they do 

not detract significantly from the data collection plan. The following limitations were 

observed for the 1833 AAV Crewman assessment. 
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J.2.2 Number of Volunteer Participant

For the AAV experiment, 17 male and 10 female volunteers began the trials, but by the 

end 16 males and 10 females were able to complete the assessment. The results 

presented in this annex are based on the performance of 27 Marines. 

J.2.3 Experience Inequalities

Volunteers enrolled in the program came from a variety of Marine Corps backgrounds 

and had varying levels of experience in the 1833 MOS. The unit’s pre-experiment 

workup was designed to bring all volunteers to the minimum level of proficiency 

necessary to execute the experiment, and to provide an equivalent level of experience 

in performing the experiment-specific tasks.

Unit workup training prior to the assessment consisted of approximately 20 weeks of 

crew-level training at Marine Corps Base Camp Lejeune, NC. The unit completed 

multiple non-live-fire field training exercises, Gunnery Skills Test qualifications for each 

crewman, and AAV Table I-V crew gunnery. Each volunteer designated to rotate crew 

positions received extensive training in all crew positions. 

J.3 Deviations

Deviations to the execution of the AAV Crewman scheme of maneuver were made; 

however, no deviations that occurred affected the analysis methodology outlined in the 

EAP. 

J.4 Data Set Description

J.4.1 Data Set Overview

The 1833 portion of the experiment at Range 500 consisted of 2 pilot trial cycles and 16 

record trial cycles. The pilot trial cycle was conducted from 3-8 March 2015. Pilot trial

data were not used in analysis due to variations in the conduct of the experiment. All 

analysis was based on the 16 record trial cycles executed from 9 March 2015 to 28 April 

2015. The 1833 Amphibious Operations were conducted at Camp Del Mar aboard 

Camp Pendleton, Ca from 9-18 May 2015. One pilot trial day was conducted on 9 May 

2015. Record trials were executed from 10-18 May 2015. 

J.4.2 Record Test Volunteer Participants

At the beginning of the first record trial, there were 17 male volunteers and 10 female 

volunteers. There was one male DOR during the execution of the experiment. The final 

number of volunteers was 16 males and 10 females. 
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J.4.3 Planned, Executed and Analyzed Trial Cycles

Table J-1 below shows the number of trials planned, executed and analyzed by task for 

the AAV experiment for Twentynine Palms and Camp Pendleton evolutions. The notes 

column provides insight on the delta between the trials analyzed versus trials 

conducted. The data collection process allowed for identification of potential outliers

and invalid data points due to data collector or Toughbook program error, or equipment 

malfunction. For 29 Palms, the AAV experiment began with 8 trials on any given day, 

but changed after the first trial cycle to include 9 trials. This increased the number of 

executed trials for many of the tasks. The decision to increase the daily number of trials 

was made based on the possible loss of data due to forecasted wind delays. Live Fire 

Engagements data was lost because of wind delays that eventually cancelled the trials 

for specific days. The increase of trials from 8 to 9 proved beneficial and maintained the 

goal of reaching the planned number of trials. 

Table J-1. 1833 Planned, Executed and Analyzed Trial Cycles1

Task and 

Metric 

Description

Integration 

Level

Number 

of 

Planned 

Trials

Number of 

Trials 

Conducted

Number 

of Trials 

Used in 

Analysis

Notes

Conduct a 

modified Gun 

Table V

C 74 74 72 Data Collection Errors (2)

LD 76 84 84 

HD 90 88 87 Data Collection Errors (1) 

Conduct 

Interior Reload

(#1 and #2)

C 74 74 74 

LD 76 84 84 

HD 90 74 74 

Conduct 

External Reload

C 37 39 37 Lost data points due to Data Collection Processing 

LD 38 42 42 

HD 45 46 45 Lost data point due to Data Collection Processing 

Break and 

Reassemble 

Track

C 37 38 36 Data Collection Errors (2)

LD 38 42 42

HD 45 46 46

Conduct a 

Manual Ramp 

Raise

C 37 39 38 Lost data point due to Data Collection Processing 

LD 38 42 42

HD 45 46 46

Load Weapons 

and Ammo

C 72 75 75

LD 76 84 83 Data Collection Errors (1) 

HD 90 92 91 Data Collection Errors (1)

Conduct 

Manual Turret 

Manipulation

C 37 38 38

LD 38 42 42

HD 45 46 45 Lost data point due to Data Collection Processing 

Conduct C 74 75 74 Data Collection Error (1)
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Task and 

Metric 

Description

Integration 

Level

Number 

of 

Planned 

Trials

Number of 

Trials 

Conducted

Number 

of Trials 

Used in 

Analysis

Notes

CASEVAC of an 

Incapacitated 

Turret Gunner 

(Internal and 

External)

LD 76 82 82

HD 90 90 89 Data Collection Error (1)

Conduct Land 

Recovery

C 25 22 22

LD 25 23 22 Mechanical Failure (1)

HD 30 27 27

Conduct a 

Secure and 

Unsecure of an 

AAVP7A1

C 50 44 44

LD 50 46 46

HD 60 54 54

Conduct Water 

Casevac

C 25 22 21 Data Collection Error (1)

LD 25 25 23 Data Collection Processing

HD 30 27 19 Data Collection Error (8)

Conduct Water 

Recovery

C 25 25 22 Lost data points due to Data Collection Processing 

LD 25 24 23 Data Collection Error (1)

HD 30 27 27

1. Some data was not captured or captured incorrectly due to human (Data Collector - DC) error or data processing equipment 

(Toughbook - TB) error. Wind delays also caused a loss of data on some occasions. Some data points were classified as 

outliers or potential influential points and were excluded from the analysis as described in the methodology section. 

J.5 Descriptive and Basic Inferential Statistics 

J.5.1 Descriptive Statistics Overview

Performance metrics were measured during the conduct of common AAV Crewman 

tasks and are indicative of unit-level proficiency during either field exercises or combat 

operations. Seven selected tasks are presented in this section. The Appendix to this 

Annex contains the descriptive statistics for the remainder of the tasks. 

This section accounts for various AAV Crew combinations when integrating MOSqualified female Marines with MOS-qualified male Marines. An AAV Crew consists of a 

three-Marine complement per vehicle. The crew positions include Rear Crewman, 

Driver, and Turret Gunner. In a typical crew, the Rear Crewman is the most junior and 

least MOS-experienced Marine. The Driver is the next senior and more MOSexperienced Marine, while the Turret Gunner, also called the Crew Chief, is the most 

senior and MOS-experienced Marine. 

This report will refer to various concentrations of vehicle crews in terms of integration 

levels. A control group (C) refers to an all-male crew filling any combination of the three 

billets; this type of crew was the control for the experiment. The low-density (LD) crew 

was made up of two males and one female filling any combination of the three billets. 

The high-density (HD) crew included one male and two females. The Marines rotated 

through the billets via random selection, without respect to MOS knowledge or 
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experience, in an effort to examine the effects of integration at all crew levels. In 

addition to integration level comparisons, there were certain tasks also analyzed by 

critical billet. A critical billet was identified for tasks where a physically demanding duty 

was primarily performed by one individual. 

This section includes experimental results based on descriptive statistics, analysis of 

variance (ANOVA), Tukey Tests (or non-parametric equivalent as necessary), and 

scatter plots. The first table titled Descriptive Statistics displays the metric, integration 

levels, sample sizes, means and standard deviations. The second table shows ANOVA 

test results including, but not limited to, metrics, p-values suggesting statistical 

significance, integration level elapsed time differences and percentage differences 

between integration levels. If non-parametric tests were needed, the second table 

displays these results instead of ANOVA and Tukey test results. Subsequent 

subsections will cover each task in detail along with scatterplots of the data. If p-values 

are less than the a-priori significance level of 0.10, we conclude that there is statistical 

evidence that the mean elapsed time for the experimental groups, LD and HD, are 

different from the C group. 

Special caution should be taken when comparing similar tasks executed by different 

MOSs within the GCEITF experiment. Comparative analysis may be misleading due to 

differing factors between MOS tasks such as distances, techniques, leadership, load 

carried, group size, and group composition. Lastly, the words “metric” and “task” are 

used interchangeably throughout this Annex. They both refer to the experimental task.

J.5.2 Conduct Interior Reload Overview 

The AAV Turret Gunner and Rear Crewman reloaded 200 rounds of .50-caliber 

ammunition and 64 rounds of 40-mm grenade rounds. The Rear Crewman moved

boxes of ammunition from the appropriate troop compartment stowage spaces and 

handed them to the Turret Gunner, who sat in the vehicle turret. This task was 

executed twice during the course of fire, simulating the requirement for the Rear 

Crewman to assist the Turret Gunner reload both weapons systems within the turret of 

the AAV.

The time began when the Rear Crewman received the command to “reload” from the 

Master Gunner and stopped when the Turret Gunner had completed the interior reload 

and was ready to re-engage targets. The Data Collector was inside the troop 

compartment and recorded start and stop times triggered by the commands from the 

Master Gunner and notifications from the AAV Turret Gunner via vehicle intercom. 

The interior reload occurred twice during the modified Gun Table V course of fire 

derived from the HBCT Gunnery Manual. The data collected for this task was analyzed 

in two ways. The first comparison looked at performance differences by integration 
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level, while the second comparison looked for performance differences by the gender of 

the Marines in two critical billets (Rear Crewman and Turret Gunner). 

J.5.2.1 Conduct Interior Reload #1 by Integration Level

Conducting interior reload is a physically demanding task: the Rear Crewman is moving 

two boxes of .50-caliber ammunition weighing approximately 35 pounds each and two 

boxes of 40-mm ammunition weighing approximately 45 pounds each. The task was 

performed as a crew event, with the AAV Rear Crewman lifting the ammunition 

individually, with the primary measure of performance being the time required to 

complete the task.

J.5.2.1.1 Conduct Interior Reload #1 by Integration Level Scatterplots

The scatter plots below display results for completing the Interior Reload # 1 task by 

integration level. No outliers were identified for this sub-section. 

Figure J-1. Interior Reload #1 by Integration Level

J.5.2.1.2 Conduct Interior Reload #1 by Integration Level Data Table and Analysis

The tables below summarize the results of the task, Interior Reload #1 by Integration 

Level. The first table compares sample sizes and means across metrics and integration 

levels. The second table presents ANOVA and other test results bringing to focus those 

metrics that resulted in statistical significance along with their percentage differences. 
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Table J-2. Interior Reload #1 by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Interior Reload #1 

(minutes)

C 37 4.43 1.37

LD 42 5.32 2.97

HD 46 5.02 1.50

Table J-3. Interior Reload #1 by Integration Level ANOVA and Welch’s Test Results

Metric

F 

Statistic 

(df)

F Test 

PValueComparison Diff % Diff 1- Sided

P-Value

2-Sided 

P-Value

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Interior 

Reload 

#1 

(minutes)

2.46

(2, 76.5)

0.09†

†

LD-C 0.89 20.02% 0.05 0.09 0.07 1.70 -0.09 1.86

HD-C 0.59 13.37% 0.03* 0.06 -0.20 1.39 -0.36 1.55

HD-LD -0.29 -5.54% 0.29 0.57 -1.06 0.47 -1.22 0.63

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances)

For this task, samples sizes are sufficiently large (n>30) to satisfy normality 

assumptions for ANOVA. Since the standard deviation of the LD group is more than 

twice that of the C group, we recommend using the robust ANOVA results presented in 

the table above.

Table J-4 shows the control group averaged faster times than the LD and HD groups. 

Table J-3 shows the LD group was 20.02% slower than the C group; this difference is 

not statistically significant. The HD group was 13.37% slower than the C group; this 

difference is not statistically significant. The HD group was 5.54% faster than the LD 

group; this difference is not statistically significant. 

J.5.2.1.3 Conduct Interior Reload #1 by Integration Level Contextual Comments

In combat operations, faster reload times (even measured in a few seconds) are highly 

desirable. Faster reloading increases the combat effectiveness and survivability of an 

AAV crew. Per the MCWP 3-13, “The AA unit should continue to engage the enemy as 

fast as possible, because fire placed in the enemy’s area will less his effectiveness and 

give friendly weapons time to adjust. A wasted opportunity to engage a target may 

never be regained.” With the service life of the AAVP7 projected to extend to 2035, the 

selection of AAV Rear Crewmen who are able to quickly move boxes of ammunition and 

assist the Turret Gunner effectively plays a significant role in maintaining the 

competitiveness of the platform. 
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J.5.2.2 Conduct Interior Reload #1 by Critical Billet

See Section J.5.2.1 for task description. 

J.5.2.2.1 Conduct Interior Reload #1 by Critical Billet Scatterplots

The scatter plots below display results for completing the Interior Reload # 1 task by 

critical billet. Despite the data point on trial cycle three having a significant higher 

elapsed time, it was determined to be a valid point and was included in the analysis. No 

outliers were identified for this sub-section. 

Figure J-2. Interior Reload #1 by Critical Billet

J.5.2.2.2 Conduct Interior Reload #1 by Critical Billet Data Table and Analysis

The tables below summarize the results of the task, Interior Reload #1 by Critical Billet. 

The first table compares sample sizes and means across metrics and critical billets. The 

second table presents ANOVA and other test results bringing to focus those metrics that 

resulted in statistical significance along with their percentage differences. 

Critical Billet Gender
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Table J-4. Interior Reload #1 by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD 

Interior Reload #1 

(Rear Crewman/Turret Gunner) 

(minutes) * 

MM 51 4.47 1.55

MF 29 5.44 1.86

FM 30 5.04 3.09

FF 15 5.41 1.50

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level.

Table J-5. Interior Reload #1 by Critical Billet ANOVA 

Metric F Statistic 

(df)

F Test 

P-Value Comparison Difference % 

Difference

2-sided 

P-Value

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Interior Reload 

#1 (Rear 

Crewman/Turret 

Gunner) 

(minutes)

5.73

(3, 7.8) 0.02†

MF-MM 0.97 21.70% 0.01* 0.40 1.40 0.28 1.50

FM-MM 0.57 12.84% 0.33 -0.08 0.65 -0.20 0.73

FF-MM 0.94 21.01% 0.01* 0.45 1.42 0.30 1.58

MF-FM 0.40 7.86% 0.10 0.12 1.20 0.00 1.30

FF-MF -0.03 -0.57% 0.87 -0.68 0.70 -0.88 0.92

FF-FM 0.37 7.25% 0.09 0.18 1.22 0.02 1.40

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

†Results presented are from Kruskal-Wallis and Mann-Whitney tests due to lack of normality.

Because of lack of normality, we recommend using the Kruskal-Wallis and MannWhitney test results presented in the table above. Also of note, the standard deviation of 

the FM group is more than twice that of the FF group, however, we continue to 

recommend the Kruskal-Wallis and Mann-Whitney results above since it is more 

conservative than parametric alternatives. For this task, the MF and FF groups are 

normally distributed with Shapiro-Wilk Test p-values of 0.11 and 0.20, respectively, 

while the MM and FM groups are not normally distributed with p-values less than 0.01.

Table J-5 display the Rear Crewman and Turret Gunner billets as a two-letter 

representation, where the first letter represents the gender of the Marine occupying the 

Rear Crewman billet and the second letter represents the gender of the Marine 

occupying the Turret Gunner billet, M for male and F for female. 

The mean time for interior reload #1 was faster when a male occupied the Turret 

Gunner position. The MF and the FF combination performed the interior reload 21.70% 

and 21.01% slower, respectively, than the MM combination. 

The mean time for interior reload #1 was faster when a male occupied the Rear 

Crewman position. The FM combination performed the interior reload 12.84% slower 

than the MM combination.
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The MF combination was 21.7% slower than the MM combination and 7.86% slower 

than the FM combination, both show no statistical significance. The FM combination 

was 12.84% slower than the MM combination: this difference is not statistically 

significant.

J.5.2.2.3 Conduct Interior Reload #1 by Critical Billet Contextual Comments

The Rear Crewman is responsible for the lifting of the boxes of ammunition and 

assisting the Turret Gunner in the reloads. This does not appear to be an experience 

disparity as the Rear Crewman is strictly moving boxes of ammunition up to the Turret 

Gunner. 

In combat operations, faster reload times (even measured in a few seconds) are highly 

desirable. Faster reloading increases the combat effectiveness and survivability of an 

AAV crew. Per the MCWP 3-13, “The AA unit should continue to engage the enemy as 

fast as possible, because fire placed in the enemy’s area will less his effectiveness and 

give friendly weapons time to adjust. A wasted opportunity to engage a target may 

never be regained.” With the service life of the AAVP7 projected to extend to 2035, 

selecting AAV Rear Crewmen who are able to quickly move boxes of ammunition and 

assist the Turret Gunner plays a significant role in maintaining the competitiveness of 

the platform. 

J.5.2.3 Conduct Interior Reload #2 by Integration Level

See Section J.5.2.1 for task description.

J.5.2.3.1 Conduct Interior Reload #2 by Integration Level Scatterplots

The scatterplot below displays the data used in the analysis for the Interior Reload task. 

No outliers were identified. 
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Figure J-3. Interior Reload #2 by Integration Level

J.5.2.3.2 Conduct Interior Reload #2 by Integration Level Data Table and Analysis

The tables below summarize the results of the task, Interior Reload #2 by Integration 

Level. The first table compares sample sizes and means across metrics and integration 

levels. The second table presents ANOVA and other test results bringing to focus those 

metrics that resulted in statistical significance along with their percentage differences. 

Table J-6. Interior Reload #2 by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Interior Reload #2 

(minutes) * 

C 37 4.32 1.72

LD 42 4.41 1.14

HD 44 5.03 1.45

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

Table J-7. Interior Reload #2 by Integration Level ANOVA and Tukey Test Results

Metric F Statistic 

(df)

F Test

 P-Value Comparison Diff % Diff 2-sided 

P-Value

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Interior Reload 

#2 (minutes)

3.01 (2,

120) 0.05*

LD-C 0.10 2.23% 0.95 -0.47 0.66 -0.58 0.77

HD-C 0.71 16.49% 0.07* 0.16 1.27 0.04 1.38

HD-LD 0.62 13.95% 0.12 0.08 1.15 -0.03 1.26

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.
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**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own

For this task, samples sizes are sufficiently large (n>30) to satisfy normality 

assumptions for ANOVA. Additionally, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA.

Table J-6 and Table J-77 show the control group executed the task faster than the LD 

and HD groups. The LD group was 2.23% slower than the C group; this difference is 

not statistically significant. The HD group was 16.49% slower than the C group; this 

difference is statistically significant, while the HD group was 13.95% slower than the LD 

group; this difference is not statistically significant in a Tukey test. 

J.5.2.3.3 Conduct Interior Reload #2 by Integration Level Contextual Comments

In combat operations, faster reload times (even measured in a few seconds) are highly 

desirable. Faster reloading increases the combat effectiveness and survivability of an 

AAV crew. Per the MCWP 3-13, “The AA unit should continue to engage the enemy as 

fast as possible, because fire placed in the enemy’s area will less his effectiveness and 

give friendly weapons time to adjust. A wasted opportunity to engage a target may 

never be regained.” With the service life of the AAVP7 projected to extend to 2035, 

selecting AAV Rear Crewmen who are able to quickly move boxes of ammunition and 

assist the Turret Gunner plays a significant role in maintaining the competitiveness of 

the platform. 

J.5.2.4 Conduct Interior Reload #2 by Critical Billet

See Section J.5.2 for task description. 

J.5.2.4.1 Conduct Interior Reload #2 by Critical Billet Scatterplots

The scatterplot below displays the data used in the analysis for this task. 
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Figure J-4. Interior Reload #2 by Critical Billet

J.5.2.4.2 Conduct Interior Reload #2 by Critical Billet Data Table and Analysis 

The tables below summarize the results of the task, Interior Reload #2 by Critical Billet. 

The first table compares sample sizes and means across metrics and critical billets. The 

second table presents ANOVA and other test results bringing to focus those metrics that 

resulted in statistical significance along with their percentage differences. 

Table J-8. Interior Reload # 2 by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD 

Interior Reload #2 

(Rear Crewman/Turret Gunner) 

(minutes) 

MM 51 4.38 1.62

MF 28 4.85 1.70

FM 29 4.62 1.03

FF 15 4.87 1.12

Table J-9. Interior Reload # 2 by Critical Billet ANOVA and Tukey Test Results

Metric F Statistic 

(df)

F Test

 P-Value Comparison Diff % Diff 2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Interior Reload 

#2 (Rear 

Crewman/Turret 

Gunner (minutes)

0.82 (3, 

119) 0.49

MF-MM 0.47 10.70% 0.53 -0.22 1.15 -0.33 1.27

FM-MM 0.24 5.42% 0.90 -0.44 0.92 -0.55 1.03

FF-MM 0.49 11.21% 0.67 -0.37 1.35 -0.51 1.49

MF-FM 0.23 5.01% 0.93 -0.54 1.00 -0.67 1.13

FF-MF 0.02 0.46% 1.00 -0.91 0.96 -1.07 1.11

FF-FM 0.25 5.50% 0.95 -0.67 1.18 -0.83 1.34

Critical Billet Gender
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Table J-8 and Table J-9 display the Rear Crewman and Turret Gunner billets as a twoletter representation, where the first letter represents the gender of the Marine 

occupying the Rear Crewman billet and the second letter represents the gender of the 

Marine occupying the Turret Gunner billet, M for Male and F for female. 

The MF combination was 10.7% slower than the MM combination and 5.01% slower 

than the FM combination; these differences are not statistically significant. The FM 

combination was 5.42% slower than the MM combination and still not statistically 

significant. See tables above for detailed analytical results.

J.5.2.4.3 Conduct Interior Reload #2 by Critical Billet Contextual Comments

In combat operations, faster reload times (even measured in a few seconds) are highly 

desirable. Faster reloading increases the combat effectiveness and survivability of an 

AAV crew. Per the MCWP 3-13, “The AA unit should continue to engage the enemy as 

fast as possible, because fire placed in the enemy’s area will less his effectiveness and 

give friendly weapons time to adjust. A wasted opportunity to engage a target may 

never be regained.” With the service life of the AAVP7 projected to extend to 2035, 

selecting AAV Rear Crewmen who are able to quickly move boxes of ammunition and 

assist the Turret Gunner plays a significant role in maintaining the competitiveness of 

the platform

J.5.2.5 Conduct External Reload Overview

The AAV Turret Gunner and Rear Crewman conducted a reload of 200 rounds of .50-

caliber ammunition and 96 rounds of 40-mm grenade rounds. A loaded can of .50-

caliber ammunition weighs approximately 35 pounds and a loaded can of 40-mm 

grenade rounds weighs approximately 45 pounds. To assist the Turret Gunner, the 

Rear Crewman moved boxes of ammunition from the appropriate troop compartment 

stowage spaces to the top of the vehicle and into the turret from the exterior. This task 

was executed once during the course of fire. The task simulated the requirement for the 

Rear Crewman to assist the Turret Gunner with reloading weapons systems from the 

exterior of the AAV. The Data Collector was located in the Troop Compartment of the 

AAV and recorded start times based on a verbal command from either the Master 

Gunner via radio or from the AAV Turret Gunner via vehicle intercom. The Data 

Collector recorded stop times when the Turret Gunner notified the entire vehicle that the 

reload was complete via vehicle intercom. We analyzed performance on this task two 

ways: by integration level, as well as by the gender of the Marine occupying the two 

critical billets (Rear Crewman and Turret Gunner).

J.5.2.5.1 Conduct External Reload by Integration Level

An exterior reload is a physically demanding task: in addition to moving the boxes of 

ammunition, it requires the Marine to open and lock the starboard rear cargo hatch, lift 
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the ammunition approximately 6.5 ft., and then pull themselves up to the top of the 

vehicle in a full combat load. The task was performed as a crew event with the AAV 

Rear Crewman lifting the ammunition individually, with the primary measure of 

performance being the time required to complete the task. 

J.5.2.5.2 Conduct External Reload by Integration Level

The scatterplot below displays the data used in the analysis for the external reload task. 

Figure J-5. Exterior Reload by Integration Level

J.5.2.5.3 Conduct External Reload by Integration Level Data Table and Analysis

The tables below summarize the results of the task, Exterior Reload by Integration

Level. The first table compares means across metrics and integration levels. The 

second table presents ANOVA and other test results bringing to focus those metrics that 

resulted in statistical significance along with their percentage differences. 

Table J-20. Exterior Reload by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

External Reload (minutes)* 

C 37 5.45 1.40

LD 42 5.64 1.38

HD 45 6.55 2.20

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level
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Table J-3. Exterior Reload by Integration Level ANOVA and other Test Results

Metric F Statistic 

(df)

F Test

 P-Value Comparison Difference % 

Difference

P-Value 

(onesided)

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

External Reload 

(minutes)

4.94 (2, 

121) 0.01*

LD-C 0.19 3.41% 0.88 -0.49 0.86 -0.62 0.99

HD-C 1.10 20.24% 0.01* 0.44 1.77 0.31 1.90

HD-LD 0.92 16.28% 0.04* 0.28 1.56 0.15 1.69

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own

For this task, samples sizes are sufficiently large (n>30) to satisfy normality 

assumptions for ANOVA. Additionally, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA.

Table J-20 and Table J-31 show the LD group was 3.41% slower than the C group; this

is not statistically significant. The HD group was 20.24% slower than the C group; this

difference is statistically significant in a Tukey test. The HD group was 16.28% slower 

than the LD group; this difference is statistically significant. The control group had a 

mean time of 5.45 minutes, faster than the LD and HD groups, with mean times of 5.64 

and 6.55 minutes, respectively. The HD group was significantly slower than the C and 

LD groups. 

J.5.2.5.4 Conduct External Reload by Integration Level Contextual Comments

Similar to the interior reloads, in combat operations, faster reload times (even measured 

in fractions of a second) are highly desirable. Faster reloading increases the combat 

effectiveness and survivability of an AAV crew. Per the MCWP 3-13, “The AA unit 

should continue to engage the enemy as fast as possible, because fire placed in the 

enemy’s area will less his effectiveness and give friendly weapons time to adjust. A 

wasted opportunity to engage a target may never be regained.” With the service life of 

the AAVP7 projected to extend to 2035, selecting AAV Rear Crewmen who are able to

quickly move boxes of ammunition and assist the Turret Gunner plays a significant role 

in maintaining the competitiveness of the platform. 

J.5.2.6 Conduct External Reload by Critical Billet

See Section J.5.2.5 and J5.2.5.1 for Task Description. 

The scatterplot below displays the data used in the analysis of the external reload by 

critical billet task. 
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Figure J-6. Exterior Reload by Critical Billet

J.5.2.6.1 Conduct External Reload by Critical Billet Data Table and Analysis

The tables below summarize the results of the task, Exterior Reload (Analysis by Critical 

Billet). The first table compares means across metrics and integration levels. The 

second table presents ANOVA and Tukey test results bringing to focus those metrics 

that resulted in statistical significance along with their percentage differences. 

Table J-12. Exterior Reload by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD 

External Reload 

(Rear Crewman/Turret Gunner) 

(minutes)* 

MM 51 5.38 1.45

MF 28 5.85 2.21

FM 30 6.26 1.21

FF 15 7.16 2.25

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

Table J-13. Exterior Reload by Critical Billet ANOVA and Tukey Test Results

Metric F Statistic 

(df)

F Test 

P-Value Comparison Diff % Diff 2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

External Reload 

(Rear 

Crewman/Turret 

Gunner) 

4.72 (3, 

120) < 0.01*

MF-MM 0.47 8.75% 0.65 -0.33 1.27 -0.46 1.40

FM-MM 0.87 16.24% 0.12 0.09 1.65 -0.04 1.79

FF-MM 1.78 33.08% < 0.01* 0.78 2.78 0.62 2.94

Critical Billet Gender
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Metric F Statistic 

(df)

F Test 

P-Value Comparison Diff % Diff 2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

(minutes) MF-FM -0.40 -6.45% 0.81 -1.29 0.49 -1.44 0.64

FF-MF 1.31 22.38% 0.08* 0.22 2.40 0.04 2.58

FF-FM 0.91 14.49% 0.34 -0.17 1.98 -0.35 2.16

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own

We proceed with presenting ANOVA results because they were confirmed by a KruskalWallis test with a p-value of less than 0.01. Additionally, group standard deviations are 

sufficiently similar to satisfy the equal variance assumption for ANOVA. For this task, 

the FM and FF groups are normally distributed with Shapiro-Wilk Test p-values of 0.08 

and 0.30, respectively, while the MM and MF groups are not normally distributed with pvalues less than 0.01.

Table J-12 and Table J-13 display the Rear Crewman and Turret Gunner billets as a 

two-letter representation, where the first letter represents the gender of the Marine 

occupying the Rear Crewman billet and the second letter represents the gender of the 

Marine occupying the Turret Gunner billet, M for Male and F for female. 

The MF combination was 8.75% slower than the MM combination, but 6.45% faster 

than the FM combination. In both cases, the differences are not statistically significant. 

The FF combination was 33.08% slower than the MM combination and 22.38% slower 

than the MF combination. In both cases, the differences are statistically significant. See 

tables above for further detailed analysis among all comparisons. 

J.5.2.6.1.1 Conduct External Reload by Critical Billet Contextual Comments

It was important to identify who was serving in the critical billets of AAV Rear Crewman 

and AAV Turret Gunner to remove the non-participating billet from the analysis. When 

a male served in the Turret Gunner billet for all combinations except one (MF), the task 

was executed faster when compared to other combinations. This may be attributed to 

the experience of the Turret Gunner in taking both weapons systems from Condition 3, 

once the Rear Crewman had finished with the movement of the ammunition cans to the 

top of the vehicle, to Condition 1.

Similar to the interior reloads, in combat operations, faster reload times (even measured 

in fractions of a second) are highly desirable. Faster reloading increases the combat 

effectiveness and survivability of an AAV crew. Per the MCWP 3-13, “The AA unit 

should continue to engage the enemy as fast as possible, because fire placed in the 

enemy’s area will less his effectiveness and give friendly weapons time to adjust. A 

wasted opportunity to engage a target may never be regained.” With the service life of 

the AAVP7 projected to extend to 2035, selecting AAV Rear Crewmen who are able to 
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quickly move boxes of ammunition and assist the Turret Gunner plays a significant role 

in maintaining the competitiveness of the platform. 

J.5.2.7 Break and Reassemble Track Overview

In this Maintenance Action subtask, the AAV crew used the vehicle SL-3 to break the 

vehicle track at the rear of the vehicle. The crews then moved the vehicle forward until 

the broken track was at the mid-point of the AAV at the dual-support roller. The vehicle 

was then placed in reverse and moved back until the crew was able to put the track 

back together. Upon completion of the setup, an AAV Platoon Staff member inspected

the vehicle to ensure it had been properly reassembled and that the crew had followed 

all necessary safety requirements. Upon verification, the crew would then stow all 

materials used and move the vehicle forward 60 feet to a marked point, signaling 

completion of the subtask. The crew had 1 hour and 30 minutes to accomplish this 

task. This task simulates multiple possible suspension and vehicle track issues that 

could arise during the course of operations. We compared task performance by 

integration level of the crew as well as by the gender of the Marines in the two critical 

billets (Rear Crewman and Turret Gunner).

J.5.2.7.1 Break and Reassemble Track by Integration Level

Breaking and reassembling track is a physically demanding task: the AAV crew used 

sledgehammers, tank bars, and other assorted SL-3 to break the 35-lb individual track 

blocks apart before putting them back together. The task was performed as a crew 

event. However, the Driver did not participate in the more physically demanding part of 

the task. 

J.5.2.7.1.1 Break and Reassemble Track by Integration Level Scatterplots

The scatterplot below displays the data used in the analysis of the results of the Break 

and Reassemble Track by integration level task. On trial cycles 5 and 14, two C-group 

data points were removed from analysis due to data entry errors. 
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Figure J-7. Break/Reassemble Track by Integration Level

J.5.2.7.1.2 Break and Reassemble Track by Integration Level Data Table and 

Analysis

The tables below summarize the results of the task, Break and Reassemble Track +by 

Integration Level. The first table compares means across metrics and integration levels. 

The second table presents ANOVA and other test results bringing to focus those 

metrics that resulted in statistical significance along with their percentage differences. 

Table J-14. Break and Reassemble Track by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Break/Reassemble Task 

(minutes)* 

C 36 28.10 9.92

LD 42 29.02 14.50

HD 46 34.42 12.81

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level.

Table J-15. Break and Reassemble Track by Integration Level ANOVA and other Test Results

Metric F Statistic 

(df)

F Test 

P-Value Comparison Diff % Diff 2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Break/Reassemb

le Task (minutes)

3.11 (2, 

121) < 0.05*

LD-C 0.92 3.28% 0.95 -4.05 5.89 -5.05 6.89

HD-C 6.32 22.51% 0.07* 1.46 11.19 0.48 12.17

HD-LD 5.40 18.62% 0.12 0.73 10.07 -0.20 11.01

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level.
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**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own.

For this task, samples sizes are sufficiently large (n>30) to satisfy normality 

assumptions for ANOVA. Additionally, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA.

The HD group was 22.51% slower than the C group; this difference is statistically 

significant. The HD group was 18.62% slower than the LD group and this difference is 

not statistically significant. On average, the control group performed the task faster than 

the LD and HD groups, with a mean time of 28.1 minutes, which was 55 seconds faster 

than the LD-group mean and 6:19 faster than the HD-group mean. The analytical 

results show metric mean values to be statistically significant only when we compare 

the HD and C groups: a 22.51% difference. 

J.5.2.7.1.3 Break and Reassemble Track by Integration Level Contextual 

Comments

However, in a combat environment, it is desirable to fix suspension issues that would 

cause a vehicle to be disabled, quickly, to deny the enemy the opportunity to maneuver 

or employ fires against a stationary AAV. 

J.5.2.7.2 Break and Reassemble Track by Critical Billet

See Section J.5.2.7 and J.5.2.7.1 for task description.

J.5.2.7.3 Break and Reassemble Track by Critical Billet Scatterplots

The scatter plots below display the results to complete the Break and Reassemble 

Track Task by critical billet. On trial cycles 5 and 14, the data points contained inside 

dark black circles were determined to be data errors and were excluded from the 

analysis. 
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Figure J-8. Break/Reassemble Track by Critical Billet

J.5.2.7.4 Break and Reassemble Track by Critical Billet Data Table and Analysis

The tables below summarize the results of the task, Break and Reassemble Track by

Critical Billet. The first table compares means across metrics and integration levels. 

The second table presents ANOVA and other test results bringing to focus those 

metrics that resulted in statistical significance along with their percentage differences. 

Table J-17. Break/Reassemble Track by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD 

Break/Reassemble Task 

(Rear Crewman/Turret Gunner) 

(minutes)* 

MM 50 27.51 10.32

MF 29 30.39 10.89

FM 30 32.04 15.07

FF 15 39.71 15.91

*Indicates there is a statistically significant difference, in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level.

Critical Billet Gender
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Table J-16. Break/Reassemble Track by Critical Billet ANOVA and other Test Results

Metric F Statistic 

(df)

F Test 

P-Value Comparison Difference % 

Difference

2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Break/Reassem

ble Track (Rear 

Crewman/Turret 

Gunner) 

(minutes)

3.82 (3, 

120) 0.01*

MF-MM 2.88 10.46% 0.76 -2.90 8.65 -3.87 9.62

FM-MM 4.52 16.43% 0.40 -1.19 10.24 -2.15 11.19

FF-MM 12.20 44.34% < 0.01* 4.92 19.48 3.69 20.71

MF-FM -1.64 -5.13% 0.96 -8.09 4.80 -9.17 5.88

FF-MF 9.32 30.67% 0.09* 1.45 17.19 0.13 18.51

FF-FM 7.68 23.97% 0.21 -0.15 15.50 -1.46 16.82

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level.

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own

We proceed with presenting ANOVA results because they were confirmed by a KruskalWallis test with a p-value of 0.05. Additionally, group standard deviations are sufficiently 

similar to satisfy the equal variance assumption for ANOVA. For this task, the MF and 

FF groups are normally distributed with Shapiro-Wilk Test p-values of 0.10 and 0.16, 

respectively, while the MM and FM groups are not normally distributed with p-values 

less than 0.01.

Rear Crewman and Turret Gunner billets are represented two-letters, where the first 

letter represents the gender of the Marine occupying the Rear Crewman billet and the 

second letter represents the gender of the Marine occupying the Turret Gunner billet, M 

for Male and F for female. 

All three combinations that included a male (i.e., MM, MF, FM) in one of the critical 

billets had faster break-track times than the all-female combination (FF). When the 

(MM) and (MF) combinations in which the rear crewman was a male were compared to 

the (FF) combination, they showed a significant difference and a much higher statistical 

significance result than other comparative groups. 

Table J-116 and Table J-1617 show that the MF and FM combinations were 10.46%

and 16.43%, respectively, slower when compared to the MM combination; in both 

cases, the differences are not statistically significant. The MF combination was 5.13% 

faster than the FM combination; this difference is not statistically significant. 

The FF combination was 44.34% slower than the MM combination and 30.67% slower 

than the MF combination. In both cases, these differences were statistically significant.

J.5.2.7.5 Break and Reassemble Track by Critical Billet Contextual Comments

This second comparison analyzed the performance differences between crews grouped 

only by the gender of the Marines serving in the critical billets. In this particular task, the 

critical billet’s responsibilities are not scripted (meaning it is a group-effort task shared 
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mostly between the two critical billets vice all three crewmembers). The impact of the 

driver on this metric is considered to be further minimalized because he/she is operating 

the vehicle in strict accordance with the ground guide’s instructions and not operating 

independently nor solely responsible for the movement of the vehicle during this task.

In a combat environment, it is desirable to fix suspension issues that would cause a 

vehicle to be disabled, quickly, to deny the enemy the opportunity to maneuver or 

employ fires against a stationary AAV. The difference demonstrated in this experiment

may have a significant impact during ground combat operations. 

J.5.2.8 Load Weapons and Ammunition Overview 

The vehicle crew loaded the M2 .50-caliber machine gun, the MK-19 40-mm grenade 

launcher, and a full complement of ammunition (two cans of .50-caliber ammunition and 

three cans of 40-mm grenades) from the lowered ramp of the AAV. The crew executed 

this task from the exterior of the vehicle (external mount of M2, MK-19, and Ammo). An 

interior loading of the fully assembled M2 was conducted, as well (see Appendix for 

those results). A fully assembled M2 weighs approximately 85 lb. and the MK-19 

weighs approximately 79 lb. Upon completion, an AAV Platoon Staff member inspected

to ensure the weapons were installed correctly. The Data Collector was located on the 

near the Troop Compartment of the AAV, and initiated this task with a verbal start time, 

recording start and stop times. There was no maximum time limit for this task. This 

task simulated the AAV crew loading weapons and ammunition from various positions 

on the vehicle. The task was performed as a crew event, with the primary measure of 

performance being the time required to complete the task. The data collected from this 

task was analyzed by crew integration only, and not by critical billet, as each Marine in 

the AAV Crew had an active role in execution. 

J.5.2.8.1 External Mount of M2, MK-19, and Ammo Scatterplot 

The scatter plots below display the results to complete the External Mount of M2, MK19, and Ammo task. The data point contained inside the dark black circle was 

determined to be a data error and was excluded from the analysis. 
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Figure J-9. Exterior Mount of M2, MK-19, and Ammo 

 

J.5.2.8.2 External Mount of M2, MK-19, and Ammo Data Table and Analysis

The tables below summarize the results of the task, External Mount of M2, MK-19, and 

Ammo by integration level. The first table compares means across metrics and 

integration levels. The second table presents ANOVA and other test results bringing to 

focus those metrics that resulted in statistical significance along with their percentage

differences. 

Table J-18. External Mount of M2, MK-19, and Ammo

Metric Integration 

Level 

Sample 

Size Mean SD 

Ext Mount of M2 & Mk19 and Ammo 

(minutes)* 

C 37 6.17 2.01

LD 42 7.62 3.25

HD 45 7.92 3.50

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level.

Table J-19. External Mount of M2, MK-19, and Ammo ANOVA and other Test Results

Metric F Statistic 

(df)

F Test 

P-Value Comparison Difference % 

Difference

2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Ext Mount of M2 

& Mk19 and 

Ammo 

(minutes)

3.76 (2, 

121) 0.03*

LD-C 1.46 23.63% 0.09* 0.28 2.64 0.04 2.88

HD-C 1.75 28.43% 0.03* 0.59 2.92 0.36 3.15

HD-LD 0.30 3.88% 0.89 -0.83 1.42 -1.05 1.65

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level.

Integration Level
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**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own

For this task, samples sizes are sufficiently large (n>30) to satisfy normality 

assumptions for ANOVA. Additionally, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA. 

The C group performed the task faster with a mean time of 6:17 minutes when 

compared to the LD and HD groups which were significantly slower than the control 

group. The LD group was 23.63% slower than the C group, while the HD group was 

28.43% slower than the C group. Both differences are statistically significant. 

J.5.2.8.3 External Mount of M2 & MK-19, and Ammo Contextual Comments

Unless under an extreme situation, either in combat or in training, the difference of 

roughly 1.5 to 2 minutes in mounting both weapons systems externally and allocating 

ammunition could be considered negligible. Environments in which crews will be 

expected to perform this task will dictate the level of importance a 2-minute difference 

can make on subsequent AAV actions. 

J.5.2.9 Conduct CASEVAC of an Incapacitated Turret Gunner Overview 

In this task, the Rear Crewman and the Driver evacuated a simulated casualty from the 

turret of the AAV, externally and internally. The simulated casualty was a dummy 

wearing the appropriate vehicle crewman fighting load, weighing approximately 205 lb. 

The Rear Crewman performed each evacuation alone for the first 60 seconds, while the 

Driver radioed a simulated CASEVAC 9-line report. If the simulated casualty was not 

evacuated by the 60-second mark, the Driver then assisted. The Driver and the Rear 

Crewman then executed the evacuation until the 6-minute mark. Then, the Turret 

Gunner assisted between the 6-minute mark and the time limit of 9 minutes. This 

additional assistance simulated a Marine from another AAV assisting the Rear 

Crewman and the Driver in cases when further help is necessary. Once the simulated 

casualty was placed on top of the vehicle for the exterior evacuation or on the floor of 

the troop compartment for the interior evacuation, the Data Collector recorded the stop 

time. The Data Collector was located in the Troop Compartment of the AAV and was 

responsible for verifying that the dummy had not sustained additional head injuries 

during the evacuation. An accelerometer check-light (green, yellow, or red) identified

any additional injury. A red check light meant the casualty sustained significant head 

injury during the casualty evacuation; a green light signaled no injury; while a yellow 

check light signaled additional head injury but not life threatening. This task simulated 

conducting a CASEVAC from the turret, and is a T&R requirement for 1833s. The task 

was performed as a crew event, with the primary measure of performance being the 

time required to complete the task and the AAV Turret Gunner not actively participating 

until after the 6-minute mark. 
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The data collected from this task was analyzed two ways. The first comparison looked 

for performance differences between the different integration-level groups. The second 

comparison looked for performance differences between crews grouped only by the 

gender of the Marines serving in the critical billets (AAV Rear Crewman and AAV 

Driver), and actively participating in the CASEVAC. 

J.5.2.9.1 External CASEVAC of an Incapacitated Turret Gunner by Integration 

Level

See Section J.5.2.9 for task description

J.5.2.9.1.1 External CASEVAC of an Incapacitated Turret Gunner by Integration 

Level Scatterplots

Figure J-1 displays the results to complete the External CASEVAC of an Incapacitated 

Turret Gunner task by integration level. There were no outliers identified in the dataset. 

Figure J-1. External CASEVAC from Turret by Integration Level

J.5.2.9.1.2 External CASEVAC of an Incapacitated Turret Gunner by Integration 

Level Data Table and Analysis

The tables below summarize the results of the task, External CASEVAC by Integration 

Level. The first table compares means across metrics and integration levels. The 

second table presents ANOVA and other test results bringing to focus those metrics that 

resulted in statistical significance along with their percentage differences. 
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Table J-20. External CASEVAC of an Incapacitated Turret Gunner by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

External CASEVAC from Turret 

(minutes)* 

C 38 1.33 0.54

LD 41 1.86 0.99

HD 44 2.81 1.79

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level.

Table J-21. External CASEVAC of an Incapacitated Turret Gunner by Integration Level ANOVA 

and other Test Results 

Metric F Statistic 

(df)

F Test

 P-Value

Compariso

n 

Difference % Diff 2-Sided 

P-Value 

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

External 

CASEVAC from 

Turret (minutes)

15.90

(2, 71.2) < 0.01††

LD-C 0.53 39.63% < 0.01* 0.30 0.76 0.23 0.83

HD-C 1.48 110.96% < 0.01* 1.11 1.84 1.00 1.95

HD-LD 0.95 51.08% < 0.01* 0.55 1.35 0.43 1.47

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level. 

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances)

For this task, sample sizes are sufficiently large (n>30) to satisfy the normality 

assumption for ANOVA. However, the standard deviation for the HD group is more than 

twice that of the C group. Thus, we recommend using the robust ANOVA results 

presented in the table above.

The LD group was 39.63% slower than the C group, while the HD group was 110.97% 

slower than the C group; this difference is statistically significant. The control group had 

a mean time of 1.33 minutes, which is 39% faster than the LD group and 110% faster

than the HD group. 

J.5.2.9.1.3 External CASEVAC of an Incapacitated Turret Gunner by Integration 

Level Contextual Comments

When conducting the analysis of this task by just the concentration (HD, LD, C) without 

consideration to the critical billets and the order in which those billets executed the 

CASEVACS, there exists the potential to lose some understanding based on the 

concentration level alone. In these tasks, there existed the potential for low-density 

crews to have two males as the critical billet holders and high-density crews to have a 

FM or MF combination for the critical billet holders. Analysis using only concentration 

levels limits our visibility on what actually took place within the crews by masking gender 

impact. This skews the data analysis as there appears to be no significant effect of 

integration based on the similar mean times found in both CASEVACs when looking at 

just the crew concentration (between 1.33 minutes to 2.81 minutes or a difference of 1 

minute and 29 seconds). By looking instead at the task by critical billets, the data show 
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more significant differences between the mean times, as shown by the percent 

differences in time to execute the task. This breakout in the data is shown in 

subsequent paragraphs.

J.5.2.9.1.4 External CASEVAC of an Incapacitated Turret Gunner by Integration 

Level Additional Insights

The requirement of an AAV Rear Crewman and/or AAV Driver to execute a CASEVAC

of an incapacitated AAV Turret Gunner is a T&R task for an AAV Crew. Unlike similar 

MOSs, the AAV T&R does not stipulate a specific time requirement. The HBCT manual 

requires a 1812 Tank Crewman MOS to conduct an evacuation out of an M1A1 Abrams 

Tank in 2 minutes. The AAV task designed in this experiment was similar to the Tank 

HBCT requirement. The ability of a Marine or Marines to extricate a casualty from the 

turret quickly could mean the difference between life and death for an injured or 

incapacitated AAV Turret Gunner. In the case of this task, seconds could be the 

determining factor. Unlike similar vehicle MOSs, the AAV T&R does not stipulate a 

specific time requirement to complete this task for it to be considered a display of 

mastery or non-mastery. The maximum time of 9 minutes was based on the goal of 

capturing all data points that could exist above a shorter time range. This data may 

help the AAV community determine an acceptable time with which to standardize the 

Assault Amphibious T&R Manual. 

J.5.2.9.2 External CASEVAC of an Incapacitated Turret Gunner by Critical Billet

See Section J.5.2.9 for task description.

J.5.2.9.2.1 External CASEVAC of an Incapacitated Turret Gunner by Critical Billet 

Scatterplots

The scatter plots below display the results to complete the External CASEVAC of an 

Incapacitated Turret Gunner task by critical billet. There were no outliers identified in the 

dataset. 
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Figure J-11. External CASEVAC from Turret by Critical Billet 

J.5.2.9.2.2 External CASEVAC of an Incapacitated Turret Gunner by Critical Billet 

Data Table and Analysis

The tables below summarize the results of the task, External CASEVAC (Analysis by 

Critical Billet). The first table compares means across metrics and integration levels. 

The second table presents ANOVA and other test results bringing to focus those 

metrics that resulted in statistical significance along with their percentage differences. 

Table J-22. External CASEVAC of an Incapacitated Turret Gunner by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD 

External CASEVAC from Turret 

(Rear Crewman/Driver) 

(minutes)* 

MM 53 1.42 0.62

MF 27 1.76 1.18

FM 26 2.17 0.71

FF 17 4.19 2.00

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level

Table J-23. External CASEVAC of an Incapacitated Turret Gunner by Critical Billet ANOVA and 

other Test Results

Metric F Statistic 

(df)

F Test

 P-Value

Compariso

n 

Diff % Diff 2-Sided 

P-Value

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

External 

CASEVAC from 

Turret (Rear 

Crewman/Driver

) (minutes)

15.63

(3, 42.7) < 0.01††

MF-MM 0.34 23.97% 0.17 0.02 0.66 -0.07 0.75

FM-MM 0.75 52.56% < 0.01* 0.54 0.96 0.47 1.02

FF-MM 2.77 194.66% < 0.01* 2.11 3.42 1.91 3.62

MF-FM -0.41 -18.74% 0.13 -0.75 -0.06 -0.85 0.04

Critical Billet Gender
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Metric F Statistic 

(df)

F Test

 P-Value

Compariso

n 

Diff % Diff 2-Sided 

P-Value

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

FF-MF 2.43 137.68% < 0.01* 1.72 3.13 1.51 3.34

FF-FM 2.02 93.14% < 0.01* 1.35 2.69 1.15 2.89

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances) 

Table J-22 display the Rear Crewman and Driver billets as a two-letter representation, 

where the first letter represents the gender of the Marine occupying the Rear Crewman 

billet and the second letter represents the gender of the Marine occupying the Driver 

billet, M for Male and F for female. 

For this task, the MM, MF, FM and FF groups are all not normally distributed with 

Shapiro-Wilk Test p-values of less than 0.01. A Kruskal-Wallis test does confirm the 

results of the standard ANOVA. However, the standard deviation of the FF group is 

more than twice that of the MM group, thus we recommend using the results of the 

robust ANOVA presented in the table above.

The MM combination had a mean time of 1.42 minutes while the MF combination had a 

mean time of 1.76 minutes. The FM combination had a mean time of 2.17 minutes with 

a SD of 0.71 minutes. The FF combination had a mean time of 4.19 minutes with a SD 

of 2 minutes. The FM combination was 52.56% slower than the MM combination. The 

FF combination was 194.66% slower than the MM combination and 137.68% slower 

than the MF combination. Analytical results show the gender of the Marine in the first 

critical billet, the AAV Rear Crewman, was significant. When the AAV Rear Crewman 

(who had 60 seconds to attempt the evacuation alone) was male and AAV Driver was 

female, this task was executed 18.74% faster than when the AAV Rear Crewman was 

female and the AAV Driver was male.

In the cases where the female was in the Rear Crewman billet, the differences were 

statistically significant. The FF combination was 194.66% slower than the MM 

combination, and 137.68% slower than the MF combination. The FM combination was 

52.56% slower than the MM combination while the FF combination was 93.14% slower 

than the FM combination. 

J.5.2.9.2.3 External CASEVAC of an Incapacitated Turret Gunner by Critical Billet

Contextual Comments

For experimental purposes, the AAV Rear Crewman participated solely in the 

evacuation for the first 60 seconds while the AAV Driver reported the incident to higher 

authority. At the 60-second mark, the AAV Driver was allowed to assist in the 

CASEVAC. The third crewmember (the Turret Gunner) could not assist until the 6-
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minute mark. At 6 minutes, the Turret Gunner simulated an AAV crewman coming from 

a nearby vehicle crew to assist the Rear Crewman and Driver. 

J.5.2.9.3 Internal CASEVAC of an Incapacitated Turret Gunner by Integration 

Level Scatterplots

The scatter plots below display the results to complete the Internal CASEVAC of an 

Incapacitated Turret Gunner task by integration level. On Trial Cycle days 3 and 4, two 

data points were excluded from analysis due to data entry errors. The data points are 

contained inside dark black circles on the scatterplot below. 

Figure J-12. Internal CASEVAC of an Incapacitated Turret Gunner by Integration Level

J.5.2.9.4 Internal CASEVAC of an Incapacitated Turret Gunner by Integration 

Level Data Table and Analysis

The tables below summarize the results of the task, Internal CASEVAC by Integration 

Level. The first table compares means across metrics and integration levels. The 

second table presents ANOVA and other test results bringing to focus those metrics that 

resulted in statistical significance along with their percentage differences. 

Table J-24. Internal CASEVAC of an Incapacitated Turret Gunner by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Internal CASEVAC from Turret 

(minutes) 

C 36 1.08 0.72

LD 41 1.12 0.59

HD 45 1.31 0.68
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Table J-25. Internal CASEVAC of an Incapacitated Turret Gunner by Integration Level ANOVA and 

other Test Results

Metric F Statistic 

(df)

F Test

 P-Value Comparison Difference % 

Difference

2-Sided 

P-Value

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Internal 

CASEVAC from 

Turret (minutes)

1.48 (2, 

119) 0.23

LD-C 0.04 3.64% 0.96 -0.22 0.30 -0.27 0.35

HD-C 0.23 21.46% 0.26 -0.02 0.49 -0.07 0.54

HD-LD 0.19 17.19% 0.37 -0.05 0.44 -0.10 0.49

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own

For this task, samples sizes are sufficiently large (n>30) to satisfy normality 

assumptions for ANOVA. Additionally, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA.

The C group performed the task faster than the LD (2 seconds faster) and HD groups 

(17 seconds faster); these differences in mean times and percentage differences are 

not statistically significant. 

J.5.2.9.4.1 Internal CASEVAC of an Incapacitated Turret Gunner by Integration 

Level Contextual Comments

Operational relevance is negligible because of the small differences.

J.5.2.9.5 Internal CASEVAC of an Incapacitated Turret Gunner by Critical Billet

The scatter plots below display the results to complete the Internal CASEVAC of an 

Incapacitated Turret Gunner task by critical billet. On Trial Cycle days 3 and 4, two data 

points were excluded from analysis due to data entry errors. The data points are 

contained inside dark black circles on the scatterplot below 
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Figure J-13. Internal CASEVAC of an Incapacitated Turret Gunner by Critical Billet

J.5.2.9.6 Internal CASEVAC of an Incapacitated Turret Gunner by Critical Billet 

Data Table and Analysis

The tables below summarize the results of the task, Internal CASEVAC by Critical Billet. 

The first table compares means across metrics and integration levels. The second table 

presents ANOVA and other test results bringing to focus those metrics that resulted in 

statistical significance along with their percentage differences. 

Table J-26. Internal CASEVAC of an Incapacitated Turret Gunner by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD 

Internal CASEVAC from Turret 

(Rear Crewman/Driver) 

(minutes)* 

MM 51 1.05 0.66

MF 28 0.98 0.56

FM 27 1.54 0.71

FF 16 1.33 0.52

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

Critical Billet Gender
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Table J-27. Internal CASEVAC of an Incapacitated Turret Gunner by Critical Billet ANOVA and 

other Test Results

Metric F Statistic 

(df)

F Test

 P-Value Comparison Difference % 

Difference

2-Sided 

P-Value

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Internal 

CASEVAC from 

Turret (Rear 

Crewman/Driver) 

(minutes)

4.88 (3, 

118) < 0.01*

MF-MM -0.07 -6.37% 0.97 -0.36 0.23 -0.41 0.28

FM-MM 0.49 47.10% < 0.01* 0.19 0.79 0.14 0.84

FF-MM 0.28 27.20% 0.40 -0.08 0.64 -0.14 0.70

MF-FM -0.56 -36.35% < 0.01* -0.90 -0.22 -0.95 -0.16

FF-MF 0.35 35.85% 0.29 -0.04 0.74 -0.11 0.81

FF-FM -0.21 -13.53% 0.73 -0.60 0.19 -0.67 0.25

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own

For this task, the FM and FF groups are normally distributed with Shapiro-Wilk Test pvalues of 0.12 and 0.57, respectively, while the MM and MF groups are not normally 

distributed with p-values less than 0.01. We proceed with presenting ANOVA results 

because they were confirmed by a Kruskal-Wallis test with a p-value of less than 0.01. 

Additionally, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA.

Analysis shows the gender of the Marine in the first critical billet, the AAV Rear 

Crewman, matters. When the AAV Rear Crewman (who had 60 seconds to attempt the 

evacuation alone) was male and AAV Driver was female, this task was executed 

36.35% faster than when the AAV Rear Crewman was female and the AAV Driver was 

male. See tables above for more detailed analytical results. 

J.5.2.9.6.1 Internal CASEVAC of an Incapacitated Turret Gunner by Critical Billet

Contextual Comments

For experimental purposes, the AAV Rear Crewman participated solely in the 

evacuation for the first 60 seconds while the AAV Driver reported the incident to higher 

authority. At the 60-second mark, the AAV Driver was allowed to assist in the 

CASEVAC. The third crewmember (the Turret Gunner) could not assist until the 6-

minute mark. At 6 minutes, the Turret Gunner simulated an AAV crewman coming from 

a nearby vehicle crew to assist the Rear Crewman and Driver. The Internal CASEVAC 

is a much less physically demanding task when compared to the External CASEVAC. 

J.5.2.10 Conduct Water Evacuation of an Incapacitated Rear Crewman 

In this task, the AAV Turret Gunner and Driver lifted a simulated casualty from the floor 

of the troop compartment to the top of the vehicle through the starboard right cargo 

hatch, which is a T&R requirement for an 1833 AAV Crewman. The casualty was 

simulated by a dummy weighing approximately 205 lbs. The Turret Gunner and Driver 
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had an experimental time limit of 25 minutes to accomplish this task which simulated 

conducting a CASEVAC from the troop compartment of the vehicle. The Data Collector, 

located in either the Troop Commander’s seat or in the Troop Compartment of the AAV, 

initiated the task and recorded the start and stop time. The task was performed as a 

crew event, with the primary measure of performance being the time required to 

complete the task.

The data collected from this task was analyzed two ways. The first comparison looked 

for performance differences between the control group and the low-density group and 

the high-density group. The second comparison looked for performance differences 

between crews grouped by the gender of the two Marines serving in the critical billets 

and actively participating in the casualty extrication -- the AAV Driver and the AAV 

Turret Gunner.

J.5.2.10.1 Conduct Water CASEVAC of an Incapacitated Rear Crewman by 

Integration Level Scatterplots

Figure J-14 shows a scatter plot displaying the results to complete the Water CASEVAC 

of an Incapacitated Rear Crewman by Integration Level task. On trial cycle 4, a data 

point was removed from analysis due to a data entry error. On Experiment Days 1 

through 6, and 8, a total of eight HD-group data points were removed from analysis as 

data entry errors. 

Figure J-14. Conduct Water CASEVAC of an Incapacitated Rear Crewman by Integration Level 
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J.5.2.10.1.1 Conduct a Water CASEVAC of an Incapacitated Rear Crewman by 

Integration Level Data Table and Analysis

The tables below summarize the results of the task Water CASEVAC by Integration 

Level). The first table compares means across metrics and integration levels. The 

second table presents ANOVA and other test results bringing to focus those metrics that 

resulted in statistical significance along with their percentage differences. 

Table J-28. Conduct Water CASEVAC of an Incapacitated Rear Crewman by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Conduct Water CASEVAC 

(minutes)* 

C 21 2.38 0.97

LD 23 4.75 5.03

HD 19 6.48 5.63

*Indicates there is a statistically significant difference in a two-sided hypothesis test between the metric’s mean 

values for the Integration Level.

Table J-29. Conduct Water CASEVAC of an Incapacitated Rear Crewman by Integration Level

ANOVA and other Test Results

Metric F Statistic 

(df)

F Test

 P-Value Comparison Difference % 

Difference

2-Side 

P-Value

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Conduct Water 

CASEVAC 

(minutes)

6.96

(2, 28.1) < 0.01††

LD-C 2.37 99.23% 0.04 0.96 3.78 0.53 4.20

HD-C 4.09 171.70% 0.01* 2.36 5.83 1.83 6.36

HD-LD 1.73 36.38% 0.31 -0.44 3.90 -1.08 4.54

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own.

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances)

For this task, the C, LD, and HD groups are all not normally distributed with ShapiroWilk Test p-values of less than 0.01. A Kruskal-Wallis test does confirm the results of 

the standard ANOVA. However, the standard deviation of the LD and HD groups are 

more than twice that of the C group, thus we recommend using the results of the robust 

ANOVA presented in the table above.

The control group executed the recovery with a mean time of 2.38 minutes; the LD 

group executed this task 99.23% slower (2:22 slower) than the C group and the HD 

group executed this task 171.70% slower (4:06 slower) than the C group. Although only 

the HD group’s time (4:06 slower) is statistically significant, the time differences based 

on integration may be operationally significant. The LD group was 99.23% slower than 

the C group, while the HD group was 171.7% slower than the C group. 
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J.5.2.10.1.2 Conduct a Water CASEVAC of an Incapacitated Rear Crewman by 

Integration Level Contextual Comments

The ability of an AAV crew to extricate a casualty from the troop compartment quickly 

could mean the difference between life and death for an injured or incapacitated Marine. 

In the case of this task, seconds could be the determining factor, especially if the AAV is 

sinking or suffering from an engine or vehicle fire. Unlike similar vehicle MOSs, the 

AAV T&R does not stipulate a specific time requirement to complete this task for it to be 

considered a display of mastery or non-mastery. The maximum time of 25 minutes to 

complete was based on the goal of capturing all data points that could exist above a 

shorter time range. These data are available to help the AAV community determine an 

acceptable time with which to standardize the Assault Amphibious T&R Manual. 

J.5.2.10.1.3 Conduct a Water CASEVAC of an Incapacitated Rear Crewman by 

Integration Level Additional Insights

The eight HD group data points that were excluded from the analysis as depicted on the 

scatterplot above (See section J.5.2.10.1) were valid data points from the perspective 

that each HD group failed to complete the task in the allotted time of 25 minutes. The 

Data Collector was following the experimental plan which asked DC to record a unit 

failure and stop the time once the crew reached the 25 minute mark. Unfortunately, we 

are not able to include the elapsed times for all these 8 data points because we cannot 

conclude when the group would have completed the task if the DC would have allowed 

the crew to continue. Table J-28 shows the HD crew with 19 complete trials vice 27, 

and a mean time of 6.48 minutes. If the excluded eight data points would have been 

accounted for in the analysis, the mean time for the HD group would have increased 

dramatically thereby producing a higher percentage difference between C and HD 

groups.

J.5.2.10.2 Conduct Water CASEVAC of an Incapacitated Rear Crewman by Critical 

Billet Scatterplots

The scatter plots below display the results to complete the Conduct Water CASEVAC of 

an Incapacitated Rear Crewman by Critical Billet task. On trial cycle 4, a data point was 

removed from analysis due to a data entry error. On Experiment Days 1 through 6, and 

8, a total of eight HD-group data points were removed from analysis as data entry 

errors. 
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Figure J-15. Conduct Water CASEVAC of an Incapacitated Rear Crewman by Critical Billet

 

J.5.2.10.3 Conduct Water CASEVAC of an Incapacitated Rear Crewman by Critical 

Billet Data Tables and Analysis

The tables below summarize the results of the task, Water CASEVAC by Critical Billet. 

The first table compares means across metrics and critical billets. The second table 

presents ANOVA and other test results bringing to focus those metrics that resulted in 

statistical significance along with their percentage differences. 

Table J-31. Conduct Water CASEVAC of an Incapacitated Rear Crewman by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD 

Conduct Water CASEVAC 

(Driver/Turret Gunner 

(minutes)* 

MM 31 2.43 0.97

MF 17 7.08 7.34

FM 12 5.74 3.35

FF 3 5.96 3.88

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

Critical Billet Gender
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Table J-30. Conduct Water CASEVAC of an Incapacitated Rear Crewman by Critical Billet ANOVA 

and other Test Results

Metric F Statistic 

(df)

F Test

P-Value Comparison Difference % 

Difference

2-Sided 

P-Value

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Conduct Water 

CASEVAC 

(Driver/Turret 

Gunner) 

(minutes)

5.11 (3, 

59) 0.02††

MF-MM 4.65 191.60% 0.02 2.26 7.04 1.53 7.77

FM-MM 3.32 136.54% 0.01* 1.98 4.65 1.56 5.07

FF-MM 3.53 145.47% 0.25 -0.68 7.74 -2.97 10.03

MF-FM 1.34 23.27% 0.52 -1.33 4.01 -2.13 4.81

FF-MF -1.12 -15.82% 0.71 -5.33 3.09 -6.86 4.62

FF-FM 0.22 3.77% 0.94 -3.85 4.29 -5.69 6.13

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own.

††Indicates statistical significance using a robust ANOVA (accounts for unequal variances

For this task, the FM and FF groups are normally distributed with Shapiro-Wilk Test pvalue of 0.08 and 0.30, respectively, while the MM and FM groups are not normally 

distributed with p-values of less than 0.01. A Kruskal-Wallis test (p-value less than 0.01) 

does confirm the results of the standard ANOVA. However, the standard deviation of 

the MF, FM, and FF groups are more than twice that of the MM group, thus we 

recommend using the results of the robust ANOVA presented in the table above.

There is a significant difference in the mean times of the AAV crews’ execution of this 

task in this method of comparison with the MF, FM, and FF critical billet combinations 

being slower by 191.6% (4:39) slower, 136.54% (3:21) slower, and 145.47% (3:31) 

slower, respectively, than the MM critical billet combination. Although only the MF 

combination showed it was statistically significant (4:39 slower), the differences in the 

ability of an integrated crew to conduct a water CASEVAC could be considered as a 

realistic and significant operational impact.

J.5.2.10.3.1 Conduct Water CASEVAC of an Incapacitated Rear Crewman by 

Critical Billet Contextual Comments

The analysis examines the task performed by critical billet: the AAV Driver and the AAV 

Turret Gunner. In this scenario, the Rear Crewman was incapacitated and the task 

accomplished by the two critical crewman billets. The order of gender by those two 

billets was not specifically important to the analysis, as the task is not scripted and the 

AAV Driver and the AAV Turret Gunner began the task at the exact same time, working 

as a team. 

The ability of an AAV crew to extricate a casualty from the troop compartment quickly 

could mean the difference between life and death for an injured or incapacitated Marine. 

In the case of this task, seconds could be the determining factor, especially if the AAV is 
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sinking or suffering from an engine or vehicle fire. Unlike similar vehicle MOSs, the 

AAV T&R does not stipulate a specific time requirement to complete this task for it to be 

considered a display of mastery or non-mastery. The maximum time of 25 minutes to 

complete was based on the goal of capturing all data points that could exist above a 

shorter time range. These data are available to help the AAV community determine an 

acceptable time with which to standardize the Assault Amphibious T&R Manual. 

J.6 Statistical Modeling Results

J.6.1 Statistical Modeling Results Overview

The previous section discussed results only as they pertain to differences due to 

integration level and critical billets. The goal of statistical modeling as applied here is to 

estimate, simultaneously, the effect of gender integration levels and other relevant 

variables on the AAV crew performance. Refer to the Methodology Annex for a broad 

overview of the analysis plan and the variables used in the models. 

For the selected tasks described in the previous section, this section presents an 

overview of the analysis and results, and then presents the modeling results for each 

task. 

For each task, we describe the significant variables in the model and whether these 

variables are either positively or negatively correlated with the result. A negative 

correlation indicates an increase in that variable will result in a decrease in the response 

variable, which is a desired outcome for elapsed time. 

J.6.2 Selected Tasks Method of Analysis

A mixed effects model with all AAV crew members and all types of personnel variables 

was run for each task. For each result, we create a model using integration level and all 

types of personnel data for each crew member with a random effect for who filled each 

position within the crew. For example, age, height, and other variables for each member 

of the crew and integration level are modeled with the result (response time) as the 

response variable. For tasks that had critical billets, i.e. only one or two Marines were 

performing the task without help from the others, only their variables were included in 

the model, along with the genders of Marines in the critical billets. Where maximum 

likelihood estimation converged, AIC was used for variable selection. Otherwise, we 

comment on the significance of individual variables in the full model. Variables reported 

as significant are concluded to be significant based on at least a one-sided test.

J.6.3 Selected Tasks Overall Modeling Results

There are no personnel data variables that are both statistically significant and have a 

practical impact to the model. Each time personnel data variables are statistically 

significant in a model, their effects are practically negligible, conflicting, and/or 
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incomplete for the AAV crew; i.e., there are no tasks for which a variable is significant 

for all, or even most members of the AAV crew. 

Integration level, however, consistently appears as statistically significant in each of the 

tasks, and its effect is clear, causal, and practical. Therefore, integration level is the 

best variable to describe performance for each of these tasks. Refer to the Descriptive 

Statistics Section for the ANOVA summary for each of the below mentioned tasks.

J.6.3.1 External CASEVAC from Turret

We model elapsed time for the external CASEVAC as a function of the personnel 

variables and gender of the Marines performing the task in a mixed effects model with a 

random effect for who filled each position. The covariates in each model are the values 

of each personnel variable for each volunteer member in the AAV crew. We report 

statistically significant positive and negative correlations.

The results from the final model for External CASEVAC from Turret show that relative to 

two males performing the task, a Male in the Rear Crewman Billet and a Female in the 

Turret Gunner Billet, perform the task 0.39 minutes slower, and the difference is not 

statistically significant. If their billets are switched, the difference increases to 0.47 

minutes and becomes statistically significantly slower (in a 1-sided test). However, if the 

task is performed by two females, then, holding all other variables constant, they 

perform it 2.52 minutes slower, on average, and this difference from a two-male crew is

strongly significant. Although other variables in the model are observed to have a 

statistically significant relationship with elapsed time for this task, their impact on the 

time is negligible.

The models for the following variables do not run due to missing values:

• None.

The following variables are significant in the model and are positively correlated with the 

external CASEVAC: 

• AFQT score of the Rear Crewman

The following Driver variables are significant in the model and are negatively correlated 

with the external CASEVAC: 

• Rifle Range score of the Driver

Because the personnel variables do not have any patters and their effects are often 

negligible, the final model includes integration level only FF groups take 2.77 minutes 

longer than MM (p < 0.01), FM groups take 0.75 minutes longer than MM (p < 0.01), 

and MF groups take .34 minutes longer than MM (one-sided p-value = 0.08) . All these 

differences are statistically significant.
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J.6.3.2 Interior Reload 1

We model elapsed time for the Interior Reload # 1 as a function of the personnel 

variables and gender of the Marines performing the task in a mixed effects model with a 

random effect for who filled each position. The covariates in each model are the values 

of each personnel variable for each volunteer member in the AAV crew. We report 

statistically significant positive and negative correlations.

For the task Interior Reload 1, gender of Marines in critical billets was not chosen by the 

AIC as one of the variables that helps predict elapsed times. 

The models for the following variables do not run due to missing values:

• None.

The following variables are significant in the model and are positively correlated with the 

first interior reload: 

• CFT MTC score for the Turret Gunner

The following variables are significant in the model and are negatively correlated with 

the first interior reload: 

• Height of the Rear Crewman

There are no patterns for any variables the first interior reload. See the 1833

Descriptive Statistics section for the ANOVA summary of this task. 

J.6.3.3 Interior Reload 2

We model elapsed time for the Interior Reload # 2 as a function of the personnel 

variables and gender of the Marines performing the task in a mixed effects model with a 

random effect for who filled each position. The covariates in each model are the values 

of each personnel variable for each volunteer member in the AAV crew. We report 

statistically significant positive and negative correlations.

For the task Interior Reload 2, gender of Marines in critical billets was not chosen by the 

AIC as one of the variables that helps predict elapsed times. 

The models for the following variables do not run due to missing values:

• None.

The following variables are significant in the model and are positively correlated with the 

second internal reload: 

• None.

The following variables are significant in the model and are negatively correlated with 

the second internal reload: 
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• Rifle score for Rear Crewman.

There are no patterns for any variables for the second interior reload. See the 1833 

Descriptive Statistics section for the ANOVA summary of this task. 

J.6.3.4 External Reload

We model elapsed time for the External Reload as a function of the personnel variables 

and gender of the Marines performing the task in a mixed effects model with a random 

effect for who filled each position. The covariates in each model are the values of each 

personnel variable for each volunteer member in the AAV crew. We report statistically 

significant positive and negative correlations.

In the External Reload task, the gender of Marines in the critical billet was eliminated 

from the model during variable selection using AIC. This means that the benefit of its 

relationship with the response variable was outweighed by the cost of including it in the 

model, or that it did not show a strong relationship with elapsed times once other 

variables were included.

The models for the following variables do not run due to missing values:

• None.

The following variables are significant in the model and are positively correlated with the 

external reload: 

• CFT MTC time of the Rear Crewman

• PFT Crunch score of the Rear Crewman

• GT Score of the Turret Gunner.

The following variables are significant in the model and are negatively correlated with 

the external reload: 

• Age of Rear Crewman

• Weight of Rear Crewman

• CFT MANUF time of Rear Crewman

• PFT run time of Rear Crewman

• AFQT score of Turret Gunner

• Weight of Turret Gunner

• Rifle Score of Turret Gunner. 
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There are no patterns for any variables for the external reload, and the effects described 

above are often negligible in size. See the 1833 Descriptive Statistics section for the 

ANOVA summary of this task. 

J.6.3.5 Break / Reassemble Track

We model elapsed time for the Break/Reassemble track as a function of each personnel 

variable for each crew member and integration level in a mixed effects model with a 

random effect for who filled each position. The covariates in each model are the values 

of each personnel variable for each volunteer member in the AAV crew. We report 

statistically significant positive and negative correlations and whether we observe any 

patterns.

For the task Break / Reassemble Track, the model selection process eliminated 

integration levels, indicating that, ceteris paribus, integration level of the crew is not a 

good predictor of how long it takes to perform this task.

The models for the following variables do not run due to missing values:

• None.

The following variables are significant in the model and are positively correlated with the 

break and reassemble track: 

• CFT MTC Score of the Rear Crewman 

• PFT Run Score of the Turret Gunner. 

The following variables are significant in the model and are negatively correlated with 

break and reassemble track: 

• Age of the Rear Crewman 

• Height of the Rear Crewman

• CFT MANUF score of the Rear Crewman 

• Weight of the Turret Gunner

• CFT MANUF score of the Turret Gunner

• PFT Run time of the Turret Gunner. 

There are no patterns for any variables for breaking and reassembling track, and the 

effects described above are often negligible in size. See the 1833 Descriptive Statistics 

section for the ANOVA summary of this task. 
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J.6.3.6 External Mount of M2 & Mk19 and Ammo

We model elapsed time for the External Mount of M2 and Mk19 as a function of each 

personnel variable for each crew member and integration level in a mixed effects model 

with a random effect for who filled each position. The covariates in each model are the 

values of each personnel variable for each volunteer member in the AAV crew. We 

report statistically significant positive and negative correlations and whether we observe 

any patterns.

For the task External Mount of M2 & Mk19 and Ammo, the model selection process 

eliminated integration levels, indicating that, ceteris paribus, integration level of the crew 

is not a good predictor of how long it takes to perform this task.

The models for the following variables do not run due to missing values:

• None.

The following variables are significant in the model and are positively correlated with the 

external mount of weapons and ammunition: 

• CFT MTC time of the Turret Gunner

• PFT Crunch Score of the Turret Gunner. 

The following variables are significant in the model and are negatively correlated with 

the external mount of weapons and ammunition: 

• CFT MTC Score of the Driver

• Rifle Range score of the Driver

• Age of the Turret Gunner 

• AFQT of Turret Gunner. 

J.6.3.7 Internal CASEVAC from Turret

We model elapsed time for the Internal Casevac from Turret as a function of the 

personnel variables and gender of the Marines performing the task in a mixed effects 

model with a random effect for who filled each position. The covariates in each model 

are the values of each personnel variable for each volunteer member in the AAV crew. 

We report statistically significant positive and negative correlations.

Genders of Marines in critical billets were not selected by AIC into the final model of 

elapsed time for Internal CASEVAC from Turret, indicating that no difference was 

observed between genders for this task. 

The models for the following variables do not run due to missing values:
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• None.

The following variables are significant in the model and are positively correlated with the 

internal CASEVAC: 

• GT of the Driver

• CFT MANUF time of the Driver.

• Rifle Range Score of the Driver

• CFT MTC time of the Rear Crewman 

• Rifle Range Score of the Rear Crewman. 

The following variables are significant in the model and are negatively correlated with 

the internal CASEVAC: 

• AFQT of the Driver

• Weight for the Rear Crewman

• GT of the Turret Gunner

• Height of the Turret Gunner 

• CFT MTC score of the Turret Gunner. 

There are no patterns for any variables for the internal CASEVAC, the effects of most 

variables above are negligible. See the 1833 Descriptive Statistics section for the 

ANOVA summary of this task. 

J.6.3.8 Water CASEVAC 

We model elapsed time for the water casevac as a function of the personnel variables 

and gender of the Marines performing the task in a mixed effects model with a random 

effect for who filled each position. The covariates in each model are the values of each 

personnel variable for each volunteer member in the AAV crew. We report statistically 

significant positive and negative correlations.

Genders of Marines in critical billets were selected by AIC into the final model of 

elapsed time for Water CASEVAC. Compared to the reference group of two males 

performing the task, a male in the Rear Crewman billet and a female in the Turret 

Gunner billet conducted the task 4.9 minutes slower. This difference is statistically 

significant with a two-sided p-value of 0.06. Other gender compositions of critical billets 

did not show significant differences from the all-male control group. 

The models for the following variables do not run due to missing values:

• None.
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The following variables are significant in the model and are positively correlated with the 

water CASEVAC: 

• AFQT of the Driver

• PFT Run time of the Driver

• CFT MTC Time of the Driver. 

The following variables are significant in the model and are negatively correlated with 

the water CASEVAC: 

• Weight of the Driver

• Rifle Range Score of the Driver

• CFT MANUF time of the Turret Gunner. 

Because there are no patterns in the significance of the above variables and because 

their effects are often negligible, our final model includes only the genders of Marines in 

critical billets and the random effects for which volunteer fills each billet. In this model, it 

takes two female Marines 3.45 minutes longer than two male Marines to perform the 

task and the difference is on the border of statistical significance (two-sided p-value of 

0.21), while a female Driver and male Turret Gunner take 3.11 minutes longer (p = 0.06) 

and a male Driver and female Turret Gunner take 4.28 minutes longer (p < 0.01) than 

two males. The last two differences are statistically significant.
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Appendix to Annex J 

1833 Supplemental Information

This appendix provides supplemental information for the 1833 portion of the GCE ITF 

experiment. It provides information regarding the additional descriptive and basic 

inferential statistics not described in Annex J. 

Section 1: Additional Task Basic and Inferential Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. The experiment included a number of tasks and associated metrics 

conducted to enhance operational realism and maintain consistent application of the 

experimental process. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

This section presents results for additional 1833 tasks. Annex J contains the descriptive 

statistics for the remainder of the 1833 tasks. The words “metric” and “task” are used 

interchangeably throughout this Appendix. They both refer to the experimental task.

The tables in this appendix display results for the additional 1833 metrics, to include 

metrics and integration levels with their respective sample sizes, means, standard 

deviations, and percent difference between integration levels, and ANOVA results, 

including metrics and integration levels, and p-values suggesting statistical significance. 

For each task, an ANOVA and t-test were conducted to compare groups. If p-values 

are less than the a-priori determined significance level of 0.10, we conclude there is 

statistical evidence that the response for the LD and HD groups are different from that in 

the C group. 

Section 2: Additional Task Results

Conduct a modified Gun Table V Overview. The AAV crews engaged multiple 

targets from 400 to 1500 meters from multiple defensive and offensive positions. These 

distances and exposure times were dictated by the US Army HBCT Manual. Marines 

conducted four separate engagements: one offensive and three defensive, and 

engaged 12 vehicle or troop targets. 

A modified Gun Table V was used to evaluate a vehicle crew’s ability to engage similar 

targets to those used during semi-annual crew and section gunnery qualifications. 

Employing both weapons systems in an AAV turret is a physically strenuous task for the 

Turret Gunner, especially in the case when immediate or remedial action is required. 

Although the other crew members are not directly involved in the employment of the UpGunned Weapons Station (UGWS), the driver’s performance spotting targets and 

maneuvering the vehicle to allow the turret gunner to safely engage those targets can 

have a significant effect on the Turret Gunner’s ability to identify and engage targets. 

Time for this task started when targets were presented and stopped when the Turret 
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Gunner placed effects on target or the target went down for time per the HBCT. The 

Master Gunner executed the range and modified gun table. A Data Collector was 

positioned alongside the Master Gunner to record target exposure times. The start time 

for each target presentation began when the target was in its exposed locked position. 

The Master Gunner identified when the target was in its locked positon and when it was 

down due to a hit or down for time. The stop time for each target engagement was 

when the Master Gunner assessed weapons effects on the presented target or that 

target went down for time based on the HBCT Unstabilized Platform Gunnery Tables. 

Subsequent paragraphs examine total engagement times for each type of engagement. 

Total engagement time for defensive engagements is the sum of 10 target exposure 

times; total engagement time for offensive engagements is the sum of 2 target exposure 

times. The data collected from this task was analyzed in two separate ways. The first 

method of comparison looked for the performance differences between the C, LD, and 

HD groups. The second method of comparison looked for performance differences 

between crews grouped by the gender of the Marine serving in the critical billet as the 

AAV Turret Gunner.

Fire Weapons – Defensive by Integration Level Data. Table J A summarizes the 

results of the task, Fire Weapons – Defensive by Integration Level. 

Table J A – Fire Weapons – Defensive by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD % Difference

(LD-C)

% Difference

(HD-C)

% Difference

(HD-LD)

Fire 

Weapons - 

Defensive 

C 35 7.14 1.40

LD 42 7.48 1.62 4.64% 8.74% 3.92% 

HD 42 7.77 1.48

Table J A shows a difference of 20.4 seconds between the mean time for the C group’s 

7.14 minutes and the LD group’s 7.48 minutes over 10 separate target exposures is 

only a 2.04-second difference per target. Considering all targets had a 70- to 

78-second exposure time (vehicle targets had a 78-second exposure time to account for 

the 8 seconds it took to lift the target), the 2.04-second difference is negligible. Both 

tasks, “Fire Weapons – Defensive” and “Fire Weapons – Offensive”, show no statistical 

significance per the ANOVA and the Tukey test. 

Fire Weapons – Offensive by Integration Level. Table J B summarizes the results of 

the task, Fire Weapons – Offensive by Integration Level. 
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Table J B - Fire Weapons – Offensive by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD % Difference

(LD-C)

% Difference

(HD-C)

% Difference

(HD-LD)

Fire Weapons 

- Offensive 

C 37 1.69 0.45

LD 42 1.7 0.43 0.69% 8.42% 7.67% 

HD 45 1.83 0.37

Table J B shows the LD group was 0.69% slower than the C group. The HD group was 

8.42% slower than the C group. The HD group was 7.67% slower than the LD group. 

Fire Weapons – Defensive by Critical Billet - Turret Gunner. Table J C summarizes 

the results of the task, Fire Weapons – Defensive by Critical Billet. 

Table J C - AAV Fire Weapons – Defensive (Turret Gunner) by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD % Difference

(LD-C)

Fire Weapons 

- Defensive 

M 78 7.17 1.4

12.75% 

F 41 8.08 1.57

Table J C shows that female (F) turret gunners were 12.75% slower. 

The analytical results for this task by critical billet, in this case the Turret Gunner, show 

female turret gunners (F) performed slower than their male counterparts (M). 

• Contextual Comments. Providing Defensive Fires from an AAV is a combat 

task where time is most critical. Faster engagement times (even those measured 

in fractions of a second) during combat operations are highly desirable. Per the 

MCWP 3-13, “The side that brings effective fire to bear on the enemy first has a 

significant advantage. Firing first with accurate fire greatly increases chances of 

winning the engagement. If the initial burst misses, the first to fire can probably 

shoot again and hit the target before receiving return fire. If surprised by the 

enemy and unable to fire first, the AA unit should return fire as quickly as 

possible. The AA unit should continue to engage the enemy as fast as possible, 

because fire placed in the enemy’s area will lessen his effectiveness and give 

friendly weapons time to adjust. A wasted opportunity to engage a target may 

never be regained.” The analytical results show statistical significance when 

gender is taken into account for the critical billet in the performance of Defensive 

Fires, but it did not present results that were statistically significant for the 

integration level analysis, i.e., C, LD, or HD groups. 
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• Additional Insights. The difference in performance between the M and F 

groups may be a result of disparity in experience levels when employing the 

weapons station vice a physical disparity, as mentioned in the Experiment 

Limitations. The male volunteers were primarily Marines with several years’ 

experience in the 1833 MOS, while the female volunteers were entry-level 

Marines based on their recent graduation from MOS school, as referenced in the 

AAV Experiment population description. 

AAV Fire Weapons – Offensive (Turret Gunner) by Critical Billet. Table J D

summarizes the results of the task, Fire Weapons – Offensive (Analysis by Critical 

Billet).

Table J D - AAV Fire Weapons – Offensive (Turret Gunner) by Critical Billet

Metric Integration 

Level 

Sample 

Size Mean SD % Difference

(LD-C)

Fire Weapons 

- Offensive 

(Turret 

Gunner) 

(minutes)

M 81 1.66 0.43

14.29% 

F 43 1.9 0.36

Table J D shows that female turret gunners were 14.29% slower on average; this 

difference is statistically significant in a one-sided hypothesis test and two-sided test. 

• Contextual Comments. When gender is taken into account for the critical billet 

(Turret Gunner), the results show statistical significance. When analyzed by 

critical billet, results show female turret gunners (F) performed slower than their 

male counterparts (M). For offensive engagements where two targets were 

presented with 70- to 78-second exposure times, the female turret gunners 

achieved effects on targets 7.2 seconds slower than male turret gunners. 

• Additional Insights 

o Faster engagement times (even those measured in fractions of a second) 

are highly desirable during combat operations. Per the MCWP 3-13, “The 

side that brings effective fire to bear on the enemy first has a significant 

advantage. Firing first with accurate fire greatly increases chances of 

winning the engagement. If the initial burst misses, the first to fire can 

probably shoot again and hit the target before receiving return fire. If 

surprised by the enemy and unable to fire first, the AA unit should return 

fire as quickly as possible. The AA unit should continue to engage the 

enemy as fast as possible, because fire placed in the enemy’s area will 
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lessen his effectiveness and give friendly weapons time to adjust. A 

wasted opportunity to engage a target may never be regained.” 

o The difference in performance between the M and F groups may be a 

result of disparity in experience levels when employing the weapons 

station vice a physical disparity, as mentioned in the Experiment 

Limitations. The male volunteers were primarily Marines with several 

years’ experience in the 1833 MOS, while the female volunteers were 

entry-level Marines based on their recent graduation from MOS school, as 

referenced in the AAV Experiment population description. 

Conduct a Manual Ramp Raise. In this Maintenance Action subtask, the AAV crew 

manually raised the AAV ramp with a ramp jack. The crews did not have 

responsibilities dictated for this task and were allowed to conduct the task as they saw 

fit until completion. Upon completion, an AAV Platoon Staff member inspected the 

ramp to ensure it had been properly secured. There was no maximum time limit for this 

task. The Data Collector stood to the rear of the vehicle and was the initiator of this task 

by verbal command and recorded start and stop times. 

The task was performed as a crew event with the primary measure of performance 

being the time required to complete the task. The data collected from this task was 

analyzed by crew integration only, and not by critical billet, as each Marine in the AAV 

Crew had an active role in the execution. 

Table J E - Conduct a Manual Ramp Raise by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Manual Raise 

of Ramp* 

C 38 2.57 0.56

LD 42 2.77 0.74

HD 46 3.28 0.91

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

Table J F - Conduct a Manual Ramp Raise by Integration Level AAV ANOVA and Tukey Test 

Results

Metric F Statistic 

(df)

F Test 

P-Value Comparison Difference % 

Difference

P-Value 

(onesided)

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Manual Raise of 

Ramp (minutes)

9.95 (2, 

123) < 0.01*

LD-C 0.19 7.56% 0.49 -0.10 0.49 -0.16 0.55

HD-C 0.71 27.70% < 0.01* 0.42 1.00 0.37 1.06

HD-LD 0.52 18.73% < 0.01* 0.24 0.80 0.18 0.86

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own
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For this task, group sample sizes are sufficiently large (n ≥ 30) to satisfy normality 

assumptions for ANOVA. Additionally, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA. Table J-E and Table J-F show the

LD group was 7.56% slower than the C group; this difference is not statistically 

significant in a Tukey test. The HD group was 27.7% slower than the C group; this 

difference is statistically significant in a Tukey test. The HD group was 18.73% slower 

than the LD group; this difference up is statistically significant in a Tukey test. 

• Contextual Comments. Analysis looked for performance differences between 

the control group and the low-density group and the high-density group. The C 

group had the fastest mean time for the manual raising of the ramp (2.57 

minutes), while the HD recorded an 18% to 27.7% difference when compared to 

the LD and C groups, respectively. This difference equates to slower times, and 

in the case of the HD groups, on average, a time 43 seconds slower than the C 

group. Although statistical significance exists from the analytical results, the 

small differences in times and percentages of raising an AAV Ramp can be 

considered operationally irrelevant. 

Load Weapons and Ammunition Overview. The vehicle crew loaded the M2 .50-

caliber machine gun, the MK-19 40-mm grenade launcher, and a full complement of 

ammunition (two cans of .50-caliber ammunition and three cans of 40-mm grenades) 

from the lowered ramp of the AAV. The crew executed this task from the interior of the 

vehicle. A fully assembled M2 weighs approximately 85 lb and the MK-19 weighs 

approximately 79 lb. Upon completion, an AAV Platoon Staff member inspected to 

ensure the weapons were installed correctly. The Data Collector was located on the 

near the Troop Compartment of the AAV, and initiated this task with a verbal start time, 

recording start and stop times. There was no maximum time limit for this task. This 

task simulated the AAV crew loading weapons and ammunition from various positions 

on the vehicle. The task was performed as a crew event, with the primary measure of 

performance being the time required to complete the task. The data collected from this 

task was analyzed by crew integration only, and not by critical billet, as each Marine in 

the AAV Crew had an active role in execution. 

Internal Mount of M2 by Integration Level. Table J G summarizes the results of the 

task, Internal Mount of M2 by integration level. 

Table J G - Internal Mount of M2 by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD % Difference

(LD-C)

% Difference

(HD-C)

% Difference

(HD-LD)

Int Mount of 

M2* 

C 38 2.33 1.82

LD 41 2.96 1.61 26.83% 40.48% 10.76% 

HD 46 3.28 1.56

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.
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Table J G shows the LD group was 26.83% slower than the C group; this difference is 

not statistically significant in a Tukey test. The HD group was 40.48% slower than the C 

group; this difference is statistically significant in a Tukey test. The HD group was 

10.76% slower than the LD group; this difference is not statistically significant in a 

Tukey test. 

• Contextual Comments. In the analysis, the C group had a mean time of 2.33 

minutes, which was 26% faster when compared to the LD group (38 seconds 

faster), and over 28% faster when compared to the HD group (57 seconds 

faster). Unless in an extreme situation (in combat or in training), a difference of 

approximately 1 minute in the internal mounting of the M-2 is operationally 

irrelevant.

Conduct Manual Turret Manipulation. In this subtask, the AAV Turret Gunner, 

without assistance, manually traversed, elevated, and depressed the vehicle turret, 

using the manual traverse and elevation controls within the turret. The Turret Gunner 

manually elevated to maximum, depressed to maximum, and then traversed the turret 

360 degrees. A Data Collector captured the elapsed time for this task; there was no 

maximum time limit. This task simulated the Turret Gunner manually manipulating the 

turret to scan and engage targets. The task was performed as an individual event, with 

the primary measure of performance being the time required to complete the task.

The data collected from this task was analyzed two ways. The first comparison looked 

for performance differences between the integration level groups. The second 

comparison looked for performance differences between crews grouped only by the 

gender of the Marines serving in the critical billet (AAV Turret Gunner) and actively 

participating in manual manipulation of the Up-Gunned Weapon Station (UGWS).

Conduct Manual Turret Manipulation by Integration Level. The tables below 

summarize the results of the task, Manual Turret Manipulation by Integration Level. 

Table J H - Conduct Manual Turret Manipulation by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Manual Manipulation of Gun 

(minutes)

C 38 1.82 0.24

LD 42 1.96 0.38

HD 45 2.13 0.42
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Table J I - Conduct Manual Turret Manipulation by Integration Level

Metric F Statistic 

(df)

F Test 

P-Value Comparison Difference % 

Difference

P-Value 

(onesided)

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Manual 

Manipulation of 

Gun (minutes)

7.75 (2, 

122) < 0.01*

LD-C 0.14 7.56% 0.21 0.00 0.28 -0.03 0.31

HD-C 0.31 17.17% < 0.01* 0.17 0.45 0.15 0.48

HD-LD 0.17 8.93% 0.07* 0.04 0.31 0.01 0.34

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own

For this task, group sample sizes are sufficiently large (n ≥ 30) to satisfy normality

assumptions for ANOVA. Additionally, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA. Table J H and Table J I show the 

LD group was 7.56% slower than the C group; this difference is not statistically 

significant in a Tukey test. The HD group was 17.17% slower than the C group; this 

difference is statistically significant in a Tukey test. The HD group was 8.93% slower 

than the LD group; this difference is statistically significant in a Tukey test. On 

Experiment Day 14, the HD-group data point was removed from analysis as a data 

entry error. 

• Contextual Comments. In the analysis, the C group had a faster mean time of 

1.82 minutes. During comparative analysis between all three integration-level 

groups, the C-HD comparison and the HD-LD comparison show statistically 

significant differences, with the HD group being 17% slower (19 seconds slower) 

than the C group in executing the task. 

• Additional Insights. Manual manipulation of the UGWS to traverse and elevate 

the weapons systems onto targets is a required task that any Marine conducting 

gunnery training or participating in combat operations will execute. It requires 

approximately 8-10 lb of force to use the manual turret traverse mechanism. If 

the turret were to lose electrical traverse capability, the Turret Gunner would 

solely use the manual turret traverse mechanism. In training and combat, the 

ability to manipulate the weapons onto a target quickly is important. Executing 

this task in a combat environment is especially important because it increases 

the effectiveness and survivability of an AAV crew. 

Conduct Manual Turret Manipulation by Critical Billet - AAV Turret Gunner. The 

tables below summarize the results of the task, Manual Turret Manipulation by Critical 

Billet. 
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Table J J - Conduct Manual Turret Manipulation by Critical Billet - AAV Turret Gunner

Metric Integration 

Level 

Sample 

Size Mean SD 

Manual Manipulation of Gun (Turret 

Gunner) (minutes)

M 82 1.83 0.27

F 43 2.26 0.41

Table J K - Conduct Manual Turret Manipulation by Critical Billet - AAV Turret Gunner ANOVA and 

Tukey Test Results

Metric F Statistic 

(df)

F Test

 P-Value Comparison Difference % 

Difference

T-Test 

Statistic

P-Value 

(onesided)

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Manual 

Manipulation of 

Gun (minutes)

49 (1, 

123) < 0.01* F-M 0.43 23.34% 6.17 

(61)

< 0.01* 

(< 0.01*) 0.34 0.52 0.31 0.55

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own

For this task, group sample sizes are sufficiently large (n ≥ 30) to satisfy normality 

assumptions for ANOVA. Additionally, group standard deviations are sufficiently similar 

to satisfy the equal variance assumption for ANOVA. Table J J and Table J K show the 

female turret gunners were 23.34% slower on average; this difference is statistically 

significant in a one-sided hypothesis test and two-sided test. 

• Contextual Comments. In the analysis, male Turret Gunners (M) had a mean 

of 1.83 minutes, while female Turret Gunners had a mean of 2.26 minutes. The 

differences between mean times produce a 23.34% difference (26 seconds 

slower) when comparing male and female Turret Gunners. 

• Additional Insights. Manual manipulation of the UGWS to traverse and elevate 

the weapons systems onto targets is a required task that any Marine conducting 

gunnery training or participating in combat operations will execute. It requires 

approximately 8-10 lb of force to use the manual turret traverse mechanism. If 

the turret were to lose electrical traverse capability, the Turret Gunner would 

solely use the manual turret traverse mechanism. In training and combat, the 

ability to manipulate the weapons onto a target quickly is important. Executing 

this task in a combat environment is especially important because it increases 

the effectiveness and survivability of an AAV crew. 

Perform Recovery Operations. In this task, the AAV crew conducted a water recovery 

and a land recovery of a simulated disabled AAV. The crews of the recovery and 

disabled AAVs worked together for each vehicle’s portion of the recoveries. 
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The water recovery required the Turret Gunner and the Rear Crewman from each 

vehicle to either throw water tow ropes to the recovery vehicle or use a boat hook to 

secure the thrown ropes. The crews would then connect both vehicles stern-to-stern 

and tow the disabled vehicle in the water. The Data Collector, located in either the 

Troop Commander’s Seat or the Troop Compartment, recorded a stop time on the 

commencement of the tow. 

The land tow required both crews to manipulate the two vehicles and the land tow bar 

weighing approximately 150 lb, and then attach it to two points on the disabled vehicle. 

The operational vehicle backed up until the tow pintle was seated. Once the vehicle 

was attached, both crews loaded up into the recovery vehicle and the recovery vehicle 

would begin to tow. The Data Collector, located outside the AAV, captured the stop 

time for this task when the recovery vehicle had towed the disabled vehicle 125 ft up the 

beach to a designated area. 

Upon completion of each tow, the crews swapped roles and executed the recovery 

again. There was no maximum time limit for this subtask. Water and land tow tasks are 

requirements outlined by the T&R Manual and are somewhat likely to occur during 

normal operations on land and in the water. Both tasks were performed as a crew 

event, with the primary measure of performance being the time required to complete the 

task. 

The data collected from this task was analyzed by comparing the performance 

difference between the control group and the low-density group and the high-density 

group. As all three crew members of a single AAV were actively engaged in this task, 

there was no requirement to conduct analysis by critical billet. The water recovery data 

is separated into two groups, operational and disabled. 

Conduct Water Recovery; Operational Vehicle. The tables below summarize the 

results of the task, Water Recover; Operational Vehicle by Integration Level. 

Table J L- Conduct Water Recovery; Operational Vehicle by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Conduct Water Recovery; operational 

(minutes)

C 22 5.40 1.78

LD 22 5.49 2.06

HD 27 5.24 1.84
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Table J M - Conduct Water Recovery; Operational by Integration Level ANOVA and Tukey

Metric F Statistic 

(df)

F Test

 P-Value Comparison Difference % Difference

P-Value 

(onesided)

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Conduct Water 

Recovery; 

operational 

(minutes)

0.12 (2, 

68) 0.89

LD-C 0.09 1.70% 0.99 -0.90 1.08 -1.10 1.28

HD-C -0.17 -3.06% 0.95 -1.11 0.78 -1.30 0.97

HD-LD -0.26 -4.67% 0.88 -1.20 0.69 -1.39 0.88

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level. 

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own. 

For the task above, the LD and HD groups are normally distributed as evidenced by 

Shapiro-Wilk Test p-values of 0.12 and 0.05, respectively, while the C group is not 

normally distributed with Shapiro-Wilk p-value of less than 0.01. We proceed with 

presenting ANOVA results since they are confirmed by a Kruskal-Wallis Test (p-value = 

0.95). Additionally, group standard deviations are sufficiently similar to satisfy the equal 

variance assumption for ANOVA. Table J-L and Table J-M show the LD group was 

1.7% slower than the C group; this difference is not statistically significant in a Tukey 

test. The HD group was 3.06% faster than the C group; this difference is not statistically 

significant in a Tukey test. The HD group was 4.67% faster than the LD group; this 

difference is not statistically significant in a Tukey test. On Experiment Day 1, the LDgroup data point was removed from analysis as a data entry error. 

• Contextual Comments. In the analysis, the C group had a mean time of 5.40 

minutes and was 1.7% (5 seconds) faster than the LD group. The HD group was 

3.06% (9 seconds) faster than the C group. Due to the means of the groups 

being so close, the determination could be made that the composition of an AAV 

Crew during the execution of this task may not have an operational impact. The 

land-recovery task analysis shows the C group had a mean time of 5.97 minutes 

and was 12.24% slower than the LD group. The HD group was 1.15% slower 

than the C group.

Conduct Water Recovery; Disabled Vehicle. The tables below summarize the results 

of the task, Water Recovery; Disabled Vehicle (Analysis by Integration Level). 

Table J N - Conduct Water Recovery; Disabled Vehicle by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Conduct Water Recovery; disabled 

(minutes)

C 22 5.70 2.81

LD 22 5.60 1.76

HD 27 5.84 2.13
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Table J O - Conduct Water Recovery; Disabled Vehicle by Integration Level ANOVA and Tukey 

Test Results

Metric F Statistic 

(df)

F Test

 P-Value Comparison Difference % 

Difference

P-Value 

(onesided)

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Conduct Water 

Recovery; 

disabled 

(minutes)

0.07 (2, 

68) 0.93

LD-C -0.11 -1.87% 0.99 -1.29 1.08 -1.53 1.32

HD-C 0.14 2.41% 0.98 -0.99 1.27 -1.22 1.50

HD-LD 0.24 4.36% 0.93 -0.88 1.37 -1.11 1.60

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own.

For the overall time to mount and remove side panels, the C and HD groups are 

normally distributed as evidenced by Shapiro-Wilk Test p-values of 0.01 and 0.02, 

respectively, while the LD group is not normally distributed with Shapiro-Wilk p-value of 

less than 0.01. We proceed with presenting ANOVA results since they are confirmed by 

a Kruskal-Wallis Test (p-value = 0.83). Additionally, group standard deviations are 

sufficiently similar to satisfy the equal variance assumption for ANOVA. Table J-N and 

Table J-O show the LD group was 1.87% faster than the C group; this difference is not 

statistically significant in a Tukey test. The HD group was 2.41% slower than the C 

group; this difference is not statistically significant in a Tukey test. The HD group was 

4.36% slower than the LD group; this difference is not statistically significant in a Tukey 

test. 

• Contextual Comments. In the analysis, the C group had a mean time of 5.70 

minutes. The LD group had a mean time of 5.60 minutes and was 6 seconds 

faster than the C group. The HD group had a mean time of 5.84 minutes that 

was 2.41% (8 seconds) slower than the C group. Due to the means of the 

groups being so close, the determination could be made that the composition of 

an AAV Crew during the execution of for this task may not have an operational 

impact. 

Conduct Land Recovery by Integration Level. The tables below summarize the 

results of the task, Conduct Land Recovery by Integration Level.

Table J P - Conduct Land Recovery by Integration Level

Metric Integration 

Level 

Sample 

Size Mean SD 

Conduct Land Recovery 

(minutes)

C 22 5.97 1.77

LD 22 5.24 1.06

HD 27 6.04 1.51
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Table J Q - Conduct Land Recovery by Integration Level ANOVA and Tukey Test Results

Metric F Statistic 

(df)

F Test

 P-Value Comparison Difference % 

Difference

P-Value 

(onesided)

80 % 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

Conduct Land 

Recovery 

(minutes)

2.07 (2, 

68) 0.13

LD-C -0.73 -12.24% 0.24 -1.50 0.04 -1.66 0.20

HD-C 0.07 1.15% 0.99 -0.67 0.81 -0.82 0.96

HD-LD 0.80 15.26% 0.15 0.06 1.54 -0.09 1.69

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, between the 

metric’s mean values for the Integration Level.

**Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given confidence 

level on its own.

For the overall time to mount and remove side panels, the LD and HD groups are 

normally distributed as evidenced by Shapiro-Wilk Test p-values of 0.09 and 0.12, 

respectively, while the C group is not normally distributed with Shapiro-Wilk p-value of 

less than 0.01. We proceed with presenting ANOVA results since they are confirmed by 

a Kruskal-Wallis Test (p-value = 0.17). Additionally, group standard deviations are 

sufficiently similar to satisfy the equal variance assumption for ANOVA. Table J-P and 

Table J-Q show the LD group was 12.24% faster than the C group; this difference is not 

statistically significant. The HD group was 1.15% slower than the C group; this 

difference up is not statistically significant. The HD group was 15.26% slower than the 

LD group; this difference is not statistically significant. 

Due to the means of the groups being so close, the determination could be made that 

the composition of an AAV Crew during the execution of for this task may not have an 

operational impact.
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Annex K. 

Combat Engineer (MOS 1371) 

This annex details the Combat Engineer (MOS 1371) portion of the Ground Combat 

Element Integrated Task Force (GCEITF) experiment executed 2 March – 26 April 2015 

at Ranges 107, 108, 110, and 114 aboard the Marine Corps Air-Ground Combat Center

(MCAGCC), Twentynine Palms, CA. The sections outline the Combat Engineer 

Scheme of Maneuver (SOM), Limitations, Deviations, Descriptive Statistics, and 

Modeling Results.

K.1 Scheme of Maneuver

K.1.1 Experimental Cycle Overview

The Combat Engineer assessment of the GCEITF took place in a field environment 

aboard MCAGCC, Twentynine Palms, CA. The assessment consisted of 21 trial cycles,

each of which was a 2-day test cycle, conducted over the course of 55 days. After 

every 4 days of trials, the Marines received 1 recovery day at Camp Wilson. Every 

squad consisted of eight volunteers and a direct-assignment squad leader. Each 

member was trained to fill each billet within the fireteam: fireteam leader, grenadier, 

automatic rifleman, and rifleman. The assessment was executed under the supervision 

of MCOTEA functional test managers and a range officer-in-charge/range safety officer

from the GCEITF. 

K.1.1.1 Experimental Details

The 2-day Combat Engineer assessment replicated offensive and defensive tasks. The 

1371s began each cycle on the offensive tasks, and transitioned to the defensive tasks 

on the second day of the evolution. Three 1371 squads executed each trial cycle: a 

control (C) nonintegrated group, a low-density (LD) group with two females, and a highdensity (HD) group with four females. For fireteam-level tasks, a C group was nonintegrated, an LD group had one female, and an HD group had two females.

Day 1 was executed on Ranges 107 and 108, and consisted of a squad-reinforced 

attack, where engineer fireteams conducted a Bangalore breach. After the squad 

attack, the engineer squads departed to Range 108 to conduct a demolitions raid. 

Day 2 was executed on Ranges 110 and 114, and consisted of squad-level defensive 

actions. The day started with a 7-km forced march from Range 107 to Range 110

wearing an approach load and carrying personal weapons. Then the squad departed 

on foot to the start of the established mine lanes in the vicinity of Range 110 to begin 

the dismounted route clearance. Upon completion of the dismounted route clearance 
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portion, the squad was transported to Range 114 to conduct a cache reduction 

evolution. 

K.1.1.2 Additional Context

Throughout the duration of the assessment, Marines bivouacked at Range 107, 

sleeping in two-man tents. During trial execution, Marines wore/carried prescribed 

loads for each task. Weighing packs each day prior to the 7-km forced march ensured 

consistency. After each trial cycle, the Marines operated under the guidance of the 

platoon leadership, performing minimal physically demanding tasks. The Marines not 

part of an assessed squad conducted the same experimental subtasks after the 

assessed squads to ensure all Marine volunteers were equally fatigued each day. 

Section K.1.3 discussed these tasks in detail.

K.1.2 SOM Experimental Tasks

K.1.2.1 1-km Movement 

Assaulting an enemy position never starts from a static position: First, a movement must 

be conducted to the assault position (AP). The distance from the line of departure to 

the AP is dependent on myriad factors. Based on time and space constraints, this 

distance was set at just under 1 km. Each Combat Engineer fireteam moved this 

distance as quickly as possible while wearing the fighting load and carrying personal 

weapons and a predetermined number of Bangalore torpedo sections. This specific 

task put the Marines under moderate fatigue prior to commencing the attack. 

K.1.2.2 Negotiate an Obstacle

The conduct of an attack often involves reducing or negotiating an obstacle. It is 

common in an urban environment to make entry through a window or over a wall—

some type of obstacle. One of the more difficult tasks is climbing over a wall with a 

fighting load. Each Combat Engineer fireteam negotiated an 8-foot wall (obstacle), 

getting all Marines and equipment over as quickly as possible. 

K.1.2.3 Squad Attack

After negotiating the obstacle, fireteams conducted a 425-meter movement in trace of 

the infantry squad to the Limit of Advance (LOA). Upon arrival at the LOA, the fireteams 

held in place until the Infantry squad completed casualty evacuation (CASEVAC) drills. 

K.1.2.4 Bangalore Breach 

The Combat Engineer fireteams conducted a hasty breach using Bangalore torpedoes

to breach a concertina wire obstacle. The purpose of such a breach, as detailed in the 

Engineer and Utilities Training and Readiness (T&R) Manual, is to “quickly overcome 

unexpected or lightly defended tactical obstacles in order to maintain the momentum of 
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the attack by denying the enemy time to mass forces at the breach sites.” Near the 

conclusion of the squad attack evolution, on arrival at the LOA, the fireteams held in 

place until the infantry squad completed CASEVAC drills. When the signal was given, 

the fireteams sprinted 100 meters with their Bangalore sections to breach a concertina 

wire obstacle. Once the fireteam had all 10 Bangalore sections connected, the 

explosives were dually primed and the Combat Engineers returned to the LOA. Once 

all Marines were verified in a safe position, the explosives were initiated via Modern 

Demolition Initiators (MDI) and the wire obstacles breached.

K.1.2.5 Demolitions Raid 

The demolitions raid portion replicated a friendly force seizing enemy terrain through 

offensive action, such as the squad attack, and then immediately disrupting an enemy’s 

mobility to prevent loss of recently acquired terrain. Upon completion of the Bangalore 

breach, the Combat Engineers returned to the 8-foot obstacle/wall. From this point in 

the trial, the Combat Engineer fireteams came together for a squad-level evolution. 

Awaiting the squad at the 8-foot obstacle/wall was a vehicle delivering the packs and 

explosives required to execute the demolitions raid. Each squad was provided two 40-

lb. shape charges and two 40-lb. cratering charges. The charges were placed in the 

assault packs in addition to the assault load equipment. 

K.1.2.5.1 2.4-km Hike

The Marines began a 2.4-km movement along a prescribed route to Range 108. Four 

Marines carried charges at the start of the movement; those not carrying charges 

carried their assault load. At the approximate halfway point of the 2.4-km movement (a 

point established at which the engineer squad departed the surface danger zone of 

Range 107) the Marines transitioned the load among squad members within their 

individual fireteam. Those who began the movement not carrying a charge now carried 

a charge, and those carrying a charge at the beginning of the movement now carried 

only the assault load and weapon. Once the load change was complete, the squad 

continued along the prescribed route to Range 108. 

K.1.2.5.2 Shape and Crater Charges

Upon arrival at the 2.4-km movement stop point on Range 108, the fireteam carrying the 

40-lb. shaped charges continued movement for another 300 meters to place the shaped 

charges. Once the charges were in place and rigged for detonation, the Marines 

initiated a 7-minute time fuse and returned the 300 meters to the 2.4-km movement stop 

point. Once the shaped charges detonated and the area was cleared by the range 

safety officer (RSO), the fireteam carrying the cratering charges on the 2.4-km 

movement now moved the 300 m to the detonation site to place the explosives. Once 

the charges were in place and rigged for detonation, the Marines initiated a 7-minute 

time-fuse initiation system and returned the 300 meters to the 2.4-km movement stop 
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point. Once the cratering charges detonated, each Marine took a Fatigue and Workload 

survey to assess overall fatigue and workload of the entire offensive task (see GCEITF

Experimental Assessment Plan [EAP], Annex D) while the RSO verified full detonation. 

Once the range was complete, the Marines boarded a vehicle for a return movement to 

Range 107. 

K.1.2.6 7-km Hike

Combat Engineers serving in the Combat Engineer Battalions (CEBs) work in direct 

support, or are often attached to, Infantry units at various levels. The Engineer and 

Utilities T&R Manual states that Combat Engineers must be prepared to “[f]ight as 

provisional infantry, participate in offensive operations such as attacks, raids, movement 

to contact, etc. Defensive operations that include withdrawal, patrolling, check point 

ops, convoy ops, and employment of organic weapons. Additional responsibilities may 

include operations other than war (civil disturbance, TRAP, cordon and search) and 

MOUT (attack, defend, patrol, clear a building, vehicle checkpoint).” As such, Combat 

Engineers must be able to move through all sorts of terrain by foot. Units often train by 

conducting a forced march with an approach load at a sustained rate of march. Due to 

the physically demanding nature of moving under load, each Marine took a Fatigue and 

Workload survey after completion of the 7-km hike. For the assessment, each Combat 

Engineer squad had to move a distance of 7 km as quickly as possible while carrying an 

approach load. At completion of the 7-km hike, Marines took a fatigue and workload 

survey to assess their fatigue and workload during execution (see GCEITF EAP, Annex 

D). 

K.1.2.7 Dismounted Route Clearance

A common responsibility of Combat Engineers, particularly those in the CEB, is to 

ensure mobility of the supported maneuver element. One common method is to 

conduct dismounted route clearance operations. The Engineer and Utilities T&R

Manual states that Combat Engineers will “[c]onduct dismounted route sweep 

operations to detect, investigate, mark, report, and reduce Explosive Hazards (EH) and 

other obstacles along a defined route to enable assured mobility.” Upon arrival to 

Range 110 at the conclusion of the 7-km hike, the squad took a 10-minute operational 

pause to remove their assault pack from the main pack, secure the main packs in a 

vehicle, and conduct an operational check of the mine detectors. 

Once the operational check was complete, the squad departed on foot to the start of the 

established mine lanes in the vicinity of Range 110 to begin the dismounted route 

clearance. Each squad leader had a specific lane assigned, and for each evolution in 

which he led a squad, he had the squad sweep his assigned lane. This assignment 

ensured that there was no overlap by the squads on an individual lane. A randomized 

target roster determined the number of target mines placed within the lane prior to the 
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research evolution. This ensured that the same number of mines was present across 

the three lanes per day, but that the number and location of the mines in each lane 

changed from trial to trial. Upon completion of the dismounted route clearance portion, 

the squad was transported to Range 114 to conduct the cache reduction evolution. 

K.1.2.8 Destroy Captured Arms and Ammunition with Explosives 

A common responsibility of Combat Engineers, particularly those in the CEB, is to 

ensure the destruction of enemy arms and ammunition to prevent their use against 

friendly personnel. The Engineer and Utilities T&R Manual describes this task as: 

“Destroy captured arms and ammunition with demolitions to ensure destruction. 

Examples include: confined gaseous, liquid, and solid propellants; explosives; 

pyrotechnics; chemical and riot-control agents; smokes and incendiaries (including bulk 

explosives); chemical warfare agents; chemical munitions; rockets; guided and ballistic 

missiles; bombs; warheads; mortar rounds; artillery ammunition; small arms 

ammunition; grenades; mines; torpedoes; depth charges; cluster munitions and 

dispensers; demolition charges; and devices and components of the above.” 

For this evolution, once instructed by the squad leader, the Marines loaded artillery 

rounds onto the vehicle. Once the rounds were loaded, the vehicle operator secured 

them for transport while the Combat Engineer squad loaded on vehicles for transport to 

the detonation site on Range 114. Once the Combat Engineer squad and ammunition 

vehicle were present at the point of detonation, the squad dug, emplaced, and rigged

the artillery shells for detonation. Pioneer equipment was provided, and the squad did 

not begin digging until instructed to do so by their squad leader. On order, the Marines 

dug eight reduction pits in which they placed four artillery rounds. Time for this 

evolution ended when all 8 holes were dug and all 32 artillery shells were offloaded from

vehicle and placed in reduction pits, rigged for detonation, and buried. Once the 

assigned tasks were completed, accountability of personnel and equipment was 

conducted, and the charges were initiated via a 7-minute time system. The Marines 

were transported to the safety bunker on Range 114 for the blasts, and once all blasts 

had detonated, Marines took a Fatigue and Workload survey to assess their fatigue and 

workload during execution (see GCEITF EAP, Annex D). At the completion of the 2-day 

cycle, Marines took a cohesion survey to record their cohesion during execution (see 

GCEITF EAP, Annex M).

K.1.3 Loading Events

The loading plan ensured, to the greatest extent possible, equity of physical activity 

among all volunteers throughout the duration of the experimental assessment. Every 

trial and task was conducted in the same manner and sequence to ensure consistency. 

Due to the number of volunteers, a handful of Marines were not part of an assessed 

squad each 2-day cycle. Collaboration with the platoon and company leadership 
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determined that the best method of loading non-assessed Marines was to form them 

into a quasi-squad and have them perform the same tasks as an assessed squad to 

experience the same conditions and physical strain. Minor modifications were permitted 

due to the reduced size of the squad. 

K.1.4 SOM Summary

The Combat Engineer assessment of the GCEITF took place in a field environment 

aboard MCAGCC, Twentynine Palms, CA. The assessment consisted of 21 2-day trial

cycles conducted over the course of 55 days. Each trial cycles consisted of an 

offensive and defensive day. The offensive day involved five tasks based around 

supporting a squad-reinforced attack: 1-km movement, negotiate an obstacle, squad 

attack, Bangalore breach, and a demolitions raid. The defensive day involved three 

tasks: 7-km hike, dismounted route clearance, and destroy captured arms and 

ammunition. During trial execution, Marines rotated through every billet within the 

Combat Engineer squad. 

K.2 Limitations 

K.2.1 1371 Limitations Overview

The GCEITF experiment allowed operationally relevant tasks to occur as naturally as 

possible, while gathering unbiased measurements. Most tasks were performed in a 

manner similar to those in an operational environment, but artificial limitations or 

interruptions were introduced that changed or altered normal performance of a task. 

While these limitations represent a degree of artificiality, they do not detract significantly 

from our ability to generalize the conclusions of this experiment to the performance of 

Marines in a field environment. The following limitations were observed for the 1371 

Combat Engineer assessment. 

K.2.2 Relative Difficulty of Record Test

The Combat Engineer GCEITF assessment gathered data associated with some of the 

most physically demanding tasks of the 1371 MOS within the Combat Engineer 

Battalion (CEB). These tasks in isolation do not fully replicate life experienced by a 

Marine during a typical CEB FEX, not to mention a combat environment. With the 

limited time available to conduct the assessment, only selective 1371 tasks were 

assessed. Due to specific experimental constraints and human-factor considerations, 

other tasks/duties outside of the assessment were minimized. During a typical FEX, it is 

common for Marines to conduct 24-hour operations that include day and nighttime 

operations/patrols, standing firewatch or security post, and conducting continuous

tactical actions. The offensive day SOM took squads approximately 2 hours to 

complete, and the defensive day SOM took approximately 4 hours to complete. Outside 
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the assessed trials, there were minimal tasks required of the volunteers that demanded 

any degree of physical strain. 

Another primary concern designing the Combat Engineer assessment was to ensure 

that it was achievable and sustainable for a 60-day period. The 7-km forced march 

distance was selected based on the amount of training time available prior to the 

assessment; however, many of the loads were decreased. The Combat Engineers did 

not carry ammunition, radios, batteries, or other equipment often required when 

operating in a tactical environment. The Marines were authorized 1 day off after every 4 

days of training. This artificial recovery period is not achievable when conducting 

training or combat operations. 

A final factor affecting the relative difficulty of the record test had to do with the 

intangible physiological impact of the volunteers being able to drop on request (DOR) at 

any point in time. Any time a volunteer dropped during a trial cycle, the squad/team 

performed the following subtasks with fewer personnel. This affected the cohesion of 

each squad and influenced their performance. 

K.3 Deviations 

Deviations to the execution of the Combat Engineer SOM were made and can be found 

in the Experimental Data Report signed May 2015; however, no deviations affected the 

analysis methodology outlined in the EAP. 

K.3.1 7-km Hike Pack Weight

The Test Plan stated that the Combat Engineer Squad would carry the same weight for 

the 7-km hike as the 0311 squad, as established by the Infantry T&R Manual, Annex E. 

Upon further examination of subsequent tasks for the Combat Engineer Squad, it was 

decided to reduce the weight to make it more operationally relevant for the test scenario 

being executed. 

K.3.2 Dismounted Route Clearance

The Test Plan stated that once the Combat Engineers completed the 7-km hike, they 

would be transported to the start point of a 1,500-meter dismounted route clearance 

lane. The original lanes were constructed so that each ended on Range 114, the range 

on which the Cache Reduction evolution would occur. After the first pilot test, the 

dismounted route clearance lanes were moved to the vicinity of Range 110 and reduced 

in distance. 

The movement of the lanes from Range 114 to Range 110 was done to eliminate a 

safety concern of the volunteers transiting an area adjacent to an active demolitions 

range. Once the lanes were moved, they were subsequently reduced due to terrain 

limitations. The sweep lanes had to be reduced in distance in order to keep similar 

conditions for all squads. Beyond 500 meters, terrain on the three lanes became 
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significantly different, so the lanes were reduced in distance to ensure that terrain 

variation was not a factor in the number of mines found by each squad.

K.3.3 Destroy Captured Arms and Ammo

The Test Plan stated that the Combat Engineer squad would dig 4 reduction pits and 

subsequently place 8 155mm artillery shells in each pit for reduction. With the 

appropriate amount of C-4 placed on the rounds for explosive reduction, the net 

explosive weight (NEW) for each of the 4 reduction shots was 196 pounds. In order to 

reduce the fragmentation distance, the Combat Engineer squad instead dug 8 reduction 

pits and placed 4 artillery shells in each reduction pit. This new configuration placed the 

NEW for each of the 8 reduction shots at 98 pounds and reduced the fragmentation 

distance. 

K.4 Data Set Description 

K.4.1 Data Set Overview

The 1371 portion of the experiment consisted of 2 pilot trial cycles and 21 record trial

cycles. The pilot trial cycles were conducted from 2 March 2015 to 6 March 2015. Pilot 

trial cycle data are not used in analysis due to variations in the conduct of the test. We 

based all analysis on the 21 record trial cycles executed from 7 March 2015 to 26 April 

2015.

K.4.2 Record Test Volunteer Participants

At the beginning of the first record trial cycle, there were 18 male 1371 volunteers and 8 

female volunteers. There were several male Marines who voluntarily withdrew, or were 

involuntarily withdrawn, during the execution of the experiment. The final number of 

male 1371 volunteers was 13, and there were no female Marines who left the 

experiment. 

K.4.3 Planned, Executed, and Analyzed Trial Cycles

Table K-1 displays the number of trial cycles planned, executed, and analyzed by task. 

The planned number of trial cycles for the 1371 MOS per Section 7.5.3 of GCEITF EAP 

is 60 trials, or 20 trial cycles per planned integration level (C, LD, and HD) at the squad 

level, and 120 trials or 40 trials per planned integration level at the fireteam level. We 

were able to plan for this number of trial cycles, but due to the number of Marines who 

voluntarily withdrew or were involuntarily withdrawn throughout the experiment, we were 

able to run only one integrated squad (LD or HD), which is why there are so few 

executed LD and HD trial cycles.

Of note, there are several occurrences of missing data for the 7-km hike by individual 

kilometer. GPS data analysis provided the individual kilometer times. Early in the 

experiment, the Garmin GPSs were set to record a volunteer’s position every second. 
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The GPS could not hold all of the data due to the limited storage capacity on the GPS, 

the length of the trial when volunteers executed the 7-km hike, and the follow-on tasks. 

Thus the GPS overwrote the hike data. Once the problem was discovered, the GPSs 

were corrected to record location every two seconds. The exact date of the change is 

unknown.

Table K-1. 1371 Planned, Executed and Analyzed Trial Cycles

Task and Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

trials 

conducted 

Number of 

trials used 

in analysis

Notes

2.4-km Hike; Total Time

C 21 20 20

LD 21 14 14

HD 21 12 12

2.4-km Hike; First Half

C 21 20 19 No data: Apr 16

LD 21 14 13 No data: Mar 9

HD 21 12 12

2.4-km Hike; Last Half

C 21 20 19

LD 21 14 13 No data: Mar 9

HD 21 12 12

Dig Trench/Unload 

Captured Arms and 

Ammo; Total Time

C 21 20 19 Remove Mar 8

LD 21 14 13 Remove Mar 8

HD 21 12 11 Remove Mar 8

Employ Bangalore; 

Breech by FT

C 42 42 39 Remove both Mar 8; Mar 9 not valid

LD 42 30 28 Remove both Mar 8

HD 42 31 29 Remove both Mar 8

Load Captured Arms and 

Ammo

C 21 20 19 Remove Mar 8

LD 21 14 13 Remove Mar 8

HD 21 12 11 Remove Mar 8

Sweep Designated Route 

for Explosive Hazards; 

Percent Detected

C 21 20 20

LD 21 14 14

HD 21 12 12

7-km Hike; Total Time

C 21 20 20

LD 21 14 14

HD 21 12 12

Employ Bangalore; 

Breech by Squad

C 21 20 19 Remove Mar 8; Mar 9 data not valid

LD 21 14 12 Remove Mar 8

HD 21 12 11 Remove Mar 8

Dig Trench/Unload 

Captured Arms and 

Ammo; Dig Trench

C 21 20 19 Remove Mar 8

LD 21 14 13 Remove Mar 8

HD 21 12 11 Remove Mar 8

Dig Trench/Unload 

Captured Arms and 

Ammo; Place Ordnance 

in Trench

C 21 20 19 Remove Mar 8

LD 21 14 13 Remove Mar 8

HD 21 12 11 Remove Mar 8

Dig Trench/Unload 

Captured Arms and 

Ammo; Rig Explosives

C 21 20 19 Remove Mar 8

LD 21 14 13 Remove Mar 8

HD 21 12 11 Remove Mar 8

1-km Hike; by FT

C 42 42 42

LD 42 30 30

HD 42 31 31
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Task and Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

trials 

conducted 

Number of 

trials used 

in analysis

Notes

Negotiate Obstacle; by 

FT

C 42 41 41

LD 42 30 30

HD 42 31 31

7-km Hike; 1km Time

C 21 20 16 No data: Mar 8, Mar 13, Mar 15, Mar 

18

LD 21 14 10 No data: Mar 8, Mar 10, Mar 15, Mar 

18

HD 21 12 8 No data: Mar 8, Mar 13, Mar 15, Mar 

18

7-km Hike; 2km Time

C 21 20 16 No data: Mar 8, Mar 13, Mar 15, Mar 

18

LD 21 14 10 No data: Mar 8, Mar 10, Mar 15, Mar 

18

HD 21 12 8 No data: Mar 8, Mar 13, Mar 15, Mar 

18

7-km Hike; 3km Time

C 21 20 14

No data: Mar 8, Mar 13, Mar 15, Mar 

18. High outlier (GPS error): Mar 20 

and Apr 19

LD 21 14 10 No data: Mar 8, Mar 10, Mar 15, Mar 

18

HD 21 12 8 No data: Mar 8, Mar 13, Mar 15, Mar 

18

7-km Hike; 4km Time

C 21 20 14 No data: Mar 8, Mar 13, Mar 15, Mar 

18. GPS error: Mar 30 and Apr 19

LD 21 14 10 No data: Mar 8, Mar 10, Mar 15, Mar 

18

HD 21 12 8 No data: Mar 8, Mar 13, Mar 15, Mar 

18

7-km Hike; 5km Time

C 21 20 16 No data: Mar 8, Mar 13, Mar 15, Mar 

18

LD 21 14 10 No data: Mar 8, Mar 10, Mar 15, Mar 

18

HD 21 12 8 No data: Mar 8, Mar 13, Mar 15, Mar 

18

7-km Hike; 6km Time

C 21 20 15 No data: Mar 8, Mar 13, Mar 15, Mar 

18. High outlier (GPS error): Mar 28

LD 21 14 10 No data: Mar 8, Mar 10, Mar 15, Mar 

18

HD 21 12 8 No data: Mar 8, Mar 13, Mar 15, Mar 

18

7-km Hike; 7km Time

C 21 20 15 No data: Mar 8, Mar 13, Mar 15, Mar 

18. GPS error: Mar 28

LD 21 14 10 No data: Mar 8, Mar 10, Mar 15, Mar 

18

HD 21 12 8 No data: Mar 8, Mar 13, Mar 15, Mar 

18

K.5 Descriptive and Basic Inferential Statistics 

K.5.1 Descriptive Statistics Overview

Performance metrics were measured during the conduct of common combat engineer

tasks and are indicative of unit-level proficiency during either field exercises or combat 

operations. Only 7 tasks out of 21 tasks are presented in this section. The Appendix to 
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this Annex contains the descriptive statistics for the remainder of the 1371 tasks. The 

words “metric” and “task” are used interchangeably throughout this Annex, since both 

refer to the experimental task.

Each fireteam consisted of four volunteer Marines: the fireteam leader, automatic 

rifleman, grenadier, and rifleman. Each squad consisted of 8 volunteer Marines (two 

fireteams) with a direct assignment (nonvolunteer) squad leader. There were three 

integration levels for all tasks. For squad-level tasks, a Control (C) group was non–

gender integrated, a Low Density (LD) group was gender-integrated with one female 

Marine, and a High Density (HD) group was gender-integrated with two female Marines. 

For fireteam-level tasks, a C group was non–gender integrated, a LD group contained 

one female, and a HD group contained two females. 

This section includes experimental results based on descriptive statistics, analysis of 

variance (ANOVA), Tukey tests (or nonparametric tests as necessary), and scatterplots. 

The subsequent sections will cover each task in detail. Finally, contextual comments, 

additional insights, and subjective comments (as applicable) tying back to each 

experimental task are incorporated. 

Special caution should be taken when comparing similar tasks executed by different 

MOSs within the GCEITF experiment. Comparative analysis may be misleading due to 

differing factors between MOS tasks such as distances, techniques, leadership, load 

carried, group size, and group composition.

K.5.2 1371 Selected Tasks Descriptive Statistics Results

The following two tables display the results for the seven selected 1371 metrics. Table 

K-2 displays the metrics and integration levels with their respective sample sizes, 

means, and standard deviations (SD). 

Table K-3 displays ANOVA and Tukey test results, including metrics and integration 

levels, p-values suggesting statistical significance, integration level elapsed time 

differences, and percentage differences between integration levels. For each task, an 

ANOVA was conducted to compare the three groups simultaneously, and Tukey tests 

were conducted to make pairwise comparisons. If nonparametric tests were needed, 

Table K-3 displays these results instead of ANOVA and Tukey test results. If p-values 

are less than the a priori-determined significance level of 0.10, we conclude that there is 

statistical evidence that the mean time or percent hits was not found the be the same 

across all three groups. 
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Table K-2. 1371 Selected Task Results (Descriptive Statistics)

Metric Integration 

Level Sample Size Mean SD 

2.4-km Hike

(minutes)a

C 20 32.90 3.17

LD 14 33.10 2.23

HD 12 37.47 3.29

2.4-km Hike; First Half

(minutes)b

C 19 17.19 2.93

LD 13 17.88 3.91

HD 12 20.50 3.38

2.4-km Hike; Last Half

(minutes)a

C 19 16.01 1.30

LD 12 15.63 0.78

HD 12 16.63 1.03

Dig Trench, Unload Captured Arms 

& Ammo

(minutes)

C 19 14.90 5.69

LD 13 18.29 6.55

HD 11 17.62 4.99

Employ Bangalore; Breach 

Movements by FT

(minutes)a

C 39 4.52 1.08

LD 28 5.40 1.57

HD 29 5.69 1.14

Load Captured Arms & Ammo

(minutes)

C 19 2.57 0.55

LD 13 2.70 0.45

HD 11 2.58 0.29

Sweep Designated Route for 

Explosive Hazards

(proportion of detected mines)

C 20 0.74 0.20

LD 14 0.82 0.14

HD 12 0.83 0.18 a

.Indicates that there is a statistically significant difference, in either a one-sided or two-sided 

hypothesis test, between integration levels according to ANOVA or a nonparametric 

equivalent test.

b.Indicates contradicting statistical significance results between ANOVA and a nonparametric 

equivalent test.
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Table K-3. 1371 Selected Task ANOVA and Tukey Test Results

Metric

F 

Statistic 

(df)

F Test 

pValueComparison Difference % 

Difference

pValue 80 % 

LCBb 80% 

UCBb 90% LCBb 90% UCBb

2.4-km Hike 10.27

(2, 43) < 0.01a

LD-C 0.20 0.60% 0.98 -1.60 1.99 -1.97 2.37

HD-C 4.57 13.89% < 

0.01a 2.69 6.45 2.30 6.84

HD-LD 4.37 13.22% < 

0.01a 2.35 6.40 1.92 6.82

2.4-km Hike; 

First Halfa 3.71(2, 41) <0.01b

LD-C 0.69 4.02% 0.73c -1.43

c 0.82c -

1.77c 1.18c

HD-C 3.31 19.27% <0.01c 2.33c 4.83c 1.82c 5.08c

HD-LD -2.62 14.66% 0.02c 1.83c 4.62c 1.43c 4.82c

2.4-km Hike; 

Last Half

2.52

(2, 40) 0.09a

LD-C -0.38 -2.37% 0.62 -1.09 0.33 -1.24 0.48

HD-C 0.62 3.85% 0.29 -0.09 1.33 -0.24 1.48

HD-LD -1.00 6.38% 0.08a 0.21 1.78 0.05 1.95

Dig Trench, 

Unload 

Captured 

Arms & 

Ammo

1.54

(2, 40) 0.23

LD-C 3.39 22.77% 0.25 -0.26 7.04 -1.02 7.80

HD-C 2.72 18.24% 0.44 -1.13 6.56 -1.93 7.36

HD-LD 0.67 -3.69% 0.96 -4.83 3.48 -5.70 4.35

Employ 

Bangalore; 

Breach 

Movements 

by FT

8.02

(2, 93) < 0.01a

LD-C 0.87 19.33% 0.02a 0.34 1.41 0.23 1.52

HD-C 1.68 25.81% < 

0.01a 0.63 1.70 0.53 1.81

HD-LD -0.29 5.43% 0.65 -0.28 0.87 -0.40 0.99

Load 

Captured 

Arms & 

Ammo

0.36

(2, 40) 0.70

LD-C 0.14 5.28% 0.70 -0.16 0.43 -0.22 0.49

HD-C 0.01 0.51% 1.00 -0.30 0.32 -0.36 0.39

HD-LD 0.12 -4.53% 0.80 -0.46 0.21 -0.53 0.28

Sweep 

Designated 

Route for 

Explosive 

Hazards

1.35

(2, 43) 0.27

LD-C 0.08 11.43% 0.38 -0.03 0.19 -0.05 0.22

HD-C 0.09 12.47% 0.35 -0.03 0.21 -0.05 0.23

HD-LD -0.01 0.93% 0.99 -0.12 0.13 -0.14 0.16

a.Indicates that there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to ANOVA or a nonparametric equivalent test. b.Tukey intervals have familywise confidence of the indicated percentage; each interval is not of the given 

confidence level on its own.

c.Results presented are from Kruskal-Wallis and Mann-Whitney nonparametric tests due to non-normality.

K.5.2.1 2.4-km Hike

K.5.2.1.1 2.4-km Hike Overview

The demolitions raid portion replicated a friendly force seizing enemy terrain through 

offensive action, and then disrupting an enemy’s mobility to prevent loss of recently 

acquired terrain. For the assessment, each Combat Engineer squad executed a 2.4-km 

movement under load and employed demolitions upon arriving at the objective. The 

recorded time for this task started when the squad departed the Range 107 start point 

and stopped when the squad arrived at the Range 108 stop point. 
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Figure K-1 displays all 1371 2.4-km hike data. All data on the scatterplot are valid for 

analysis

Figure K-1. 2.4-km Hike

The data are normally distributed, as evidenced by the Shapiro-Wilk test that resulted in 

a p-value of 0.13 for the C group, 0.30 for the LD group, and 0.104 for the HD group.

The C group had a mean time of 32.90 minutes. This time is faster (but not statistically 

significantly) than the LD mean time of 33.10 minutes, and statistically significantly 

faster than the HD mean time of 37.47 minutes. These differences result in 0.60% 

(0.20-minute) and 13.89% (4.57-minute) degradations in time for the LD and HD 

groups, respectively. In addition, the LD groups had less variability and HD groups had 

greater variability, as shown by the 0.94-minute and 0.12-minute respective changes in 

SD (3.17 minutes for the C group, 2.23 minutes for the LD group, and 3.29 minutes for 

the HD group). The LD group was statistically significantly faster than the HD group. 

There was a 4.37% degradation in hike time from the LD to HD group. See Table K-2

and Table K-3 for detailed analytical results.

K.5.2.1.2 2.4-km Hike Contextual Comments

Analysis shows that the C group had a mean time of 32.90 minutes, while the LD and 

HD groups had mean times of 33.10 minutes (12 seconds slower than the C group) and 

37.47 minutes (4:34 minutes slower than the C group), respectively.
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K.5.2.1.3 2.4-km Hike Additional Insights

Time is critical when a unit is moving into position with the intent to deploy demolitions, 

and it can be the determining factor in the success of the mission. Marine Corps 

Doctrinal Publications (MCDP) consistently emphasize the importance of speed. MCDP 

1-3: Tactics devotes an entire chapter to “Being Faster,” which states: “Physical speed, 

moving more miles per hour, is a powerful weapon in itself.” MCDP-6: Command and 

Control also speaks to speed relative to the enemy: “The speed differential does not 

necessarily have to be a large one: a small advantage exploited repeatedly can quickly 

lead to decisive results.” A 2.4-km hike movement is meant to be executed quickly, 

without delay. Faster results are favorable, because reaching the objective to employ 

demolitions is critical to the mission.

K.5.2.1.4 2.4-km Hike Subjective Comments

For subjective comments relating to this task, see the Appendix. 

K.5.2.2 2.4-km Hike First Half

K.5.2.2.1 2.4-km Hike First Half Overview

Figure K-2 displays all 2.4-km hike/first data. All data on the scatterplot are valid for 

analysis.

Figure K-2. 2.4-km Hike First Half

The C group and HD group data are normally distributed, as evidenced by the ShapiroWilk test that resulted in a p-value of 0.17 for the C group and 0.62 for the HD group. 

However, the LD data are not normally distributed (p-value <0.01). 
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The C group had a mean time of 17.19 minutes. This time is faster (but not statistically 

significantly) than the LD mean time of 17.88 minutes, and statistically significantly 

faster than the HD mean time of 20.50 minutes. These differences result in 4.02% 

(0.69-minute) and 19.27% (3.31-minute) degradations in time for the LD and HD 

groups, respectively. The LD group was statistically significantly faster than the HD 

group only in a one-sided t-test, but in both one- and two-sided Mann-Whitney tests. 

There was a 14.66% (2.62-minute) degradation in hike time from the LD to HD group. 

Because of a lack of normality, we recommend using the Mann-Whitney test results 

(reported in Table K-3). However, the conflict of parametric and nonparametric results 

suggests that further study of this task is warranted.

In addition, the LD and HD groups had greater variability, as shown by the 0.98-minute 

and 0.45-minute respective changes in SD (2.93 minutes for the C group, 3.91 minutes 

for the LD group, and 3.38 minutes for the HD group). See Table K-2 and Table K-3 for 

detailed analytical results.

K.5.2.2.2 2.4-km Hike First Half Contextual Comments

None. 

K.5.2.2.3 2.4-km Hike First Half Additional Insights

None.

K.5.2.2.4 2.4-km Hike First Half Subjective Comments

For subjective comments relating to this task, see the Appendix. 

K.5.2.3 2.4-km Hike Last Half

K.5.2.3.1 2.4-km Hike Last Overview

Figure K-3 displays all 2.4-km hike last half data. All data on the scatter plot are valid 

for analysis.
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Figure K-3. 2.4-km Hike/Last Half

The data are normally distributed as evidenced by the Shapiro-Wilk test that resulted in 

a p-value of 0.12 for the C group, 0.58 for the LD group, and 0.43 for the HD group. 

The C group had a mean time of 16.01 minutes. This time is slower (but not statistically 

significantly) than the LD mean time of 15.63 minutes, and faster (but not statistically 

significantly) than the HD mean time of 16.63 minutes. These differences result in 

2.37% (0.38-minute) improvement in time for the LD group and 3.85% (0.62-minute) 

degradation in time for the HD group. In addition, the LD and HD groups had less 

variability, as shown by the 0.52-minute and 0.27-minute respective changes in SD 

(1.30 minutes for the C group, 0.78 minutes for the LD group, and 1.03 minutes for the 

HD group). The LD group was statistically significantly faster than the HD group. There 

was a 6.38% (1.00-minute) degradation in hike time from the LD to HD group. See 

Table K-2 and Table K-3 for detailed analytical results.

K.5.2.3.2 2.4-km Hike Last Half Contextual Comments

None.

K.5.2.3.3 2.4-km Hike Last Half Additional Insights

None.

K.5.2.3.4 2.4-km Hike Last Half Subjective Comments

For subjective comments relating to this task, see the Appendix. 
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K.5.2.4 Dig Trench, Unload Captured Arms and Ammo, Rig for Detonation

K.5.2.4.1 Dig Trench, Unload Captured Arms and Ammo, Rig for Detonation Overview

A common responsibility of Combat Engineers—particularly those in the currently 

closed CEB—is to ensure the destruction of enemy arms and ammunition to prevent 

their use against friendly personnel. For the assessment, each Combat Engineer squad 

had to dig 8 reduction pits to specified dimensions, unload 32 155-mm artillery shells 

from the MTVR, place them in the reduction pits, rig for detonation, and bury the 

charges as quickly as possible. Time began when the squads began digging the 

trenches and ended once the 155-mm shells were buried.

This task is broken down into the following sub-tasks: 

• Dig Trench 

• Place Explosives 

• Rig for Detonation.

Figure K-4 displays all destroy-captured-arms-and-ammo-with-explosives data. All data 

on the scatterplot are valid for analysis.

Figure K-4. Dig Trench, Unload Captured Arms and Ammo, Rig for Detonation

The LD and HD group data are normally distributed, as evidenced by the Shapiro-Wilk 

test that resulted in a p-value of 0.105 for the LD group and 0.75 for the HD group. 

However, the results for the C group do not appear normal with a p-value < 0.01. 
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Because nonparametric results are consistent with ANOVA results for this task, we 

present only the ANOVA results below.

The C group had a mean time of 14.90 minutes. This time is faster (but not statistically 

significantly) than the LD mean time of 18.29 minutes and the HD mean time of 17.62 

minutes. These differences result in 22.77% (3.39-minute) and 18.24% (2.72-minute) 

degradations in time for the LD and HD groups, respectively. In addition, the LD group 

had greater variability and the HD groups had less variability, as shown by the 0.86-

minute and 0.70-minute respective changes in SD (5.69 minutes for the C group, 6.55 

minutes for the LD group, and 4.99 minutes for the HD group). The LD group was 

slower (but not statistically significantly) than the HD group. There was a 3.69% (0.67-

minute) improvement in time from the LD to HD group. See Table K-2 and Table K-3

for detailed analytical results.

K.5.2.4.2 Dig Trench, Unload Captured Arms and Ammo, Rig for Detonation Contextual 

Comments

None.

K.5.2.4.3 Dig Trench, Unload Captured Arms and Ammo, Rig for Detonation Additional 

Insights

In an operational environment, the time it takes a unit to accomplish this type of task 

corresponds with time in a relatively static position, in the open and away from cover 

from indirect fires. Faster times are favorable in the performance of this task to limit 

exposure and the possibility of taking casualties. Loading and transferring captured 

ammunitions in an expeditious manner is a key aspect of mission accomplishment.

K.5.2.4.4 Dig Trench, Unload Captured Arms and Ammo, Rig for Detonation Subjective 

Comments

For subjective comments relating to this task, see the Appendix. 

K.5.2.5 Employ Bangalore

K.5.2.5.1 Employ Bangalore Overview 

The Combat Engineer fireteams used Bangalore torpedoes to breach a concertina wire 

obstacle. For the assessment, each four-Marine Combat Engineer fireteam executed a 

hasty Bangalore breach as quickly as possible. The recorded time began on the 

command “Breach, Breach, Breach,” and ended when the last Marine was prone at the 

LOA.

Figure K-5 displays all 1371 Employ Bangalore data. Data for all groups on March 7 

were invalid because these data points were high outliers due to the learning curve. In 

addition, data for the C group on March 9 were invalid due to a test incident. With the 

exception of these data points, all data on the scatterplot are valid for analysis.
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Figure K-5. Employ Bangalore

For this task, sample sizes are sufficiently large (n > 30) to satisfy the normality 

assumption for ANOVA.

The C group had a mean time of 4.50 minutes. This time is statistically significantly 

faster than the LD mean time of 5.40 minutes and the HD mean time of 5.69 minutes. 

These differences result in 19.33% (0.87-minute) and 25.81% (1.68-minute) 

degradations in time for the LD and HD groups, respectively. In addition, the LD group 

had greater variability, as shown by the 0.49-minute increase in SD (1.08 minutes for 

the C group, 1.57 minutes for the LD group). The LD group was faster, on average, 

than the HD group. There was a 5.43% (0.29-minute) degradation in hike time from the 

LD to the HD group, but this difference is not statistically significant. See Table K-2 and 

Table K-3 for detailed analytical results.

K.5.2.5.2 Employ Bangalore Contextual Comments

Although only the HD group showed a statistical significance, the execution of a breach 

is a critical point in combat operations and time is critical. Employing a Bangalore and 

executing a breach requires a unit to overcome enemy obstacles rapidly and maintain 

friendly momentum. According to Sun Tzu: “Speed is the essence of war. Take 

advantage of the enemy’s unpreparedness; travel by unexpected routes and strike him 

where he has taken no precautions” (MCDP-1, p. 69). Speed and surprise are crucial to 

success. 

Faster results are more desirable because the longer a unit spends conducting a 

breach, the longer it is exposed to the effects of concentrated enemy fires and the 
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greater the propensity of increased casualties or potential mission failure. The ANOVA

and other statistical tests support the claim that integrated Combat Engineer units, on 

average, would take longer to execute a breach when compared to a nonintegrated 

Combat Engineer unit.

K.5.2.5.3 Employ Bangalore Additional Insights

None.

K.5.2.5.4 Employ Bangalore Subjective Comments

For subjective comments relating to this task, see the Appendix. 

K.5.2.6 Load Captured Arms and Ammo

K.5.2.6.1 Load Captured Arms and Ammo Overview

A common responsibility of Combat Engineers—particularly those in the closed CEB—

is to ensure the destruction of enemy arms and ammunition to prevent their use against 

friendly personnel. Stockpiles of enemy arms require movement to a reduction site to 

prevent unnecessary collateral damage. For the assessment, each Combat Engineer 

squad loaded 32 155-mm artillery shells from ground level to the back of a 7-ton 

Medium Tactical Vehicle Recovery (MTVR) vehicle as quickly as possible. Time for this 

task began when the first Marine began moving rounds and ended when all rounds 

were on the MTVR.

Figure K-6 displays all load-captured-arms-and-ammo data. All data on the scatterplot 

are valid for analysis.
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Figure K-6. Load Captured Arms and Ammo

The data are normally distributed as evidenced by the Shapiro-Wilk test that resulted in 

a p-value of 0.29 for the C group, 0.43 for the LD group, and 0.17 for the HD group.

The C group had a mean time of 2.57 minutes. This time is faster (but not statistically 

significantly) than the LD mean time of 2.70 minutes and the HD mean time of 2.58 

minutes. These differences result in 5.28% (0.14-minute) and 0.51% (0.01-minute) 

degradations in time for the LD and HD groups, respectively. In addition, the LD and

HD group had less variability, as shown by the 0.10-minute and 0.26-minute respective 

changes in SD (0.55 minutes for the C group, 0.45 minutes for the LD group, and 0.29 

minutes for the HD group). The LD group was slower (but not statistically significantly) 

than the HD group. There was a 4.53% (0.12-minute) improvement in time from the LD 

to the HD group. See Table K-2 and Table K-3 for detailed analytical results.

K.5.2.6.2 Load Captured Arms and Ammo Contextual Comments

None.

K.5.2.6.3 Load Captured Arms and Ammo Additional Insights

In an operational environment, the time it takes a unit to accomplish this type of task 

corresponds with time in a relatively static position, likely in the open and away from 

cover from indirect fires. Faster times are favorable in the performance of this task to 

limit exposure and the possibility of taking casualties. Loading and transferring
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captured ammunitions in an expeditious manner is a key aspect of accomplishing this 

mission. 

K.5.2.6.4 Load Captured Arms and Ammo Subjective Comments

Although the times are not statistically significant, it is important to note that during the 

execution of this particular task there were numerous observations made of males in the 

integrated groups shouldering a disproportionate amount of the physical load to 

accomplish the mission. There were 34 total GCEITF direct assignment subjective 

comments regarding this task. Of the 34 comments, there were 16 comments regarding 

males in an integrated squad (either LD or HD) compensating for other Marines or doing 

the majority of the work. Of the 34 comments, there were 6 comments noting females 

who required assistance because they were unable to lift and push the rounds up the 

height of the vehicle bed by themselves.

There was no prescribed method for the squad to accomplish this task to prevent the 

introduction of operational artificiality, but it was observed that males assumed the more 

physically demanding task of lifting the rounds to the bed of the vehicle, and that 

females, when attempting this same task, could not do so on their own. 

For additional subjective comments relating to this task, see the Appendix. 

K.5.2.7 Sweep Designated Route for Explosive Hazards 

K.5.2.7.1 Sweep Designated Route for Explosive Hazards Overview

A common responsibility of Combat Engineers—particularly those in the closed Combat 

Engineer Battalion—is to ensure the mobility of the supported maneuver element. One 

method is to conduct dismounted route clearance operations. For the assessment, 

each Combat Engineer squad swept a 500-meter route and located buried inert mines. 

There was no time component to this task.

Figure K-7 displays all sweep-designated-route-for-explosive-hazards data. All data on 

the scatterplot are valid for analysis.
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Figure K-7. Sweep Designated Route for Explosive Hazards

The data are normally distributed, as evidenced by the Shapiro-Wilk test that resulted in 

a p-value of 0.17 for the C group, 0.02 for the LD group, and 0.48 for the HD group.

The C group had a mean proportion of mines found of 0.74. This proportion is lower 

(but not statistically significantly) than the LD mean proportion of 0.82 and the HD mean 

proportion of 0.83. These differences result in 11.43% (0.08–percentage point) and 

12.47% (0.09–percentage point) degradations in time for the LD and HD groups, 

respectively. The LD group proportion was lower (but not statistically significantly) than 

the HD group. There was a 0.93% (0.01–percentage point) increase in proportion from 

the LD to the HD group. See Table K-2 and Table K-3 for detailed analytical results. 

K.5.2.7.2 Sweep Designated Route for Explosive Hazards Contextual Comments

From an operational standpoint, the most favorable results are the ones with the highest

find percentage. If an explosive hazard is not identified and mitigated by the route 

clearance element, a follow-on unit may trigger it, resulting in injury or death. The ability 

for Combat Engineers to locate and eliminate explosive hazards is critical to the 

mission; a higher find percentage is important as a contributor to the success of the 

mission. 

K.5.2.7.3 Sweep Designated Route for Explosive Hazards Additional Insights

None.
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K.5.2.7.4 Sweep Designated Route for Explosive Hazards Subjective Comments

For subjective comments relating to this task, see the Appendix. 

K.6 Statistical Modeling Results 

K.6.1 Statistical Modeling Overview

The previous section discussed results only as they pertain to differences due to 

integration level alone. The goal of statistical modeling as applied here is to estimate 

simultaneously the effect of gender integration levels and other relevant variables on 

Engineer squad performance. Refer to the Methodology Annex for a broad overview of 

the analysis plan and the variables used in the models.

For the same seven selected tasks described in the previous section, this section 

presents an overview of the analysis and results, and then presents the modeling 

results for each of the tasks.

For each task, we describe the significant variables in the model and whether these 

variables are either positively or negatively correlated with the result. A negative 

correlation indicates that an increase in that variable will result in a decrease in the 

response variable, which is a desired outcome for elapsed time but not a desired 

outcome for the percent of mines found outcome. The results report where certain

patch numbers are significant for a given variable. The experiment tracked Marines 

within the Engineer squad by a patch number that associated their random position 

within the squad to a specific billet. Table K-4 displays the patch numbers and 

associated billet titles for the Combat Engineer squad.

Table K-4. Patch Numbers and Billet titles for the Combat Engineer Squad

Patch Number Billet Title

1 FT 1 Fireteam Leader

2 FT 1 Automatic Rifleman

3 FT 1 Grenadier

4 FT 1 Rifleman

5 FT 2 Fireteam Leader

6 FT 2 Automatic Rifleman

7 FT 2 Grenadier

8 FT 2 Rifleman

K.6.2 1371 Method of Analysis

Due to the small number of trials, a mixed-effects model with all engineer squad

members and all types of personnel data did not work for the 1371 dataset. Thus we 
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model each personnel variable with integration level separately with a random effect for

who filled each position within the engineer squad. For example, age for each member 

of the engineer squad (eight variables) and integration level are modeled with the result 

(response time or percentage of mines found) as the response variable. Where 

maximum likelihood estimation converged, the Akaike information criterion (AIC) was 

used for variable selection. Otherwise, we comment on the significance of individual 

variables in the full model. Variables reported as significant are concluded to be 

significant based on at least a one-sided test.

K.6.3 1371 Selected Tasks Overall Modeling Results

There are no personnel data variables that are both statistically significant and have a 

practical impact to the model. Each time personnel data variables are statistically 

significant in a model, their effects are practically negligible, conflicting, and/or 

incomplete for the Engineer squad (i.e., there are no tasks for which a variable is 

significant for all members of the Combat Engineer squad). 

Integration level is significant in the final model for the following selected tasks: 2.4-km 

hike, 2.4-km hike second half, Bangalore breach, and load captured arms and ammo. 

For each of these tasks, modeling the random effects for the individuals participating in 

the task results in changes from the initial results in the descriptive statistics. Each 

respective task paragraph describes these changes. For all other tasks, AIC chose the 

intercept model. See Section K.5 for descriptive statistics for these tasks.

K.6.3.1 2.4-km Hike

We model elapsed time for the 2.4-km hike as a function of each personnel variable and 

integration level in a separate mixed model. The covariates in each model are the 

values of each personnel variable for each patch number, integration level, and a 

random effect of who filled each position on the squad. For each model, we report 

statistically significant positive and negative correlations, and whether we observe any 

patterns.

The models for the following variables do not converge: 

• PFT crunches

• CFT MANUF

• Rifle score. 

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Squad leader

• Age
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• Height

• Weight

• AFQT score

• GT score

• PFT 3-mile run. 

The LD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• GT score

• CFT MTC. 

Both the HD and the LD integration levels are significant and negatively correlated with 

the response for the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the 2.4-km hike time: 

• Age of patch 1

• Height of patches 2 and 3

• AFQT score of patch 2

• GT score of patch 3

• CFT MTC of patches 1, 2, 5, 6, and 7. 

The following variables are significant in their respective models and are negatively 

correlated with the 2.4-km hike time: 

• Age of patches 2 and 4

• Weight of patch 4

• AFQT score of patches 6 and 8

• GT score of patches 2, 4, 6 and 7. 

The following personnel variables have no significant variables in their respective 

models:

• Number of female carries.

Because we did not identify any discernable patterns in the effects of the personnel 

variables, and because their effects are often negligible, our final model includes 

integration level with only HD significant with a difference of 4.04 minutes when 
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compared to the C group. The comparison yields a statistically significant p-value of 

<0.01. This difference is a decrease from the 4.57 difference found in the descriptive 

statistics, which is a 11.59% change.

K.6.3.2 2.4-km Hike First Half

We model elapsed time for the 2.4-km hike first half as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and 

a random effect of who filled each position on the squad. For each model, we report 

statistically significant positive and negative correlations, and whether we observe any 

patterns.

The models for the following variables do not converge: 

• Age

• PFT crunches

• PFT 3-mile run

• Rifle score. 

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Squad leader

• Height

• AFQT score

• GT score. 

The LD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• GT score.

Both the HD and the LD integration levels are significant and negatively correlated with 

the response for the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the 2.4-km hike first half time: 

• Height of patch 3

• GT score of patch 3

• CFT MTC of patches 1, 5, and 7
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• CFT MANUF of patches 1 and 2. 

The following variables are significant in their respective models and are negatively 

correlated with the 2.4-km hike first half time: 

• Weight of patches 1, 2, 3, 4, and 7

• AFQT score of patch 8

• GT score of patches 4, 6, and 7

• CFT MANUF of patch 5. 

The following personnel variables have no significant variables in their respective 

models:

• None.

Because we did not identify any discernable patterns in the effects of the personnel 

variables, and because their effects are often negligible, our final model includes 

integration level only where HD has a difference of 3.18 minutes when compared to the

C group. The comparison yields a statistically significant p-value of <0.01. This 

difference is a decrease from the 3.31-minute difference identified in the descriptive 

statistics, which is a 3.93% change. However, AIC prefers the intercept model. Refer 

to Section K.5.2.2 to see the ANOVA summary for this task.

K.6.3.3 2.4-km Hike/Last Half

We model elapsed time for the 2.4-km hike/second half) as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and 

a random effect of who filled each position on the squad. For each model, we report 

statistically significant positive and negative correlations, and whether we observe any 

patterns.

The models for the following variables do not converge: 

• Age

• PFT crunches

• PFT 3-mile run. 

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Squad leader

• Height

• Weight
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• AFQT score 

• GT score

• Rifle score. 

The LD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• GT score. 

Both the HD and the LD integration levels are significant and negatively correlated with 

the response for the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the 2.4-km hike/last half time: 

• GT score of patches 3 and 8

• CFT MTC of patches 1, 2, and 6

• Rifle score of patches 1 and 6. 

The following variables are significant in their respective models and are negatively 

correlated with the 2.4-km hike/last half time: 

• Weight of patch 4

• GT score of patches 4 and 7

• CFT MANUF of patches 1 and 3

• Rifle score of patch 2. 

The following personnel variables have no significant variables in their respective 

models:

• None.

Because we did not identify any discernable patterns in the effects of the personnel 

variables, and because their effects are often negligible, our final model includes 

integration level only where HD has a difference of 0.73 minutes when compared to the

C group. The comparison yields a statistically significant p-value of 0.08. This 

difference is an increase from the 0.62-minute difference identified in the descriptive 

statistics, which is a 17.74% change.

K.6.3.4 Dig Trench, Unload Captured Arms and Ammo

We model elapsed time for the dig trench, unload captured arms and ammo as a 

function of each personnel variable and integration level in a separate mixed model. 
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The covariates in each model are the values of each personnel variable for each patch 

number, integration level, and a random effect of who filled each position on the squad. 

For each model, we report statistically significant positive and negative correlations, and 

whether we observe any patterns.

The models for the following variables do not converge: 

• Height

• CFT MTC

• PFT crunches. 

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Squad leader. 

The LD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Squad leader

• Age

• GT score

• CFT MANUF

• PFT 3-mile run 

• Rifle score. 

Both the HD and the LD integration levels are significant and negatively correlated with 

the response for the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the dig trench, unload captured arms and ammo time: 

• Squad leader

• CFT MANUF of patch 6. 

The following variables are significant in their respective models and are negatively 

correlated with the dig trench, unload captured arms and ammo time: 

• Age of patches 4, 7 and 8

• Weight of patches 2, 4, and 7

• AFQT score of patches 1 and 7
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• GT score of patch 1

• CFT MANUF time of patch 7. 

The following personnel variables have no significant variables in their respective 

models:

• None.

Because we did not identify any discernable patterns in the effects of the personnel 

variables, and because their effects are often negligible, our final model includes 

integration level only where LD has a difference of 2.62 minutes when compared to the

C group. The comparison yields a statistically significant p-value of 0.15 in a one-way 

test. However, AIC prefers the intercept model. Refer to Section K.5.2.4 to see the

ANOVA summary for this task. 

K.6.3.5 Employ Bangalore

We model elapsed time for the Bangalore breach as a function of each personnel 

variable and integration level in a separate mixed model. The covariates in each model 

are the values of each personnel variable for each patch number, integration level, and 

a random effect of who filled each position on the squad. For each model, we report 

statistically significant positive and negative correlations, and whether we observe any 

patterns.

The models for the following variables do not converge: 

• None.

Both the HD and the LD integration levels are significant and positively correlated with 

the response for the models that include the following personnel variables: 

• Squad leader

• Age

• AFQT score

• GT score

• PFT crunches

• PFT three-mile

• Rifle score. 

Both the HD and the LD integration levels are significant and negatively correlated with 

the response for the models that include the following personnel variables: 

• None. 
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The following personnel variables are significant in their respective models and are 

positively correlated with the Bangalore breach time: 

• Age of patch 2

• CFT MTC of patches 1, 2, and 3

• CFT MANUF of patches 3 and 4

• PFT 3-mile run of patch 1. 

The following variables are significant in their respective models and are negatively 

correlated with the Bangalore breach time: 

• Age of patch 4

• Height of patches 2, 3, and 4

• Weight of patches 1, 2, 3, and 4

• GT score of patch 4

• PFT crunches of patch 1

• Rifle score of patch 1. 

The following personnel variables have no significant variables in their respective 

models:

• None.

Because we did not identify any discernable patterns in the effects of the personnel 

variables, and because their effects are often negligible, our final model includes 

integration level only where HD has a difference of 1.08 minutes when compared to the

C group. The comparison yields a statistically significant p-value of <0.01. This 

difference is a decrease from the 1.68 minutes identified in the descriptive statistics, 

which is a 35.71% change. The LD integration level has a difference of 0.74 minutes 

when compared to the C group and a p-value of 0.01. This difference is a decrease 

from the 0.87 difference found in the descriptive statistics, which is a 14.94% change.

K.6.3.6 Load Captured Arms and Ammo

We model elapsed time for the load captured arms and ammo as a function of each 

personnel variable and integration level in a separate mixed model. The covariates in 

each model are the values of each personnel variable for each patch number, 

integration level, and a random effect of who filled each position on the squad. For 

each model, we report statistically significant positive and negative correlations, and 

whether we observe any patterns.

The models for the following variables do not converge: 
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• GT score

• PFT 3-mile run. 

The HD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Weight. 

The LD integration level is significant and positively correlated with the response for the 

models that include the following personnel variables: 

• Squad leader

• Age

• Height

• AFQT score

• CFT MTC

• Rifle score. 

Both the HD and the LD integration levels are significant and negatively correlated with 

the response for the models that include the following personnel variables: 

• PFT crunches. 

The following personnel variables are significant in their respective models and are 

positively correlated with the load captured arms and ammo time: 

• Age of patches 4, 6, and 7

• CFT MANUF of patches 2, 4, and 6

• PFT crunches of patches 4, 6, and 7. 

The following variables are significant in their respective models and are negatively 

correlated with the load captured arms and ammo time: 

• Age of patch 8

• Height of patches 7 and 8

• Weight of patches 1, 3, and 5

• AFQT score of patches 1, 5, 6 and 8

• CFT MANUF of patch 8

• PFT crunches of patches 2 and 5

• Rifle score of patch 5. 
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The following personnel variables have no significant variables in their respective 

models:

• None.

Because we did not identify any discernable patterns in the effects of the personnel 

variables, and because their effects are often negligible, our final model includes 

integration level only where LD has a difference of 0.30 minutes when compared to a C 

group. The comparison yields a statistically significant p-value of 0.04. This difference 

is greater than the 0.14-minute difference found in the descriptive statistics, which is a 

16% change.

K.6.3.7 Sweep Designated Route for Explosive Hazards

We model proportion sweep designated route for explosives as a function of each 

personnel variable and integration level in a separate mixed model. The covariates in 

each model are the values of each personnel variable for each patch number, 

integration level, and a random effect of who filled each position on the squad. For 

each model, we report statistically significant positive and negative correlations, and 

whether we observe any patterns.

The models for the following variables do not converge: 

• Weight

• PFT crunches. 

Both the HD and the LD integration levels are significant and positively correlated with 

the response for the models that include the following personnel variables: 

• Age. 

Both the HD and the LD integration levels are significant and negatively correlated with 

the response for the models that include the following personnel variables: 

• None. 

The following personnel variables are significant in their respective models and are 

positively correlated with the proportion of mines found: 

• Age of patches 3, 7 and 8

• GT score of patches 6 and 8

• CFT MANUF for patch 3

• PFT 3-mile run of patches 3, 4, 6 and 8. 

The following variables are significant in their respective models and are negatively 

correlated with the proportion of mines found: 
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• GT score of patches 4 and 7

• Height of patches 1 and 3. 

The following personnel variables have no significant variables in their respective 

models:

• Squad leader

• CFT MTC

• Rifle score. 

Because we did not identify any discernable patterns in the effects of the personnel 

variables, and because their effects are often negligible, our final model includes 

integration level only. AIC prefers only the intercept in the final model. Refer to Section 

K.5.2.7 to see the ANOVA summary for this task.
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Appendix to Annex K

1371 Supplemental Information

This appendix provides supplemental information for the 1371 portion of the GCE ITF 

experiment. It provides additional descriptive and basic inferential statistics not 

described in Annex K. 

Section 1: GCE ITF Leadership Subjective Comments

The GCE ITF leadership provided comments on their observations of the experiment 

throughout its execution. Table K A displays a summary of these comments broken 

down by task, integration level, gender, and type of comment.

Table K A – Summary of GCE ITF Leadership Comments

Section 2. Additional Task Basic and Inferential Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. The experiment included a number of tasks and associated metrics 

conducted to enhance operational realism and maintain consistent application of the 

experimental process. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

This section presents results for 13 additional 1371 tasks. Annex K contains the 

descriptive statistics for the remainder of the 1371 tasks. The words “metric” and “task” 

are used interchangeably throughout this appendix; they both refer to the experimental 

task. 

The two tables below display the results for 13 additional 1371 metrics. Table K B

displays the metrics and integration levels with their respective sample sizes, means, 

and standard deviations. Table K C displays ANOVA and Tukey Test results, including 

metrics and integration levels, p-values suggesting statistical significance, integrationlevel elapsed-time differences, and percentage differences between integration levels. 

For each task, an ANOVA was conducted to compare the three groups and Tukey Tests 

were conducted to compare each pair of two groups. If non-parametric tests were 

needed, Table K C displays these results instead of ANOVA and Tukey Test results. If 

Task and Metric 

Description Gender Total

C LD HD Total C LD HD Total C LD HD Total C LD HD Total C LD HD Total C LD HD Total C LD HD Total C LD HD Total

M 6 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6

F 0 0 3 3 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4

M 0 0 0 0 0 0 0 0 0 0 0 0 11 5 1 17 0 7 3 10 0 0 0 0 0 0 0 0 1 0 0 1 28

F 0 0 0 0 0 0 0 0 0 2 3 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5

M 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 3

F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

F 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

M 4 1 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 6

F 0 1 9 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10

No category Falling behind/slowing 

movement

Requesting extra 

breaks

Requires extra 

assistance Needs no assistance Compensating for another Marine Gear pass off

2.4-km Hike

Load Captured Arms and 

Ammo

Other

7-km Hike

Sweep Designated Route for 

Explosive Hazards

Dig Trench/Unload Captured 

Arms and Ammo
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p-values are less than the a-priori determined significance level of 0.10, we conclude 

that there is statistical evidence that the result was not found to be the same across all 

three groups. We present basic inferential statistics for three additional 1371 tasks.

Table K B. 1371 Test Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference 

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

7-km Hike

C 20 84.06 6.17

LD 14 88.32 3.91 5.07% 10.95% 5.59%

HD 12 93.26 6.86

7-km Hike; First 

km

C 16 9.65 0.46

LD 10 9.85 0.66 2.11% 3.21% 1.08%

HD 8 9.96 0.39

7-km Hike; 

Second km

C 16 9.65 0.54

LD 10 10.21 0.64 5.80% 6.62% 0.78%

HD 8 10.29 0.61

7-km Hike; Third 

km

C 14 9.31 0.46

LD 10 9.78 0.69 5.05% 4.61% -0.42%

HD 8 9.74 0.58

7-km Hike; Fourth 

km

C 14 9.69 0.43

LD 10 10.19 0.71 5.15% 10.80% 5.38%

HD 8 10.74 1.37

7-km Hike; Fifth 

km

C 16 12.73 3.94

LD 10 14.60 5.72 14.67% 57.65% 37.49%

HD 8 20.07 3.90

7-km Hike; Sixth 

km

C 15 15.98 4.08

LD 10 17.87 4.78 11.85% -18.60% -27.22%

HD 8 13.01 4.03

7-km Hike; 

Seventh km

C 15 11.64 1.74

LD 10 11.39 0.71 -2.14% 2.23% 4.47%

HD 8 11.90 0.85

1-km Hike; by FT

C 42 9.42 1.18

LD 30 10.01 0.65 6.29% 9.63% 3.14%

HD 31 10.33 0.81

Dig Trench/Unload 

Captured Arms & 

Ammo; Dig Trench

C 19 5.07 2.76

LD 13 6.24 3.42 23.12% 19.62% -2.84%

HD 11 6.07 2.88

Dig Trench/Unload 

Captured Arms & 

Ammo; Place 

Ordnance in 

Trench

C 19 5.73 1.92

36.35% 13.59% -16.69% LD 13 7.81 3.17

HD 11 6.50 1.87
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Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference 

(LD-C)

% 

Difference

(HD-C)

% 

Difference

(HD-LD)

Dig Trench/Unload 

Captured Arms & 

Ammo; Rig for 

Detonation

C 19 4.10 1.91

LD 12 4.59 1.70 11.76% 20.03% 10.08%

HD 11 5.05 1.60

Negotiate 

Obstacle; by FT

C 41 1.50 0.40

LD 28 1.97 0.89 31.87% 52.48% 15.63%

HD 30 2.28 1.24

Table K C. Engineers ANOVA and Tukey Test Results. 

Metric

F 

Statistic

(df)

F Test 

P-Value Comparison Difference P-Value 80 % 

LCB**

80% 

UCB**

90% 

LCB**

90% 

UCB**

7-km Hike 9.58

(2, 43) < 0.01*

LD-C 4.26 0.10* 0.74 7.78 0.01 8.51

HD-C 9.20 < 0.01* 5.51 12.89 4.75 13.65

HD-LD 4.94 0.09* 0.96 8.91 0.14 9.74

1-km Hike; by 

FT

8.70

(2, 100) < 0.01*

LD-C 0.59 0.03* 0.20 0.98 0.12 1.06

HD-C 0.91 < 0.01* 0.52 1.29 0.44 1.37

HD-LD 0.31 0.40 -0.10 0.73 -0.19 0.82

Negotiate 

Obstacle; by 

FT

3.80† 

(2) 0.15† 

LD-C 0.48 0.02† 0.15† 0.55† 0.08† 0.63† 

HD-C 0.76 < 0.01† 0.33† 0.62† 0.30† 0.67† 

HD-LD 0.31 0.28† -0.02† 0.40† -0.12† 0.48† 

*Indicates there is a statistically significant difference between Integration Levels

**Tukey intervals have familywise confidence of the indicated percentage, each interval is not of the given 

confidence level on its own.

†Results presented are from Kruskal-Wallis and Mann-Whitney non-parametric tests due to nonnormality.

Additional Task Results:

7-km Hike. The data are normally distributed, as evidenced by the Shapiro-Wilk Test 

that resulted in a p-value of 0.27 for the C group, 0.18 for the LD group, and 0.30 for the 

HD group.

The C group had a mean time of 84.06 minutes, which is statistically significantly faster 

than the 88.32-minute average for the LD group and significantly faster than the 93.26-

minute average for the HD group. The difference between the LD and HD group is

statistically significant, as well. There was a 5.07% degradation in performance from 

the C to the LD group, and a 10.95% degradation in performance from the C to the HD 

group. No obvious pattern emerges from looking at the hiking times, by kilometer.

• Contextual Comments. The analytical results show that integrated Combat 

Engineer units would move at a slower rate than an all-male unit. The operational 
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relevance is the potential negative impact on mission accomplishment during a 

unit moving into position to conduct operations.

1-km Hike; by FT. The data are normally distributed, as evidenced by the Shapiro-Wilk 

Test that resulted in a p-value of 0.55 for the C group, 0.36 for the LD group, and 0.95 

for the HD group.

The C group had a mean time of 9.42 minutes, which is statistically significantly faster 

than the LD group mean time of 10.01 minutes and also statistically significantly faster 

than the HD group mean time of 10.33 minutes. On average, the LD group was 6.29% 

slower than the C group, and the HD group was 9.63% slower than the C group. On 

average, the HD group was 3.14% slower than the LD group and the difference 

between the LD and HD group is not statistically significant in a Tukey test.

• Contextual Comments. Although operational situations may differ, the time a 

unit takes to move into position can be the determining factor in the success of 

the mission. This 1 Km hike movement is meant to be executed quickly and 

without delay. Therefore, faster results favorable because reaching the objective 

in a timely manner is critical to the mission

Negotiate Obstacle; by FT. The data are not normally distributed for the HD and LD 

groups, as evidenced by the Shapiro-Wilk Test p-values less than 0.01. We thus 

analyze these data using the Kruskal-Wallis and Mann-Whitney-U non-parametric 

procedures.

The C group had a mean time of 1.50 minutes, the LD group had a mean time of 1.97

minutes, and the HD group had a mean time of 1.97 minutes. Although the KruskalWallis test does not show that the three groups are statistically significantly different at a 

10% level, the pairwise comparisons indicate that differences do exist. On average, the

LD group was 31.87% slower than the C group and the difference between the LD and 

C group is statistically significant when compared to a Bonferroni-adjusted significance 

level of 0.03. On average, the HD group was 52.48% slower than the C group and the 

difference between the HD and C group is statistically significant when compared to a 

Bonferroni-adjusted significance level of 0.03. On average, the HD group was 15.63% 

slower than the LD group and the difference between the LD and HD group is not 

statistically significant.

• Contextual Comments. It is operationally realistic to expect that a Combat 

Engineer unit will have to negotiate an obstacle such the one provided for this 

research this rather than breaching or bypassing it. One such example may be a 

compound, or security wall in a MOUT environment. In most all scenarios, it is 

more beneficial to negotiate the obstacle in a shorter amount of time in order to 

maintain movement rate or to reduce exposure time to potential enemy fires.
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Annex L. 

Mountaineering - Closed MOSs

This annex details the Mountaineering portion of the Ground Combat Element 

Integrated Task Force (GCEITF) experiment that consisted of Marine volunteers who 

participated in the closed combat arms MOS (0311, 0331, 0341, 0351, 0352) portion of 

the experiment. The Mountaineering experiment was executed 4 May – 18 May 2015 at 

the Leavitt Training Area (LTA), aboard the Mountain Warfare Training Center (MWTC), 

Bridgeport, CA. The sections outline the Mountaineering assessment (closed MOSs)

Scheme of Maneuver (SOM), Limitations, Deviations, and Descriptive and Basic 

Inferential Statistics. 

L.1 Scheme of Maneuver

L.1.1 Experimental Cycle Overview

The Mountaineering assessment (closed MOSs only) of the GCEITF took place aboard 

MWTC, Bridgeport, CA. The assessment continued over 15 days, in which the closed 

MOS squads conducted trials every other day. Every Marine received 1 day of recovery 

after each execution day. All squads consisted of 12 volunteers and a directassignment squad leader who was not assessed. Every volunteer was assigned a 

patch number, which dictated their order in conducting two of the assessed subtasks. 

The assessment was executed under the supervision of MCOTEA functional test 

managers and a range officer in charge/range safety officer from the GCEITF unit. The 

technical sites (gorge crossing and cliff climb) were established each morning by 

mountaineering subject matter experts, referred to as “red hats,” from the MWTC staff. 

L.1.2 Experimental Details

The mountaineering assessment simulated conducting a logistical resupply of a 

forward-staged squad while moving in a mountainous environment. Each squad 

departed an assembly area located at the Lower Base Camp (LBC) of MWTC. Four 

closed MOS squads executed a trial cycle: two control (C) non-integrated squads, and 

two high-density (HD) integrated squads with six females in each squad.

They hiked 4.6 km with a 75-lb pack and personal weapon (M-4) to an objective rally 

point (ORP). They then made a short non-assessed movement to a gorge, where they 

tied a Swiss seat. The second assessed task consisted of the 12-person squad 

crossing a 200-ft gorge via two single-rope bridges. After all 12 Marines had crossed 

the gorge, they pulled the packs across and made another short movement to the LTA. 

The third assessed task consisted of the 12-Marine squad climbing a 40-ft cliff using two 

climbing lanes. The Marines executed the gorge crossing and cliff climb per a 

prescribed order. The final assessed task was a 5-km hike back to LBC carrying the 
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same load. At the conclusion of the trial day, the composition of the squad was 

dissolved and a new sample of males and females were randomly assigned for the 

following cycle. 

L.1.3 Additional Context

Throughout the duration of the assessment, Marines lived in squad bays at LBC. 

During trial execution, Marines wore/carried prescribed loads. Weighing packs each 

day prior to the initial hike ensured consistency. After each experimental cycle, the 

Marines operated under Company leadership, performing minimal physically demanding 

tasks. Marines who were not part of an assessed squad conducted the same 

experimental subtasks to ensure equity between individuals participating in a trial cycle 

and those not chosen for that particular cycle. 

L.1.4 Experimental Tasks

L.1.4.1 4.6-km Movement 

Primary functions of Marine Corps maneuver elements are shoot, move, and 

communicate. Movement is a task common to all MOSs and applies to a variety of 

terrain and climate types. Special consideration must be given to certain factors while 

moving through a mountainous environment, to include distance, load, pace, technical 

skill, and special equipment. During the assessment, squads conducted a 4.6-km foot 

movement with a 75-lb pack and their personal weapon through highly restrictive 

terrain, starting at the LBC and ending at a gorge. Squads moved as quickly as they

could without any Marines falling behind. This task determined the squad’s rate of 

movement while carrying a specified load. Due to the physically demanding nature of 

moving under load, each Marine took a fatigue and workload survey after completion of 

the 4.6-km hike (see GCEITF Experimental Assessment Plan [EAP], Annex D). 

L.1.4.2 Gorge Crossing

Crossing gorges is a specific challenge when moving through mountainous terrain. 

Mountain leaders develop the skill and train with the equipment to establish gorgecrossing sites. Once established, Marines must pull themselves across and continue 

their mission. During the assessment, each squad crossed a 200-ft gorge using two 

single-rope bridges. Each Marine crossed the gorge one at a time in a specified order

using a specific route. Once all Marines had crossed the gorge, a “mule team” (working 

party) loaded their packs onto the rope bridge and the volunteers pulled them across. A 

“red hat” instructor provided a safety brief to the volunteers, checked their knots and 

Swiss seats, hooked up each volunteer to the rope bridge, consistently reset the safety 

line after each Marine, and supervised the entire gorge-crossing evolution. This task 

was chosen due to the upper body strength required to pull oneself across the gorge. 

This task determined the time for a squad to cross a gorge. 
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L.1.4.3 Cliff Ascent

Climbing a cliff (rock climbing) is another specific challenge when moving through 

mountainous terrain. Mountain leaders develop the skill and train with the equipment to 

establish a climbing site. Once the site has been established, Marines must safely and 

efficiently climb a rock-climbing route and continue their mission. During the 

assessment, each squad climbed a 40-ft cliff using two climbing routes. Each Marine 

climbed in a specified order using a specific route. Upon reaching the top of the route, 

they were lowered to the bottom of the climbing route by a belay Marine. A “red hat” 

instructor provided a safety brief to the volunteers, checked their knots and Swiss seats, 

and supervised the climbing and belaying techniques. This task was chosen due to the 

upper body and lower body strength required to climb a cliff. This task determined the 

time for a squad to climb a cliff.

L.1.4.4 5-km Movement 

During the assessment, squads conducted a 5-km foot movement with a 75-lb pack and 

their personal weapon through highly restrictive terrain to return from the cliff where they 

had conducted the climb back to LBC in order to complete the trial. 

At the completion of the trial, each Marine took a fatigue and workload survey to assess 

their fatigue and workload during the execution of the gorge crossing, cliff ascent, and 

5-km movement (see GCEITF EAP, Annex D). Marines took a cohesion survey to 

record their cohesion during the execution of all tasks (see GCEITF EAP, Annex M).

L.1.5 Loading Plan

The loading plan ensured, to the greatest extent possible, equity of physical activity 

among all volunteers throughout the duration of the experimental assessment. Trials 

and tasks were conducted in the same manner and sequence to ensure consistency. 

Due to the number of volunteers, a handful of Marines were not part of an assessed 

squad each cycle. Collaboration with Company leadership determined that the best 

method of loading non-assessed Marines was to have them perform the same tasks as 

an assessed squad in order to experience the same conditions and physical strain. In 

some instances, the loading Marines formed a quasi-squad and conducted the trial after 

all the assessed squads were done for the day. When the quasi-squad was too small, 

the loading Marines were attached to an assessed squad, in which case they operated 

at the rear of the assessed squad. At no point in time did a loading Marine aid or 

interfere with an assessed Marine/squad. 

L.1.6 Scheme of Maneuver Summary

The mountaineering experiment consisted of a 1-day trial cycle executed every other 

day that simulated moving through a mountainous environment to conduct a logistical 

resupply. Each trial consisted of the following tasks: 4.6-km movement, gorge 
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crossing, cliff ascent, and 5-km movement. During the course of the experiment, the 

closed MOS squads executed five trial cycles. 

L.2 Limitations 

L.2.1 Limitations Overview

The GCEITF experiment was designed to allow operationally relevant tasks to occur as 

naturally as possible, while unbiased measurements were gathered. Most tasks were 

performed in a manner similar to the way they would be performed in an operational 

environment. Under certain situations, artificial limitations or interruptions were 

introduced that changed or altered the way a task would normally be performed. While 

these limitations represent a degree of artificiality, they do not detract significantly from 

our abilities to generalize the conclusions of this experiment to the performance of 

Marines in a field environment. The following limitations were observed for the 

Mountaineering assessment. 

L.2.2 Relative Difficulty of Record Test

The Mountaineering assessment was designed to gather data associated with some of 

the most physically demanding tasks that Marines of all MOSs could perform in a 

mountainous environment. Marines are required to conduct continuous operations in a 

variety of environments and climates, to include mountainous terrain. The difficulty of 

the assessed tasks in isolation do not fully replicate life experienced by a unit during a 

Mountain Training Exercise (MTX) or combat operations in a mountainous location. 

Due to the limited amount of time available to conduct the assessment, only selected

mountaineering tasks were assessed. Due to specific experimental constraints and 

consideration of human factors, tasks/duties outside of the assessment were minimized. 

During a typical field exercise, it is common for Marines to conduct 24-hour operations 

that include performing daytime and nighttime operations/patrols, standing firewatch or 

a security post, and conducting continuing tactical actions. The Marines in the 

experiment were not required to bivouac in the elements, but rather slept in squad bays 

every night. Outside of the assessed trials, there were minimal tasks required of the 

volunteers that demanded any degree of physical strain.

Lastly, the Marines only conducted trials every other day, with a day-on/day-off 

schedule. This artificial recovery period (or delay in operations) is not realistic when 

conducting training or combat operations.

L.2.3 Experimental Timing Requirements

Another primary concern in designing the mountaineering assessment was throughput 

for the Marines. Only four squads were supportable, given the time and space 

requirements of the SOM and the limited amount of daylight. Initially, it took a single 

squad approximately 5 hours to complete a single trial. To prevent a squad from 

influencing another, there was a 1.5-hour delay between squads. 
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L.2.4 Execution Artificialities

Several artificialities were present as the volunteers completed the SOM. Once the 

squad completed the initial 4.6-km hike, the unit arrived at the gorge to an alreadyestablished high-tension crossing site to expedite the throughput. This is realistic in the 

sense that a commander or unit leader, if supportable, could send an element forward 

of the main body and have the technical sites established. There was a fire team of 

non-volunteers emplaced at the gorge-crossing site prior to the squad’s arrival. This 

team assisted with loading the individual packs onto the rope system once the squad 

completed the gorge-crossing movement, allowing the squad to complete the crossing 

unimpeded and the test team to minimize the random error inherent in the experiment

created by the administrative movement.

Another artificiality that existed pertained to the requirement to lower Marines after 

climbing the cliff. During a typical cliff ascent, once Marines reach the top of the cliff 

they climb over the crest and continue with the mission. Due to experimental and safety 

constraints, after the volunteers topped out, they had another volunteer in the squad 

belay for them and lower them to the ground. The belay-man’s technical skill level 

affected the time for total execution by the squad. An experienced individual was

comfortable lowering the climber back down to the bottom quickly, while an 

inexperienced one lowered the climber more slowly. These artificialities impacted total 

performance time. 

L.2.5 Limitations Summary

The mountaineering assessment was designed to replicate realistic training in a field 

environment in mountainous terrain. The endstate was to create an experiment in 

which the volunteers felt they were conducting realistic and operationally relevant tasks. 

Certain unavoidable limitations to both the assessed tasks and the non-assessed 

operating environment introduced a level of artificiality that would not normally have 

been present in a field training or combat environment. 

L.3 Deviations 

L.3.1 Gorge Crossing

During initial planning and coordination with MWTC, it was established that all squads 

would utilize one high-tension system to cross the gorge. However, during the “dry

runs,” the MWTC instructors and subject matter experts, or “red hats,” advised 

MCOTEA and the GCEITF leadership that they could establish two high-tension 

systems at the gorge-crossing site. The high-tension systems would be the same 

distance and level of difficulty, with minimum variations. Since there was an initial 

concern about how long the entire evolution would take, MCOTEA decided to approve 

the deviation in order to gain efficiencies in the overall time and reduce the likelihood of 

a backlog at the gorge.
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Additionally, the packs that the Marines carried to the gorge crossed the high-tension 

rope bridge. After all Marines crossed the gorge and the assessment time stopped, 

there was an administrative movement in which the packs were tied together and

loaded for the squad to pull across. Groups of three Marines pulled three packs across 

in order to ensure that all Marines were under equal loading conditions.

L.3.2 Failure Criteria for the Gorge Crossing

Annex D of the Experimental Test Plan is the Data Collection Execution Matrix. As 

written, the failure criteria for the gorge-crossing portion of the assessment stated that 

failure would occur once the unit took 2 hours to complete the crossing. This correlated 

to each Marine in the 12-Marine squad having 10 minutes to complete the gorge 

crossing, at which point the “red hat” would pull the Marine to the far side of the gorge. 

After discussion with the MWTC staff, the consensus was that if it took a Marine more 

than 5 minutes to cross the gorge, there would be a safety concern requiring the “red 

hat” to facilitate completion. It was agreed that 5 minutes was acceptable for an 

individual failure on the gorge crossing. Additionally, the overall time for the squad to 

complete the gorge would be reduced to 1 hour for squad task failure.

L.3.3 Concentration of Squad

The Test Plan stated that MCOTEA would assess three levels of integration for the Rifle 

Squad: the control group, the low-integration group, and the high-integration group. 

However, before the record trial cycle began, the ITF population could no longer support 

a low-integration group. The Infantry test team decided to eliminate the lowconcentration group and began the record trial cycle on 4 May 2015 with the control 

group and the high-concentration group of six females per squad. 

L.3.4 Two-Day Test Event

Based on the number of Marines and squads that were expected to train at Bridgeport, 

the initial plan outlined a 3-day cycle to support 12 squads. The plan was for each 

squad to execute the trial once every 3 days. However, due to volunteer attrition by the 

commencement of the Bridgeport assessment, the task force was only able to fill four 

closed MOS squads. This reduction allowed for the trials to be conducted over a 2-day 

cycle (1 day for open MOS squads, and 1 for closed MOS squads). 

L.4 Data Set Description 

L.4.1 Data Set Overview

The closed MOS portion of the Bridgeport experiment consisted of 1 pilot trial cycle day 

and 13 trial cycles. The pilot trial was conducted on 4 May 2015. Because the pilot trial

data and execution did not deviate from record trial execution, we use all pilot trial data 

for analysis. The final data set includes data collected 4 May – 18 May 2015.
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L.4.2 Record Test Volunteer Participants

At the beginning of the first pilot trial, there were 43 male closed MOS volunteers and 19 

female closed MOS volunteers. All Marines who began this portion of the experiment 

completed it.

L.4.3 Planned, Executed, and Analyzed Trial Cycles

Table L-1 displays number of trial cycles planned, executed, and analyzed by task. The 

planned number of trial cycles for the closed MOS portion of Bridgeport per Section 

7.5.3 of GCEITF EAP is 60 trials, or 20 trials per planned integration level (C, lowdensity, and HD). Due to the number of Marines who voluntarily withdrew or were 

involuntarily withdrawn from the experiment prior to the execution of the first record trial 

cycle, only two squads of the C and HD integration levels remained. 

The planned number of trial cycles in Table L-1 reflects 14 planned trial cycles for each 

integration level. There were no trials on 7 May – 9 May 2015 or on 15 May 2015, 

resulting in the loss of four trials per integration level. We used 1 make-up day to make 

up two of those trials for each integration level.

Table L-1. Bridgeport Closed MOS Planned, Executed, and Analyzed Trial Cycles

Task and Metric 

Description

Integration 

Level

Number of 

Planned Trials

Number of 

Trials 

Conducted 

Number of 

Trials Used in 

Analysis

Notes

4.6-km Hike C 14 12 12 Did not execute 4 May due to 

weather

HD 14 13 13

5-km Return Hike C 14 12 12 Did not execute 4 May due to 

weather

HD 14 12 12

Gorge Crossing C 14 12 12 Did not execute 4 May due to 

weather

HD 14 12 12

Cliff Ascent C 14 11 11 Did not execute 4 May due to 

weather

HD 14 12 12

4.6-km Hike; 1km 

Time

C 14 12 10 Missing data: 17 May 

HD 14 13 11 Missing data: 17 May

4.6-km Hike; 2km 

Time

C 14 12 10 Missing data: 17 May

HD 14 13 11 Missing data: 17 May

4.6-km Hike; 3km 

Time

C 14 12 10 Missing data: 17 May

HD 14 13 11 Missing data: 17 May

4.6-km Hike; 4km 

Time

C 14 12 10 Missing data: 17 May

HD 14 13 11 Missing data: 17 May

4.6-km Hike; 5km 

Time

C 14 12 10 Missing data: 17 May

HD 14 13 11 Missing data: 17 May

5-km Return Hike; 

1km Time

C 14 12 10 Missing data: 17 May

HD 14 12 10 Missing data: 17 May

5-km Return Hike; 

2km Time

C 14 12 10 Missing data: 17 May

HD 14 12 10 Missing data: 17 May

5-km Return Hike; 

3km Time

C 14 12 10 Missing data: 17 May

HD 14 12 10 Missing data: 17 May

5-km Return Hike; 

4km Time

C 14 12 10 Missing data: 17 May

HD 14 12 10 Missing data: 17 May
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Task and Metric 

Description

Integration 

Level

Number of 

Planned Trials

Number of 

Trials 

Conducted 

Number of 

Trials Used in 

Analysis

Notes

5-km Return Hike; 

5km Time

C 14 12 10 Missing data: 17 May

HD 14 12 10 Missing data: 17 May

L.5 Descriptive and Basic Inferential Statistics 

L.5.1 Descriptive Statistics Overview

Performance metrics were measured during the conduct of common infantry tasks and 

are indicative of unit-level proficiency during either field exercises or combat operations. 

Four tasks out of 14 are presented in this section. Bridgeport Closed MOS Appendix 

contains the descriptive statistics for the remainder of the Bridgeport tasks. The words 

“metric” and “task” are used interchangeably throughout this Annex. They both refer to 

the experimental task. 

Each fireteam consisted of four volunteer Marines: the fireteam leader, automatic 

rifleman, grenadier, and rifleman. Each squad consisted of 12 volunteer Marines (three 

fireteams) with a direct assignment (nonvolunteer) squad leader. There were two 

integration levels for all tasks. A C group was non-gender-integrated and a HD group 

was gender integrated with six female Marines.

This section includes experimental results based on descriptive statistics, MannWhitney tests, and scatter plots. The subsequent sections will cover each task in detail. 

Lastly, contextual comments, additional insights, and subjective comments (as 

applicable) tying back to each experimental task are incorporated. 

Caution must be used when comparing similar tasks executed by different MOSs within 

the GCEITF experiment. Comparative analysis may be misleading due to differing 

factors between MOS tasks, such as distances, techniques, leadership, load carried, 

group size, and group composition.

L.5.2 Bridgeport Closed MOS Selected Tasks Descriptive Statistic Results

The two tables below display the results for the four selected Bridgeport closed MOS 

metrics. Table L-2 displays the metrics and integration levels with their respective 

sample sizes, means, and standard deviations. Table L-3 displays Mann-Whitney 

results, including metrics and integration levels, p-values suggesting statistical 

significance, elapsed-time differences between integration levels, and percentage 

differences between integration levels. For each task, a Mann-Whitney test (due to the 

small sample size) was conducted to compare the two groups. If p-values are less than 

the a-priori determined significance level of 0.10, we conclude that there is statistical 

evidence that the mean time or percent hits for the HD group is different from that for 

the C group.
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Table L-2. Bridgeport Closed MOS Selected Task Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD

4.6-km Hike (minutes)* C 12 59.39 4.97

HD 13 70.36 6.34

5-km Return Hike (minutes)* C 12 56.45 6.07

HD 12 67.59 6.56

Gorge Crossing (minutes)* C 12 16.62 2.64

HD 12 19.51 3.40

Cliff Ascent (minutes)* C 11 34.92 7.46

HD 12 40.69 9.61

*Indicates there is a statistically significant difference, in either a one-sided or 

two-sided hypothesis test, between integration levels according to a MannWhitney test. 

Table L-3. Bridgeport Closed MOS Mann-Whitney Test Results

Metric Comparison Difference % 

Difference

2-sided 

P-Value

1-sided 

P-Value

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

4.6-km Hike 

(minutes) HD-C 10.97 18.47% < 0.01* <0.01* 7.56 13.85 6.58 14.93

5-km Return Hike 

(minutes) HD-C 11.14 19.74% < 0.01* <0.01* 6.86 15.25 6.27 15.59

Gorge Crossing 

(minutes) HD-C 2.89 17.37% 0.01* 0.01* 1.43 4.00 0.91 4.32

Cliff Ascent 

(minutes) HD-C 5.77 16.51% 0.12 0.06* 0.87 10.14 -0.39 12.02

*Indicates there is a statistically significant difference, in either a one-sided or two-sided hypothesis test, 

between integration levels according to the Mann-Whitney test. 

L.5.2.1 4.6-km Hike

L.5.2.1.1 4.6-km Hike Overview

This experimental task assessed a squad of 12 Marines moving 4.60 km while each 

Marine carried a 75-lb pack (resupply load) and an M-4. The route for this movement 

was on an unimproved surface and very hilly; the terrain was hard and rocky. This 

movement consisted primarily of elevation gain (uphill) as shown in Figure L-1. The 

recorded time for this task started when the squad departed the LBC start point and 

stopped when the squad arrived at the gorge-crossing site. Each squad moved as fast 

as the slowest person and could take as many breaks as necessary.
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Figure L-1. 4.6-km Hike Elevation Profile

Figure L-2 displays all closed MOS 4.6-km hike time data. All data on the scatter plot 

are valid for analysis.

Figure L-2. 4.6-km Hike

The C group had a mean time of 59.39 minutes. This time is statistically significantly 

faster than the HD mean time of 70.36 minutes. This difference results in an 18.47%, or 

a 10.97-minute, degradation in hike time between the groups. The HD group has 
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greater variability, as shown by the 1.37-minute increase in standard deviation (SD) 

(4.97 minutes for the C group and 6.34 minutes for the HD group).

L.5.2.1.2 4.6-km Hike Contextual Comments

The difference in hike times is relevant to both the training and combat environments as 

it will take integrated squads more time to conduct foot marches. Per the tactical march 

standards noted in the 0311 Descriptive Statistics, the Marine Corps standard of hiking 

is 4.0 km/h. The HD group failed to meet this standard. The C group’s average pace 

was 4.65 km/h and the HD group’s average pace was 3.92 km/h. To extrapolate this 

pace over a 20-km movement (an optimistic assumption that does not account for any 

further degradation of performance), the HD group would finish 48 minutes behind the C 

group. Furthermore, on any given day (under the same environmental conditions), the 

fastest group was always a C group and the slowest group was always an HD group. 

L.5.2.1.3 4.6-km Hike Additional Insights 

Based on the USMC standard of a 4.0-km/h pace over a 4.6-km route (which would 

result in a 69-minute 4.6-km completion time), the HD groups was 1.36 minutes slower 

than that standard. In a battlefield situation, in which speed is essential, this delay is 

advantageous for the enemy. Marine Corps Doctrinal Publications (MCDPs) 

consistently emphasize the importance of speed. MCDP 1-3 Tactics devotes an entire 

chapter to “Being Faster” and states, “Physical speed, moving more miles per hour, is a 

powerful weapon in itself.” MCDP-6 Command and Control also speaks to speed 

relative to the enemy and states, “The speed differential does not necessarily have to 

be a large one: a small advantage exploited repeatedly can quickly lead to decisive 

results.” 

L.5.2.1.4 4.6-km Hike Subjective Comments

For subjective comments relating to this task, see the BP Closed-MOS Appendix.

L.5.2.2 5.0-km Return Hike

L.5.2.2.1 5.0-km Return Hike Overview

This experimental task assessed a squad of 12 Marines moving 5.0 km while each 

Marine carried a 75-lb pack (resupply load) and an M-4. The route for this movement 

was on an unimproved surface and very hilly; the terrain was hard and rocky. This 

movement consisted primarily of elevation loss (downhill) as shown in Figure L-3. The 

recorded time for this task started when the squad departed the LTA and stopped when 

the squad arrived at the LBC. Each squad moved as fast as the slowest person and 

could take as many breaks as necessary.
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Figure L-3. 5.0-km Return Hike Elevation Profile

Figure L-4 displays all Bridgeport closed MOS 5.0-km hike time data. All data on the 

scatter plot are valid for analysis.

Figure L-4. 5.0-km Hike

The C group had a mean time of 56.45 minutes. This time is statistically significantly 

faster than the HD mean time of 67.59 minutes. This difference results in a 19.74%, or 

an 11.14-minute, degradation in hike time between the groups. The HD group has 

greater variability, as shown by the 0.49-minute increase in SD (6.07 minutes for the C 

group and 6.56 minutes for the HD group).
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L.5.2.2.2 5.0-km Return Hike Contextual Comments

The difference in hike times is relevant to both the training and combat environments as 

it will take integrated squads more time to conduct foot marches. Per the tactical march 

standards noted in the 0311 Descriptive Statistics, the Marine Corps standard of hiking 

is 4.0 km/h. Both the C group and HD group met this standard. The C group’s average

pace was 5.31 km/h and the HD group’s average pace was 4.44 km/h. To extrapolate 

this pace over a 20-km movement (an optimistic assumption that does not account for 

any further degradation of performance), the HD group would finish 44.3 minutes behind 

the C group. Furthermore, on any given day (under the same environmental

conditions), the slowest C group was faster than the fastest HD group.

L.5.2.2.3 5.0-km Return Hike Additional Insights

MCDPs consistently emphasize the importance of speed. MCDP 1-3 Tactics devotes 

an entire chapter to “Being Faster” and states, “Physical speed, moving more miles per 

hour, is a powerful weapon in itself.” MCDP-6 Command and Control also speaks to 

speed relative to the enemy and states, “The speed differential does not necessarily 

have to be a large one: a small advantage exploited repeatedly can quickly lead to 

decisive results.”

L.5.2.2.4 5.0-km Return Hike Subjective Comments

For subjective comments relating to this task, see the BP Closed-MOS Appendix.

L.5.2.3 Gorge Crossing

L.5.2.3.1 Gorge Crossing Overview

This experimental task assessed a squad of 12 Marines moving across two 200-foot 

single-rope bridges. A mountaineering expert (“red hat”) was the only one authorized to 

verify knots and hook up each Marine to the rope bridge. Crossing the gorge was an 

individual task, but the recorded time was for the squad as a whole. After each 

individual reached the far side of the gorge, a squad leader reset each lane by pulling 

the tag-line back to the near side of the gorge for the next Marine. The recorded time 

for this task started when the first Marine of the squad touched the rope bridge and 

stopped when last member of the squad was completely disconnected from the rope

bridge on the far side.

Figure L-5 displays all Bridgeport closed MOS gorge-crossing time data. All data on the 

scatter plot are valid for analysis.
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Figure L-5. Gorge Crossing

The C group had a mean time of 16.62 minutes. This time is statistically significantly 

faster than the HD mean time of 19.51 minutes. This difference results in a 17.37%, or 

a 2.89-minute, degradation in hike time between the groups. The HD group has greater 

variability, as shown by the 0.76-minute increase in SD (2.64 minutes for the C group 

and 3.40 minutes for the HD group).

L.5.2.3.2 Gorge Crossing Contextual Comments

Sun Tzu stated, “Speed is the essence of war. Take advantage of the enemy’s 

unpreparedness; travel by unexpected routes and strike him where he has taken no 

precautions” (MCDP-1, p. 69). Gaining this advantage in a mountainous environment 

may involve crossing a gorge. Crossing a single-rope bridge by pulling oneself across 

is a physical strain on the upper body. While no purely objective standard can be set for 

crossing a gorge, any decrement in speed translates into increased exposure to enemy 

fires and greater risk for friendly casualties. On average, the HD group took 2.89 

minutes longer than the C group. Furthermore, on any given day (under the same 

environmental conditions), the C group was always the fastest squad to finish and the 

HD group was always the slowest squad to finish.

L.5.2.3.3 Gorge-Crossing Additional Insights

A purely objective evaluation of 2.89-minute difference is elusive but may possess some 

practical significance on the battlefield that would reduce the survivability of an 

integrated unit. Considering an enemy unit moving at 4.0 km/h on foot to defend a 

piece of key terrain, the enemy would be able to move an additional 193 meters as the 

HD group was still crossing the gorge. Far worse would be if an enemy observer could 
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call for fire with mortars, artillery, or aviation assets against the integrated group, given 

the time delay. 

Additionally, one source of masking occurred during this task that was not anticipated 

during the design. The physically demanding aspect of this task involved pulling oneself 

across the gorge, but the reset time was generally twice that of the execution time. For 

instance, many Marines were able to cross the gorge within 60 seconds; however, it 

consistently took approximately 2.5 minutes to unhook a Marine, pull the tag-line back 

to the near side, and hook up the next Marine. Since six Marine went across each line, 

a time of approximately 6 minutes was devoted to Marines crossing the gorge while a 

time of approximately 12.5 minutes was devoted to the reset process. Strictly 

considering the performance of each Marine would magnify the results and reveal the 

gender difference as being even greater.

L.5.2.3.4 Gorge Crossing Subjective Comments

For subjective comments relating to this task, see the BP Closed-MOS Appendix.

L.5.2.4 Cliff Ascent

L.5.2.4.1 Cliff Ascent Overview

This experimental task assessed a squad of 12 Marines climbing two 40-foot technical 

rock-climbing routes. A mountaineering expert ( “red hat”) was the only one authorized 

to verify knots and hook up each Marine to the belay line. Climbing the cliff was an 

individual task, but the recorded time was for the squad as a whole. After each 

individual reached the top of the cliff, a fellow Marine on belay lower the climber to the 

ground. The recorded time for this task started when the first Marine of the squad 

touched the rope and stopped when last member of the squad was completely 

disconnected from the rope.

Figure L-6 displays all Bridgeport closed MOS cliff ascent time data. All data on the 

scatter plot are valid for analysis.
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Figure L-6. Cliff Ascent

The C group had a mean time of 34.92 minutes. This time is statistically significantly 

faster than the HD mean time of 40.69 minutes. This difference results in a 16.51%, or 

a 5.77-minute, degradation in hike time between the groups. The HD group has greater 

variability, as shown by the 2.51-minute increase in SD (7.46 minutes for the C group 

and 9.61 minutes for the HD group).

L.5.2.4.2 Cliff Ascent Contextual Comments

Sun Tzu stated, “Speed is the essence of war. Take advantage of the enemy’s 

unpreparedness; travel by unexpected routes and strike him where he has taken no 

precautions” (MCDP-1, p. 69). Gaining this advantage in a mountainous environment 

may involve climbing a cliff. Technical rock-climbing is a physical strain on the upper 

and lower body. While no purely objective standard can be set for climbing a cliff, any 

decrement in speed translates into an advantage to the enemy and a greater risk of 

friendly casualties. On average, the HD group took 5.77 minutes longer than the C 

group. Furthermore, on any given day (under the same environmental conditions), the 

C group was always the fastest squad to finish and, with the exception of one trial, the 

HD group was always the slowest squad to finish.

L.5.2.4.3 Cliff Ascent Additional Insights

A purely objective evaluation of 5.77 minutes is elusive but may possess some practical 

significance on the battlefield that would reduce the survivability of an integrated unit. 

Considering an enemy unit moving at 4.0 km/h on foot to defend a piece of key terrain, 

the enemy would be able to move an additional 385 meters as the HD group was still 

climbing the cliff. Far worse would be if an enemy observer could call for fire with 

mortars, artillery, or aviation assets against the integrated group, given the time delay. 
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The obvious “learning curve” (trial cycles 1 and 2) that occurred can be explained in two 

ways: familiarity of the climbing route and the masking effect of belaying. First, there 

were two separate but similar routes that Marines had to climb. Each subsequent 

opportunity to climb involved learned techniques/behaviors that resulted in a faster 

climb time. Second, a source of masking occurred during this task that was not 

anticipated during the design. The physically demanding aspect involved climbing the 

cliff; however, the belay/lowering time was a significant part of the overall time. The 

belay time also got drastically shorter as the assessment progressed, because belay 

Marines became more comfortable with this skill. Strictly considering the performance 

of each Marine would have better informed the gender difference involved in this task.

L.5.2.4.4 Cliff Ascent Subjective Comments

For subjective comments relating to this task, see the BP Closed MOS Appendix.
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Appendix to Annex L

Mountaineering Closed MOSs Supplemental Information

This appendix provides supplemental information for the Mountaineering Closed MOSs 

portion of the GCEITF experiment. It provides information regarding the GCEITF

leadership subjective comments and additional descriptive statistics not described in 

Annex L.

Section 1. GCEITF Leadership Subjective Comments

The GCEITF leadership provided comments on their observations of the experiment 

throughout its execution. Table L A displays a summary of these comments broken 

down by task, integration level, gender, and type of comment.

Table L A – Summary of GCEITF Leadership Comments

Section 2. Additional Task Basic Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. The experiment included a number of tasks and associated metrics 

conducted to enhance operational realism and maintain consistent application of the 

experimental process. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

This section presents results for 10 additional Closed MOS tasks. Annex L contains the 

descriptive statistics for the remainder of the Closed MOS tasks. The words “metric” 

and “task” are used interchangeably throughout this Appendix. They both refer to the 

experimental task.

The table below displays the results for 10 additional Closed MOS metrics. Table L B

displays the metrics and integration levels with their respective sample sizes, means, 

standard deviations, and percent differences between integration levels.

Task and Metric 

Description Gender Total

C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total

M 16 3 19 15 1 16 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 37

F 0 34 34 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 38

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1

M 3 1 4 0 0 0 3 0 3 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 8

F 0 17 17 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 20

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 3 0 0 0 3

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 0 0 0 0 0 0 5 5 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 6

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3

F 0 0 0 0 0 0 0 4 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1

Cliff Ascent

Gorge Crossing

Other No category

4.6-km Hike

5-km Return Hike

Falling 

behind/slowing 

movement

Requesting extra 

breaks

Requires extra 

assistance

Needs no 

assistance

Compensating 

for another 

Marine

Gear pass off
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Table L B – Bridgeport 03XX Test Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD % Difference

(HD-C)

4.6-km Hike; first km 

(minutes)

C 10 9.54 0.39 11.06% HD 11 10.60 0.45

4.6-km Hike; second 

km (minutes)

C 10 10.53 0.24 21.82%

HD 11 12.83 1.03

4.6-km Hike; third km 

(minutes)

C 10 12.29 1.14 17.63% HD 11 14.45 1.86

4.6-km Hike; fourth 

km (minutes)

C 10 17.86 2.83 25.50% HD 11 22.41 3.04

4.6-km Hike; fifth km 

(minutes)

C 10 9.31 0.90 14.70% HD 11 10.68 1.03

Return Hike; first km 

(minutes)

C 10 12.05 0.98

21.36% HD 10 14.62 1.52

Return Hike; second 

km (minutes)

C 10 11.96 2.05 23.43% HD 10 14.77 1.61

Return Hike; third km 

(minutes)

C 10 10.19 1.50 14.12% HD 10 11.63 0.90

Return Hike; fourth 

km (minutes)

C 10 10.07 1.29

17.42% HD 10 11.83 1.59

Return Hike; fifth km 

(minutes)

C 10 12.74 1.28 24.52% HD 10 15.87 1.48

Additional Task Results: 

4.6-km Hike by km. The general trend for the 4.6-km hike was that the difference 

between the HD and C groups increased over the course of the hike. These differences 

are largest during the points of the largest elevation change.

Return Hike by km. The general trend for the return hike was that the difference 

between the HD and C groups increased over the course of the hike. These differences 

are largest during the points of the largest elevation change.
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Annex M. 

Mountaineering - Open MOSs

This annex details the mountaineering portion of the Ground Combat Element 

Integrated Task Force (GCEITF) experiment that consisted of Marine volunteers who 

hold an open MOS (in this experiment, all open MOSs consisted of Marines trained as 

MOS 1371 Combat Engineers, provisional infantry riflemen, and provisional infantry 

machine gunners). The mountaineering experiment was executed from 4 May to 18 

May 2015 at the Leavitt Training Area (LTA), aboard the Mountain Warfare Training 

Center (MWTC), Bridgeport, CA. The sections outline the mountaineering assessment 

(open MOSs) Scheme of Maneuver (SOM), Limitations, Deviations, and Descriptive and 

Basic Inferential Statistics. 

M.1 Scheme of Maneuver

M.1.1 Experimental Cycle Overview

The mountaineering assessment (open MOSs only) of the GCEITF took place aboard 

MWTC, Bridgeport, CA. The assessment continued over 15 days during which the open

MOS squads conducted trials every other day. Every Marine received 1 day of recovery 

after each execution day. All squads consisted of 12 volunteers and a direct-assignment 

squad leader who was not assessed. All volunteers were assigned patch numbers, 

which dictated their order in conducting two of the assessed subtasks. The assessment 

was executed under the supervision of MCOTEA functional test managers and a range 

officer in charge/range safety officer from the GCEITF unit. The technical sites (gorge 

crossing and cliff climb) were established each morning by mountaineering subject 

matter experts, referred to as “Red Hats,” from the MWTC staff. 

M.1.2 Experimental Details

The mountaineering assessment simulated conducting a logistical resupply of a 

forward-staged squad while moving in a mountainous environment. Each squad 

departed an assembly area located at the Lower Base Camp (LBC) of MWTC. Four 

open MOS squads executed a trial cycle: two control (C) nonintegrated squads and two 

high-density (HD) integrated squads with six females in each squad.

They hiked 4.6 km with 75-lb packs and personal weapons (M-4s) to an objective rally 

point (ORP). They then made a short nonassessed movement to a gorge where they 

tied a Swiss seat. The second assessed task consisted of the 12-person squad crossing 

a 200-ft gorge via two single-rope bridges. After all 12 Marines crossed the gorge, they 

pulled the packs across and made another short movement to the LTA. The third 

assessed task consisted of the 12-Marine squad climbing a 40-ft cliff using two climbing 

lanes. The Marines executed the gorge crossing and cliff climb per a prescribed order. 
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The final assessed task was a 5-km hike back to LBC carrying the same load. At the 

conclusion of the trial day, the composition of the squad was dissolved and a new 

sample of males and females were randomly assigned for the following cycle. 

M.1.3 Additional Context

Throughout the duration of the assessment, Marines lived in squad bays at LBC. During 

trial execution, Marines wore/carried prescribed loads. Weighing packs each day prior 

to the initial hike ensured consistency. After each experimental cycle, the Marines 

operated under company leadership, performing minimal physically demanding tasks. 

Marines who were not part of an assessed squad conducted the same experimental 

subtasks to ensure equity between individuals participating in a trial cycle and those not 

chosen for that particular cycle. 

M.1.4 Experimental Tasks

M.1.4.1 4.6-km Movement 

Primary functions of Marine Corps maneuver elements are shoot, move, and 

communicate. Movement is a common task to all MOSs and applies to a variety of 

terrain and climate. Special consideration must be made while moving through a 

mountainous environment to include distance, load, pace, technical skill, and special 

equipment. During the assessment, squads conducted a 4.6-km foot movement with 75-

lb packs and personal weapons through highly restrictive terrain, starting at the LBC 

and ending at a gorge. Squads moved as quickly as they were able without any Marines 

falling behind. This task determined the squad’s rate of movement while carrying a 

specified load. Due to the physically demanding nature of moving under load, each 

Marine took a fatigue and workload survey after completion of the 4.6-km hike (see 

GCEITF Experimental Assessment Plan [EAP], Annex D). 

M.1.4.2 Gorge Crossing

Crossing gorges is a specific challenge when moving through mountainous terrain. 

Mountain leaders develop the skill and train with the equipment to establish gorgecrossing sites. Once established, Marines must pull themselves across and continue 

their mission. During the assessment, each squad crossed a 200-ft gorge using two 

single-rope bridges. Marines crossed the gorge one at a time in a specified order using 

a specific route. Once all Marines had crossed the gorge, a mule team (working party) 

loaded their packs onto the rope bridge and the volunteers pulled them across. A Red 

Hat instructor provided a safety brief to the volunteers, checked their knots and Swiss 

seats, hooked up each volunteer to the rope bridge, consistently reset the safety line 

between Marines, and supervised the entire gorge-crossing evolution. This task was 

chosen for the upper body strength required to pull oneself across the gorge. This task 

determined the time for a squad to cross a gorge. 
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M.1.4.3 Cliff Ascent

Climbing a cliff (rock climbing) is another specific challenge when moving through 

mountainous terrain. Mountain leaders develop the skill and train with the equipment to 

establish a climbing site. Once established, Marines must safely and efficiently climb a 

rock-climbing route and continue their mission. During the assessment, each squad 

climbed a 40-ft cliff using two climbing routes. Each Marine climbed in a specified order 

using a specific route. Upon reaching the top of the route, he or she was lowered to the 

bottom of the climbing route by a belay Marine. A Red Hat instructor provided a safety 

brief to the volunteers, checked their knots and Swiss seats, and supervised the 

climbing and belaying techniques. This task was chosen for the upper body and lower 

body strength required to climb a cliff. This task determined the time for a squad to 

climb a cliff.

M.1.4.4 5-km Movement 

During the assessment, squads conducted a 5-km foot movement with 75-lb packs and 

personal weapons through highly restrictive terrain to return from the cliff where they 

conducted the climb back to LBC to complete the trial. 

At the completion of the trial, each Marine took a fatigue and workload survey to assess 

their fatigue and workload during the execution of the gorge crossing, cliff ascent, and 

5-km movement (see GCEITF EAP, Annex D). Marines took a cohesion survey to 

record their cohesion during the execution of all tasks (see GCEITF EAP, Annex M). 

M.1.5 Loading Plan

The loading plan ensured, to the greatest extent possible, equity of physical activity 

among all volunteers throughout the duration of the experimental assessment. Trials 

and tasks were conducted in the same manner and sequence to ensure consistency. 

Due to the number of volunteers, a handful of Marines were not part of an assessed 

squad each cycle. Collaboration with company leadership determined that the best 

method of loading nonassessed Marines was to have them perform the same tasks as 

an assessed squad to experience the same conditions and physical strain. In some 

instances, the loading Marines formed a quasi-squad and conducted the trial after all 

the assessed squads were done for the day. When the quasi-squad was too small, the 

loading Marines were attached to an assessed squad, in which case they operated at 

the rear of the assessed squad. At no point in time did a loading Marine aid or interfere 

with an assessed Marine/squad. 

M.1.6 Scheme of Maneuver Summary

The mountaineering experiment consisted of a 1-day trial cycle executed every other 

day that simulated moving through a mountainous environment to conduct a logistical 

resupply. Each trial consisted of the following tasks: 4.6-km movement, gorge crossing, 
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cliff ascent, and 5-km movement. During the course of the experiment, the open MOS 

squads executed four test cycles. 

M.2 Limitations 

M.2.1 Limitations Overview

The GCEITF experiment was designed to allow operationally relevant tasks to occur as 

naturally as possible, while gathering unbiased measurements. Most tasks were 

performed in a manner similar to those in an operational environment. Under certain 

situations, artificial limitations or interruptions were introduced that altered the way a 

task would normally be performed. While these limitations represent a degree of 

artificiality, they do not detract significantly from our abilities to generalize the 

conclusions of this experiment to the performance of Marines in a field environment. 

The following limitations were observed for the mountaineering assessment. 

M.2.2 Relative Difficulty of Record Test

The mountaineering assessment was designed to gather data associated with some of 

the most physically demanding tasks that Marines of all MOSs could perform in a 

mountainous environment. Marines are required to conduct continuous operations in a 

variety of environments and climates, including mountainous terrain. The difficulty of the 

assessed tasks in isolation do not fully replicate life experienced by a unit during a 

Mountain Training Exercise (MTX) or combat operations in a mountainous location. 

Because of the limited amount of time available to conduct the assessment, only 

selected mountaineering tasks were assessed. Due to specific experimental constraints 

and human factor considerations, other tasks/duties outside the assessment were 

minimized. During a typical field exercise, it is common for Marines to conduct 24-hour 

operations that include daytime and nighttime operations/patrols, standing firewatch or a 

security post, and conducting continuing tactical actions. The Marines in the experiment 

were not required to bivouac in the elements, but rather slept in squad bays every night. 

Outside the assessed trials, minimal tasks were required of the volunteers that 

demanded any degree of physical strain.

Lastly, the Marines only conducted trials every other day, with a day on/day off 

schedule. This artificial recovery period (or delay in operations) is not realistic when 

conducting training or combat operations.

M.2.3 Experimental Timing Requirements

Another primary concern in designing the mountaineering assessment was throughput 

for the Marines. Only four squads were supportable given the time and space 

requirements of the SOM and the limited amount of daylight. Initially, it took a single 

squad approximately 5 hours to complete a single trial. To prevent one squad from 

influencing another, there was a 1.5-hour delay between squads. 
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M.2.4 Execution Artificialities

Several artificialities were present as the volunteers completed the SOM. Once the 

squad completed the initial 4.6-km hike, the unit arrived at the gorge to an alreadyestablished high-tension crossing site to expedite the throughput. This is realistic in the 

sense that a commander or unit leader, if supportable, could send an element forward 

of the main body and have the technical sites established. A fire team of nonvolunteers 

was emplaced at the gorge-crossing site prior to the squad’s arrival. This team assisted

with loading the individual packs onto the rope system once the squad completed the 

gorge-crossing movement, allowing the squad to complete the crossing unimpeded and 

the test team to minimize the random error inherent in the experiment created by the 

administrative movement.

Another artificiality that existed pertained to the requirement to lower Marines after 

climbing the cliff. During a typical cliff ascent, once Marines reach the top of the cliff, 

they climb over the crest and continue with the mission. Due to experimental and safety 

constraints, after the volunteers topped-out, they had another volunteer in the squad 

belay for them and lower them to the ground. The belay Marine’s technical skill level 

affected the time for total execution by the squad. An experienced individual was

comfortable lowering the climber back down to the bottom quickly, while an 

inexperienced one lowered the climber more slowly. These artificialities affected total 

performance time. 

M.2.5 Limitations Summary

The mountaineering assessment was designed to replicate realistic training in a field 

environment in mountainous terrain. The end state was to create an experiment in 

which the volunteers felt they were conducting realistic and operationally relevant tasks. 

Certain unavoidable limitations to both the assessed tasks and nonassessed operating 

environment introduced a level of artificiality that would not normally have been present 

in a field training or combat environment. 

M.3 Deviations 

M.3.1 Gorge Crossing

During initial planning and coordination with MWTC, it was established that all squads 

would utilize one high-tension system to cross the gorge. During the dry runs, however, 

the MWTC instructors and subject matter experts, or Red Hats, advised MCOTEA and 

the GCEITF leadership that they could establish two high-tension systems at the gorge 

crossing site. Both high-tension systems were the same distance and level of difficulty, 

with minimal variations. Since there was an initial concern about how long the entire 

evolution would take, MCOTEA decided to approve the deviation to gain efficiencies in 

the overall time and reduce the likelihood of a backlog at the gorge.
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Additionally, the packs that the Marines carried to the gorge crossed the high tension 

rope bridge. After all Marines crossed the gorge and the assessment time stopped, 

there was an administrative movement in which the packs were tied together and 

loaded for the squad to pull across. Groups of three Marines pulled three packs across 

in order to ensure that all Marines were under equal loading conditions.

M.3.2 Failure Criteria for the Gorge Crossing

Annex D of the Experimental Test Plan is the Data Collection Execution Matrix. As 

written, the failure criteria for the gorge crossing portion of the assessment stated that 

failure would occur once the unit took 2 hours to complete the crossing. This correlated 

to each Marine in the 12-Marine squad having 10 minutes to complete the gorge 

crossing, at which time the red hat would pull the Marine to the far side of the gorge. 

After discussion with the MWTC staff, the consensus was that, if it took a Marine more 

than 5 minutes to cross the gorge, there would be a safety concern requiring the red hat 

to facilitate completion. It was agreed that 5 minutes was acceptable for an individual 

failure on the gorge crossing. Additionally, the overall time for the squad to complete the 

gorge would be reduced to 1 hour for squad task failure. 

M.3.3 Concentration of Squad

The Test Plan stated that MCOTEA would assess three different levels of integration for 

the Rifle Squad: the control group, low-integration, and high-integration. However, prior 

to the record trial cycle beginning, the ITF population could no longer support a lowintegration group. The Infantry test team decided to eliminate the low-concentration 

group and began the record trial cycle on 5 May 2015 with the control group and highconcentration of six females per squad. 

M.3.4 Two-Day Test Event

Based on the number of Marines and squads that were expected to train at Bridgeport, 

the initial plan outlined a 3-day cycle to support 12 squads. The plan was for each 

squad to execute the trial once every 3 days. Due to volunteer attrition, however, by the 

commencement of the Bridgeport assessment, the task force was only able to fill four 

open MOS squads. This reduction allowed for the trials to be conducted over a 2-day 

cycle (1 day for open MOS squads and 1 for closed MOS squads). 

M.4 Data Set Description 

M.4.1 Data Set Overview

The open MOS portion of the Bridgeport experiment consisted of 1 pilot trial cycle day 

and 13 trial cycles. The pilot trial cycle was conducted on 5 May 2015. Because the pilot 

trial data and execution did not deviate from record trial execution, we use all pilot trial

data for analysis. The final data set includes data collected from 4 May to 18 May 2015.
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M.4.2 Record Test Volunteer Participants

At the beginning of the first pilot trial cycle, there were 46 male open MOS volunteers 

and 17 female open MOS volunteers. All Marines who began this portion of the 

experiment completed it.

M.4.3 Planned, Executed, and Analyzed Trial Cycles

Table M-1 displays the number of trial cycles planned, executed, and analyzed by task. 

The planned number of trial cycles for the open-MOS portion of Bridgeport per Section 

7.5.3 of GCEITF EAP is 60 trials, or 20 trials per planned integration level (C, LD, and 

HD). Due to the number of Marines who voluntarily withdrew or were involuntarily 

withdrawn from the experiment prior to the execution of the first record test, only two 

squads of the C and HD integration levels remained. 

The planned number of trials in Table M-1 reflects 14 planned trial cycles for each 

integration level. There were no trials on 7–9 May 2015 or on 15 May 2015, resulting in 

the loss of 4 trials per integration level.

Table M-1. Bridgeport Open MOS Planned, Executed, and Analyzed Trial Cycles

Task and 

Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

Trials 

Conducted 

Number of 

Trials Used 

in Analysis

Notes

4.6-km Hike C 14 10 10

HD 14 10 10

5-km Return 

Hike

C 14 10 9 Did not execute 14 May due to weather. 

Remove 5 May run 2 high outlier

HD 14 10 10

Gorge 

Crossing

C 14 10 10

HD 14 10 9 Missing data 17 May 

Cliff Ascent C 14 9 9 Did not execute 14 May due to weather

HD 14 10 10

4.6-km Hike; 

1-km Time

C 14 10 10

HD 14 10 10

4.6-km Hike; 

2-km Time

C 14 10 10

HD 14 10 10

4.6-km Hike; 

3-km Time

C 14 10 10

HD 14 10 10

4.6-km Hike; 

4-km Time

C 14 10 10

HD 14 10 10

4.6-km Hike; 

5-km Time

C 14 10 10

HD 14 10 10

5-km Return 

Hike; 1-km 

Time

C 14 10 10

HD 14 10 10

5-km Return 

Hike; 2-km 

Time

C 14 10 10

HD 14 10 10

5-km Return 

Hike; 3-km 

Time

C 14 10 10

HD 14 10 10

5-km Return 

Hike; 4-km 

Time

C 14 10 9 Remove influential point

HD 14 10 10

5-km Return C 14 10 10
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Task and 

Metric 

Description

Integration 

Level

Number of 

Planned 

Trials

Number of 

Trials 

Conducted 

Number of 

Trials Used 

in Analysis

Notes

Hike; 5-km 

Time HD 14 10 10

M.5 Descriptive and Basic Inferential Statistics 

M.5.1 Descriptive Statistics Overview

Performance metrics were measured during the conduct of common infantry tasks and 

are indicative of unit-level proficiency during either field exercises or combat operations. 

This section presents 4 out of 14 tasks. Bridgeport Open MOS Appendix contains the 

descriptive statistics for the remainder of the Bridgeport tasks. The words “metric” and 

“task” are used interchangeably throughout this annex. They both refer to the 

experimental task. 

Each fireteam consisted of four volunteer Marines: the fireteam leader, automatic 

rifleman, grenadier, and rifleman. Each squad consisted of 12 volunteer Marines (three 

fireteams) with a direct assignment (nonvolunteer) squad leader. There were two 

integration levels for all tasks. A (C) group was not gender integrated and a HD group 

was gender integrated with six female Marines.

This section includes experimental results based on descriptive statistics, MannWhitney Tests, and scatter plots. The subsequent sections will cover each task in detail. 

Lastly, contextual comments, additional insights, and subjective comments (as 

applicable) tying back to each experimental task are incorporated. 

Use caution when comparing similar tasks executed by different MOSs within the 

GCEITF experiment. Comparative analysis may be misleading due to differing factors 

between MOS tasks, such as distances, techniques, leadership, load carried, group 

size, and group composition.

M.5.2 Bridgeport Open MOS Selected Task Descriptive Statistics Results

The two tables that follow display the results for the four selected Bridgeport Open MOS 

metrics. Table M-2 displays the metrics and integration levels with their respective

sample sizes, means, and standard deviations. Table M-3 displays Mann-Whitney 

results, including metrics and integration levels, p-values suggesting statistical 

significance, integration level elapsed-time differences, and percentage differences 

between integration levels. For each task, a Mann-Whitney test (due to the small 

sample size) was conducted to compare the two groups. If p-values are less than the a

priori determined significance level of 0.10, we conclude that there is statistical evidence 

that the mean time or percent hits for the HD group is different from that in the C group.

Table M-2. Bridgeport Open MOS Selected Task Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD
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Metric Integration 

Level

Sample 

Size Mean SD

4.6-km Hike (minutes)*

C 10 63.38 5.99

HD 10 70.83 3.61

5-km Return Hike (minutes)* C 9 61.95 4.15

HD 10 69.03 5.46

Gorge Crossing (minutes)* C 10 17.09 1.95

HD 9 19.76 2.71

Cliff Ascent (minutes)* C 9 37.78 6.02

HD 10 45.88 9.26

Cliff Ascent (minutes) 

(influential point removed)*

C 9 37.78 6.02

HD 9 43.57 6.06

*Indicates that there is a statistically significant difference, in either a one-sided 

or two-sided hypothesis test, between integration levels according to a MannWhitney test. 

Table M-3. Bridgeport Open MOS Mann-Whitney Test Results

Metric Comparison Difference % 

Difference

2-sided 

P-Value

1-sided 

P-Value

80% 

LCB

80% 

UCB

90% 

LCB

90% 

UCB

4.6-km Hike 

(minutes) HD-C 7.45 11.75% 0.01* 0.01* 3.85 10.38 2.85 11.95

5-km Return Hike 

(minutes) HD-C 7.08 11.43% <0.01* <0.01* 3.70 10.23 2.95 11.82

Gorge Crossing 

(minutes) HD-C 2.67 15.62% 0.02* 0.01* 1.00 3.97 0.80 4.25

Cliff Ascent 

(minutes) HD-C 8.10 21.45% 0.04* 0.02* 3.20 12.10 1.65 13.18

Cliff Ascent 

(minutes) 

(potential 

influential point 

removed)

HD-C 5.79 15.34% 0.08* 0.04* 1.73 9.40 0.28 11.05

*Indicates that there is a statistically significant difference, in either a one-sided or two-sided hypothesis 

test, between integration levels according to the Mann-Whitney test.

M.5.2.1 4.6-km Hike

M.5.2.1.1 4.6-km Hike Overview

This experimental task assessed a squad of 12 Marines moving 4.60 km while each 

Marine carried a 75-lb pack (resupply load) and an M-4. The route for this movement 

was on an unimproved surface and very hilly; the terrain was hard and rocky. This 

movement consisted primarily of elevation gain (uphill) as shown in Figure M-1. The 

recorded time for this task started when the squad departed the LBC start point and 

stopped when the squad arrived at the gorge crossing site. Each squad moved as fast 

as the slowest person and could take as many breaks as necessary. 
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Figure M-1. 4.6-km Hike Elevation Profile

Figure M-2 displays all Bridgeport open MOS 4.6-km hike data. All data on the scatter 

plot are valid for analysis.

Figure M-2. 4.6-km Hike

The C group had a mean time of 63.68 minutes. This time is statistically significantly 

faster than the HD mean time of 70.83 minutes. This difference results in an 11.75%, or 

7.45-minute, degradation in hike time between the groups. The HD group has less 

variability, as shown by the 2.38-minute decrease in standard deviation (SD) (5.99 
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minutes for the C group and 3.61 minutes for the HD group). See Table M-2 and Table 

M-3 for detailed analytical results.

M.5.2.1.2 4.6-km Hike Contextual Comments

The difference in hike times is relevant to both the training and combat environment as 

it will take integrated squads more time to conduct foot marches. Per the tactical march 

standards noted in the 0311 Descriptive Statistics, the Marine Corps standard of hiking 

is 4.0 km/h. The HD group failed to meet this standard. The average C group pace was 

4.65 km/h, and the average HD group’s pace was 3.92 km/h. To extrapolate this pace 

over a 20-km movement (an optimistic assumption that does not account for any further 

degradation of performance), the HD group would finish 48 minutes behind the C group. 

Furthermore, on any given day (under the same environmental conditions), the fastest 

group was always a C group and the slowest group was always an HD group. Only on 

one instance did an HG group finish faster than a C group on a given day.

M.5.2.1.3 4.6-km Hike Additional Insights

Based on the USMC standard of a 4.0-km/h pace over a 4.6-km route (which would 

result in a 69-minute 4.6-km completion time), the HD group was 1.83 minutes slower 

than that standard. In a battlefield situation, in which speed is essential, this delay is 

advantageous for the enemy. Marine Corps Doctrinal Publications (MCDPs) 

consistently emphasize the importance of speed. MCDP 1-3 Tactics devotes an entire 

chapter to “Being Faster” and states, “Physical speed, moving more miles per hour, is a 

powerful weapon in itself.” MCDP-6 Command and Control also speaks to speed 

relative to the enemy and states, “The speed differential does not necessarily have to 

be a large one: a small advantage exploited repeatedly can quickly lead to decisive 

results. 

M.5.2.1.4 4.6-km Hike Subjective Comments

For subjective comments relating to this task, see the BP Open-MOS Appendix.

M.5.2.2 5.0-km Return Hike

M.5.2.2.1 5.0-km Return Hike Overview

This experimental task assessed a squad of 12 Marines moving 5.0 km while each 

Marine carried a 75-lb pack (resupply load) and an M-4. The route for this movement 

was on an unimproved surface and very hilly; the terrain was hard and rocky. This 

movement consisted primarily of elevation loss (downhill) as shown in Figure M-3. The 

recorded time for this task started when the squad departed the LTA and stopped when 

the squad arrived at the LBC. Each squad moved as fast as the slowest person and 

could take as many breaks as necessary. 
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Figure M-3. 5.0-km Return Hike Elevation Profile

Figure M-4 displays all Bridgeport open MOS 5.0-km return hike data. All data on the 

scatter plot are valid for analysis.

Figure M-4. 5.0-km Hike

The C group had a mean time of 61.95 minutes. This time is statistically significantly 

faster than the HD mean time of 69.03 minutes. This difference results in an 11.43%, or 

7.08-minute, degradation in hike time between the groups. The HD group has greater 

variability, as shown by the 1.31-minute increase in SD (4.15 minutes for the C group 
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and 5.46 minutes for the HD group). See Table M-2 and Table M-3 for detailed 

analytical results.

M.5.2.2.2 5.0-km Return Hike Contextual Comments

The difference in hike times is relevant to both the training and combat environment as 

it will take integrated squads more time to conduct foot marches. Per the tactical march 

standards noted in the 0311 Descriptive Statistics, the Marine Corps standard of hiking 

is 4.0 km/h. Both the C group and HD group met this standard. The average C group 

pace was 4.46 km/h, and the average HD group’s pace was 4.00 km/h. To extrapolate 

this pace over a 20-km movement (an optimistic assumption that does not account for 

any further degradation of performance), the HD group would finish 30.9 minutes behind 

the C group. Furthermore, on any given day (under the same environmental/weather 

conditions), the fastest group was always a C group and, with the exception of one trial, 

the slowest group was always a HD group.

M.5.2.2.3 5.0-km Return Hike Additional Insights

MCDPs consistently emphasize the importance of speed. MCDP 1-3 Tactics devotes an 

entire chapter to “Being Faster” and states, “Physical speed, moving more miles per 

hour, is a powerful weapon in itself.” MCDP-6 Command and Control also speaks to 

speed relative to the enemy and states, “The speed differential does not necessarily 

have to be a large one: a small advantage exploited repeatedly can quickly lead to 

decisive results.”

M.5.2.2.4 5.0-km Hike Subjective Comments

For subjective comments relating to this task, see the BP Open-MOS Appendix. 

M.5.2.3 Gorge Crossing

M.5.2.3.1 Gorge Crossing Overview

This experimental task assessed a squad of 12 Marines moving across two 200-foot 

single-rope bridges. A mountaineering expert (a red hat) was the only one authorized to 

verify knots and hook up each Marine to the rope bridge. Crossing the gorge was an 

individual task, but the recorded time was for the squad as a whole. After each Marine

reached the far side of the gorge, a squad leader reset each lane by pulling the tag-line 

back to the near side of the gorge for the next Marine. The recorded time for this task 

started when the first Marine of the squad touched the rope-bridge and stopped when 

last member of the squad was completely disconnected from the rope-bridge on the far 

side.

Figure M-5 displays all Bridgeport open MOS gorge crossing data. All data on the 

scatter plot are valid for analysis.
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Figure M-5. Gorge Crossing

The C group had a mean time of 17.09 minutes. This time is statistically significantly 

faster than the HD mean time of 19.76 minutes. This difference results in a 15.62%, or 

2.67-minute, degradation in hike time between the groups. The HD group has greater 

variability, as shown by the 1.37-minute increase in SD (1.95 minutes for the C group 

and 2.71 minutes for the HD group). See Table M-2 and Table M-3 for detailed 

analytical results.

M.5.2.3.2 Gorge Crossing Contextual Comments

Sun Tzu stated, “Speed is the essence of war. Take advantage of the enemy’s 

unpreparedness; travel by unexpected routes and strike him where he has taken no 

precautions” (MCDP-1, p. 69). Gaining this advantage in a mountainous environment 

may involve crossing a gorge. Crossing a single-rope bridge by pulling oneself across is 

a physical strain on the upper body. While no purely objective standard can be set for 

crossing a gorge, any decrement in speed translates into increased exposure to enemy 

fires and greater risk for friendly casualties. On average, the HD group took 2.67 

minutes longer than the C group. Furthermore, on any given day (under the same 

environmental conditions), the fastest group was always a C group, and, with the 

exception of one trial, the slowest group was always an HD group.

M.5.2.3.3 Gorge Crossing Additional Insights

A purely objective evaluation of 2.67 minutes is elusive but may possess some practical 

significance on the battlefield that would reduce the survivability of an integrated unit. 

Considering an enemy unit moving at 4.0 km/h on foot to defend a piece of key terrain, 

the enemy would be able to move an additional 178 meters as the HD group was still 
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crossing the gorge. Far worse would be an enemy observer who could call for fire with 

mortars, artillery, or aviation assets against the integrated group given the time delay. 

Additionally, one source of masking occurred during this task that was not anticipated 

during the design. The physically demanding aspect of this task involved pulling oneself 

across the gorge; however, the reset time was generally twice that of the execution 

time. For instance, many Marines were able to cross the gorge within 60 seconds. 

However, it consistently took approximately 2.5 minutes to unhook a Marine, pull the 

tag-line back to the near-side, and hook up the next Marine. Since six Marines went 

across each line, approximately 6 minutes were devoted to Marines crossing the gorge 

while approximately 12.5 minutes were devoted to the reset process. Strictly 

considering the performance of each Marine would magnify the results and make the 

gender-difference even greater.

M.5.2.3.4 Gorge Crossing Subjective Comments

For subjective comments relating to this task, see the BP Open-MOS Appendix.

M.5.2.4 Cliff Ascent

M.5.2.4.1 Cliff Ascent Overview

This experimental task assessed a squad of 12 Marines climbing two 40-foot technical 

rock-climbing routes. A mountaineering expert (a red hat) was the only one authorized 

to verify knots and hook up each Marine to the belay line. Climbing the cliff was an 

individual task, but the recorded time was for the squad as a whole. After each Marine

reached the top of the cliff, a fellow Marine on belay lowered the climber to the ground. 

The recorded time for this task started when the first Marine of the squad touched the 

rope and stopped when last member of the squad was completely disconnected from 

the rope.

Figure M-6 displays all Bridgeport open MOS cliff ascent data. There was one potential 

influential point—one of the HD points on trial cycle 1. Because the impact of these 

points is unknown, we perform all analysis with and without this point. All data on the 

scatter plot are valid for analysis with the potential influential point circled.
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Figure M-6. Cliff Ascent with Potential Influential Point Circled

The inclusion of the potential influential points does not change the statistical 

significance between groups. It does, however, change the SD and percentage

differences between the integration levels. Once we remove the potential influential 

points, the percentage differences between the C group and LD group, as well as the C 

group and HD group, decrease. The percentage difference between the LD and HD 

group increases. The SD for both the LD and HD groups decrease without the potential 

influential points. The following sections discuss results with and with the potential 

influential points.

M.5.2.4.1.1 Cliff Ascent Descriptive Statistics with Potential Influential Point

The C group had a mean time of 37.78 minutes. This time is statistically significantly 

faster than the HD mean time of 45.88 minutes. This difference results in a 21.45%, or 

8.10-minute, degradation in hike time between the groups. The HD group has greater 

variability, as shown by the 3.24-minute increase in SD (6.02 minutes for the C group 

and 9.26 minutes for the HD group). See Table M-2 and Table M-3 for detailed 

analytical results.

M.5.2.4.1.2 Cliff Ascent Descriptive Statistics without Potential Influential Point

The C group had a mean time of 37.78 minutes. This time is statistically significantly 

faster than the HD mean time of 43.57 minutes. This difference results in a 15.34%, or 

5.79-minute, degradation in hike time between the groups. The HD group has greater 

variability, as shown by the 3.24-minute increase in SD (6.02 minutes for the C group 

and 9.26 minutes for the HD group). See Table M-2 and Table M-3 for detailed 

analytical results.
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M.5.2.4.2 Cliff Ascent Contextual Comments

Sun Tzu stated, “Speed is the essence of war. Take advantage of the enemy’s 

unpreparedness; travel by unexpected routes and strike him where he has taken no 

precautions” (MCDP-1, p. 69). Gaining this advantage in a mountainous environment 

may involve climbing a cliff. Technical rock-climbing is a physical strain on the upper 

and lower body. While no purely objective standard can be set for climbing a cliff, any 

decrement in speed translates into an advantage to the enemy and greater risk for 

friendly casualties. On average, the HD group took 8.1 minutes longer than the C group. 

Furthermore, on any given day (under the same environmental conditions), the C group 

was always the fastest squad to finish, and, with the exception of one trial, the HD group 

was always the slowest squad to finish.

M.5.2.4.3 Cliff Ascent Additional Insights

A purely objective evaluation of 8.1 minutes is elusive but may possess some practical 

significance on the battlefield that would reduce the survivability of an integrated unit. 

Considering an enemy unit moving at 4.0 km/h on foot to defend a piece of key terrain, 

the enemy would be able to move an additional 540 meters as the HD group was still 

climbing the cliff. Far worse would be an enemy observer who could call for fire with 

mortars, artillery, or aviation assets against the integrated group given the time delay. 

The steady “learning curve” that occurred can be explained in two ways: familiarity of 

the climbing route and the masking effect of belaying. First, there were two separate, 

but similar routes that Marines had to climb. Each subsequent opportunity to climb 

involved learned techniques/behaviors that resulting in a faster climb time. Second, a 

source of masking occurred during this task that was not anticipated during the design. 

The physically demanding aspect involved climbing the cliff; however, the 

belay/lowering time was a significant part of the overall time. The belay time also got 

drastically shorter as the assessment progressed because belay Marines became more 

comfortable with this skill. Strictly considering the performance of each Marine would 

have better informed the gender-difference involved in this task.

M.5.2.4.4 Cliff Ascent Subjective Comments

For subjective comments relating to this task, see the BP Open MOS Appendix.
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Appendix to Annex M

Mountaineering Open MOSs Supplemental Information

This appendix provides supplemental information for the Mountaineering Open MOSs 

portion of the GCEITF experiment. It provides information regarding the GCEITF

leadership subjective comments and additional descriptive and basic inferential 

statistics not described in Annex M.

Section 1. GCEITF Leadership Subjective Comments

The GCEITF leadership provided comments on their observations of the experiment 

throughout its execution. Table M A displays a summary of these comments broken 

down by task, integration level, gender, and type of comment.

Table M A – Summary of GCEITF Leadership Comments

Section 2. Additional Task Basic and Inferential Statistics

Not all data collected during the experiment were used for MOS-specific task analysis 

and conclusions. The experiment included a number of tasks and associated metrics 

conducted to enhance operational realism and maintain consistent application of the 

experimental process. Where data were collected on tasks not used for analysis and 

conclusions, we simply report means, standard deviations, and percent differences. 

This section presents results for 10 additional Open MOS tasks. Annex M contains the 

descriptive statistics for the remainder of the Open MOS tasks. The words “metric” and 

“task” are used interchangeably throughout this Appendix; t. They both refer to the 

experimental task.

Task and Metric 

Description Gender Total

C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total C HD Total

M 7 0 7 4 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11

F 0 18 18 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 19

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

F 0 8 8 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 9

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

M 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

F 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2

Unit 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Gorge Crossing

Cliff Ascent

Other No category

4.6-km Hike

5-km Return Hike

Falling 

behind/slowing 

movement

Requesting extra 

breaks

Requires extra 

assistance

Needs no 

assistance

Compensating 

for another 

Marine

Gear pass off
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The table below displays the results for 10 additional Open MOS metrics. Table M B

displays the metrics and integration levels with their respective sample sizes, means, 

standard deviations, and percent differences between integration levels.

Table M B – Bridgeport Open MOS Test Results (Descriptive Statistics)

Metric Integration 

Level

Sample 

Size Mean SD

% 

Difference

(HD-C)

4.6-km Hike; first km 

(minutes)

C 10 10.27 0.50 7.90%

HD 10 11.08 0.37

4.6-km Hike; second km 

(minutes)

C 10 11.09 0.53 17.37% HD 10 13.02 0.63

4.6-km Hike; third km 

(minutes)

C 10 13.91 2.65 7.19% HD 10 14.91 1.54

4.6-km Hike; fourth km 

(minutes)

C 10 18.06 3.77 12.22% HD 10 20.45 2.60

4.6-km Hike; fifth km 

(minutes)

C 10 10.05 0.97 13.14% HD 10 11.37 0.73

Return Hike; first km 

(minutes)

C 10 12.80 0.76 18.79% HD 10 15.20 1.00

Return Hike; second km 

(minutes)

C 10 13.83 2.82 6.70% HD 10 14.76 1.09

Return Hike; third km 

(minutes)

C 10 11.42 0.73 4.32% HD 10 11.91 1.31

Return Hike; fourth km 

(minutes)

C 10 10.87 1.37 8.72% HD 10 11.81 1.26

Return Hike; fourth km 

[excluding potential 

influential point] (minutes)

C 9 10.51 0.84

12.38% HD 10 11.81 1.26

Return Hike; fifth km 

(minutes)

C 10 14.58 1.29 5.18% HD 10 15.34 1.68

Additional Task Results: 

4.6-km Hike by km. The general trend for the 4.6-km hike was that the difference 

between the HD and C groups increased over the course of the hike. These differences 

are largest during the points of the largest elevation change.

Return Hike by km. The general trend for the return hike was that the difference 

between the HD and C groups increased over the course of the hike. These differences 

are largest during the points of the largest elevation change.
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Annex N. 

Fatigue, Workload, and Cohesion Surveys

This annex details the results of the three self-report surveys (Fatigue, Workload, and 

Unit Cohesion) administered to all volunteers—in keeping with their respective MOS’

Schemes of Maneuver—during the Ground Combat Element Integrated Task Force 

(GCEITF) experiment executed from 2 March – 18 May 2015. In the sections below, we 

outline Survey Design and Collection, Limitations, Data Set Description, and Detailed 

Survey Results.

N.1 Survey Design and Collection

N.1.1 Survey Design Overview

Three different surveys were administered—sometimes multiple times per trial—to 

GCEITF volunteers during the course of each run-cycle. All had been originally 

designed, or modified, to permit “in-stream” administration (to minimize interruption to 

each MOS’ Scheme of Maneuver). 

Two surveys—the individual Fatigue and Workload surveys—had been derived from the 

Crew Status Survey instrument, in order for Marines to self-report their perceived levels 

of fatigue (i.e., weariness or exhaustion from labor) and relative workload following 

some or all tasks within a trial. 

For the Fatigue survey, volunteers were asked to pick the statement on a seven-point 

(ordinal) scale that best described how they felt at that moment, ranging from “1 – Fully 

Alert, Wide Awake; Extremely Peppy” to “7 – Completely Exhausted; Unable to Function 

Effectively; Ready to Drop”. 

For the workload survey—also on a seven-point (ordinal) scale—volunteers were asked 

to pick both the statement that best described the maximum workload they had 

experienced during the preceding work period, as well as their average workload during 

that period; responses could range from “1 – Nothing to do; No Task Demands” to “7 – 

Unmanageable; Potentially Dangerous; Unacceptable”. 

Unlike the original Crew Status Survey form—which can be found in the Experimental 

Assessment Plan (EAP), Annex D—we allowed the Fatigue and Workload surveys to be 

administered independently, and did not allow free-form comments. 

The third survey—the Unit Cohesion survey—had been taken from the Group

Environmental Questionnaire (GEQ), specifically its Group Integration-Task (GI-T) subsection (see EAP, Annex M). Our survey had five statements (Q1 – Q5) designed to 
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query an individual’s beliefs about their team’s relatively closeness, similarity, and 

bonding around a group’s task. Responses fell along a nine-point Likert scale, with 

volunteers reporting what number best indicated their level of agreement with each 

statement, where “1” indicated strongly disagree and “9” indicated strongly agree. 

N.1.2 Survey Administration and Collection

Our primary method for administering the surveys was on the same portable

Toughbooks used by data collectors to collect observational data. At the appropriate 

break in each scenario (either before, during, or after), the data collection program 

would display the appropriate survey to be taken. The order each survey was to be 

taken was also fixed, based on billet. In the event that a volunteer was not available 

(either temporarily or because they’d been dropped from the trial or the study), the data 

collector could defer a particular survey or mark it not taken/invalid. 

Marines responded to the survey by touching the appropriate multiple choice box—

using either the Toughbook stylus or their finger tip. Volunteers would then hit “enter” to 

save their response—ensuring the anonymity of their responses. In the event of 

Toughbook failure, all data collectors carried paper backup copies and pens. Volunteers 

would fill out their response and return the paper to the data collector, who would add 

their Experimental ID code (EID), unit run order, and MOS in order to properly tie the 

paper backups to the correct trial. 

Surveys were not administered to non-trial (i.e., loading units). 

N.1.2.1 Pre-Trial Surveys

All volunteers participating in a trial run were given a pre-trial (i.e., baseline) Fatigue 

survey prior to the start of their trial. This was intended as a way to recognize when task 

or trial-specific fatigue results might have been influenced by initial fatigue levels.

N.1.2.2 Post-Trial Surveys

All volunteers participating in a trial were also given post-trial Fatigue and Workload 

surveys after completing their final task. Efforts were made to administer the surveys as 

close to the end of the trial as possible, although on occasion, range safety 

requirements necessitated that a survey be administered once the volunteers had come 

off the range and/or the range had gone cold. 

In addition to the post-trial surveys, volunteers were given the Unit Cohesion survey 

following the last trial in their respective run-cycles. 

N.1.2.3 Mid-Trial Surveys

In addition to the pre- and post-trial surveys mentioned above—which were given to all 

volunteers, regardless of MOS—some MOS also incorporated mid-trial surveys into 
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their data collection plan. Where mid-trial Workload surveys were administered, data 

collectors instructed the volunteers to respond with their maximum and average 

workload levels over a work period defined as the period since their last survey. If no

mid-trial surveys were administered, the work period was defined as the entire trial 

period. We discuss each mid-trial survey, when they occur, within each MOS section 

below.

N.2 Limitations 

N.2.1 Limitations Overview

Unlike much of the quantitative data collected, analyzed, and presented elsewhere in 

this study, there are some additional limitations that should be taken into consideration 

with regards to survey results. 

N.2.1.1 Respondent Biases

All surveys results represent volunteers’ self-reports about their internal perceptions. As 

such, their responses are subject to potential (intentional and unintentional) biases. 

Some common types of bias include:

• Acquiescence – respondents answer based upon what they think the questioner 

wants to hear (or contrary to what they think they want to hear)

• Response fatigue – respondents answer in a uniform or inaccurate manner due 

to excessive survey requests or duration 

• End aversion – respondents avoid selecting values at either end; also known as 

central tendency 

• Yea- and nay-saying – respondents have a more or less global tendency answer 

positively or negatively

• Social desirability – respondents avoid responding with, or under-report, answers 

that might be viewed as socially unacceptable to the group

One reason we chose our primary method for collecting survey data (i.e., volunteers 

privately entered their responses directly into the Toughbook) was to attempt to mitigate 

against acquiescence and social desirability biases. We also limited, where possible, 

the number of times each survey was administered during a trial and streamlined the 

process as much as possible in order to stave off response fatigue biases. However, 

there is no way to completely protect against response bias, so we have tried to be 

cautious in the conclusions we draw below. 

N.2.1.2 Original Survey Design 

Our surveys also have certain limitations based upon their initial design. For example, 

the Fatigue and Workload surveys were taken from the Crew Status Survey 
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instrument—which was designed to compare the fatigue and workload perceptions of 

each air crew member against their own previous responses over the course of their 

shift. For this purpose, the Crew Status survey designers had been able to verify the 

repeatability of each response level.

However, the Crew Status survey was not specifically designed to compare results 

between individuals—there being no way to know that different people will use the same 

internal criteria for selecting one response over another, beyond the wording of each 

potential response. As such, we caution against drawing too much from comparisons of 

fatigue and workload results between groups. 

In addition, all three surveys (Fatigue, Workload, and Unit Cohesion) have subjectivelydefined (i.e., ordinal) intervals, and as such we are not able to use most parametric 

analysis methods that make use of mathematical manipulation of the data. Statistical 

significance, where found, do not indicate a statistical difference between means—only 

that the two (or more) populations under inspection are sufficiently dissimilar.

N.2.1.3 Consistency of Administration

As mentioned above in Survey Administration and Collection, we scripted when and 

where each survey was taken into each MOS’ Scheme of Maneuver. Every effort was 

made to ensure consistency in administration. However, changes to run order, 

unplanned interruptions, and range safety demands—to name a few—did, on occasion, 

interfere with survey administration and so it was not always possible to ensure 

consistency in the conditions under which each survey was conducted. 

N.2.1.4 Inter-MOS variability

Because each MOS Scheme of Maneuver was independently designed and executed, 

with different definitions for unit size, task load, and integration level, we cannot directly 

compare survey results between different MOS groups—not even if, on the face of it, 

they have very similar Schemes of Maneuvers (e.g., 0331s and Provisional Machine 

Gunners). 

N.3 Data Set Description 

N.3.1 Data Set Overview

For the purposes of this annex, our data set includes all Fatigue, Workload, and Unit 

Cohesion surveys completed by members of a valid, trial unit. 

Baseline fatigue results were included, regardless of whether that individual actually

completed a trial. Mid- and Post-Trial survey results were kept as long as the FTMs and 

Data Managers for each site determined that the tasks conducted during the course of a 

trial were sufficiently consistent with the Scheme of Maneuver to maintain proper 
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loading and division of labor (i.e., did not suffer from gross deviations in the execution of 

the trial). 

We did not remove any outliers. We only culled individual responses if the response 

was not that of the Marine identified on the roster for that unit and billet (e.g., another 

Marine accidentally responded out of order). In some instances, Marines simply failed to 

complete all or some elements of a survey. The actual number of responses used for 

any particular analysis is detailed within the appropriate MOS-specific section below.

N.4 Detailed Survey Results 

N.4.1 Analytical Approach Overview

As outlined in the GCEITF Experimental Assessment Plan (EAP), we focused primarily 

on the differences between male and female responses (i.e., gender differences) within 

the same MOS, and differences (in males’ responses1

) based upon integration level. 

This does not constitute the totality of analysis that we believe could be done with this 

data set and additional analysis—at some future date—may be desirable to gain 

additional insight potential drivers for the results collected.

Also, as previously mentioned above, survey responses are subjective (and ordinal) in 

nature. Responses can impart relative order but this does not imply even distribution 

along the scale2

. As such, care should be taken to not draw conclusions based upon 

assumptions of equal intervals. 

N.4.2 Infantry Rifleman (0311)

N.4.2.1 Fatigue Results

For the 0311 volunteers at Twentynine Palms, we have baseline, mid-trial, and final 

fatigue self-reports from 34 males and nine females. Because fatigue survey responses 

were ordinal in nature, we restricted our statistical analysis to the non-parametric 

Kruskal-Wallis (rank sum) test to check for significance between factors, using the 

criteria of p ≤ 0.10 for statistical significance (*). 

N.4.2.1.1 Fatigue Results by Gender

We first looked at looking at how fatigue self-reports compared between males and 

females, including their baseline (pre-trial), their final (post-trial, for both days in the runcycle), and post-7km Hike (mid-trial, Defense trials) fatigue levels. Results are 

summarized in the table below (Table 1).

 

1 By definition, females were only present in integrated groups. 

2 For example, an ordinal response of “1” is less than “2” and “2” is less than “3”, but the difference between “1” 

and “2” may not be equal to the difference between “2” and “3”.
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Table 1 - Summary of Pre-Trial, Mid-Trial, and Final Fatigue Scores (by Gender) - 0311

N.4.2.1.1.1 Pre-Trial Fatigue Scores (by Gender)

We found a significant difference between female and male 0311 volunteers’ pre-trial 

fatigue scores. Males tended to report being less fatigued, with responses typically 

clustered around “1-Fully Alert” (25.6%), “2-Very Lively” (36.8%), and “3-Okay” (24.5%), 

whereas females most often reported being “3-Okay” (61.0%) or “4-A Little Tired” 

(22.0%) before the start of a trial (Table 2). 

However, we found very few of the higher fatigue scores for either gender (i.e., “5-

Moderately Tired”, “6-Extremely Tired”, or “7-Exhausted”)—only 2.4 percent of male 

responses (driven largely by one Marine), and 3.7 percent of female responses (driven 

entirely by two Marines)—and no obvious pattern of increasing scores over time, 

suggesting volunteers largely had sufficient recovery time between trials. 

N.4.2.1.1.2 Final Fatigue Scores (by Gender)

In looking at the volunteers’ post-trial responses, we found significant differences in the 

distribution of scores—by gender—for both days of the 0311 trial-cycle. While the 

majority of male responses were clustered within the “2-Very Lively” to “3-Okay” range 

for both days (56.3% for Offense trials, 52.9% for Defense trials), females’ post-trial 

responses in this same range were far fewer—i.e., 28.6% and 30.0%, respectively. 

Females more often reported being either “4-A Little Tired” or “5-Moderately Tired” 

(59.5% for “Offense” scenario, 67.5% for the “Defense” scenario). Similar to pre-trial 

results for both genders, we saw few examples of fatigue reports (4 reports from males, 

10 reports from females) in the highest levels (“6-Extremely Tired”, “7-Exhausted”); in all 

cases, these were associated with Offense trials. 

N.4.2.1.1.3 Post-7km Hike Fatigue Scores (by Gender)

For the Defense scenario, 0311 volunteers also completed a fatigue survey following 

the completion of their 7km Hike under load; we found a significant difference in the 

distributions of male and female fatigue responses for this survey as well. 

MOS Fatigue Location / 

Day Gender N Median / Mode χ2 

Statistic

χ2 pValue

0311

Baseline

(Pre-Trial) 29Palms/1,2

M 903 2 / 2

56.6 <0.01*

F 82 3 / 3

Post-7km

(Mid-Trial)

29Palms/2 

“Defense”

M 450 3 / 3

36.1 <0.01*

F 39 5 / 5

Final

(Post-Trial)

29Palms/1 

“Offense”

M 439 3 / 3

27.8 <0.01*

F 42 4 / 4

29Palms/2 

“Defense”

M 451 4 / 3

23.9 <0.01*

F 40 4 / 4
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We found the single most post-7km Hike scores for males at “3-Okay” (29.6%), but with 

a relatively flat span (13% to 19%) of responses on either side—from “1-Fully Alert” to 

“5-Moderately Tired”. 

A similar pattern was found for female responses, but shifted to the right with their peak 

(35.9%) at “5-Moderately Tired”, with other responses spanning from “3-Okay” (23.1%) 

to “6-Extremely Tired” (15.4%). As the female responses for the post-7km hike extend 

more to the right (i.e., more fatigued) than their post-trial responses for the same day, 

some recovery may have been occurring. 

Table 2 - Pre-Trial, Mid-Trial, and Final Fatigue Score Distributions (by Gender) - 0311

N.4.2.1.2 Fatigue Results by Integration Level

Next, we looked at whether males fatigue responses remained consistent at different 

integration levels. For 0311s, we compared males’ responses in Control (i.e., all-male) 

and High-Density (i.e., 2 females) Rifle Squads. We have mid-trial and final fatigue selfreports from 34 males (33 in the Control group and 34 in the High-Density group); 

statistical results are summarized in the table below (Table 3). 
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Table 3 – Summary of Males’ Mid-Trial and Final Fatigue Scores (by Integration Level) - 0311

N.4.2.1.2.1 Post-7km Hike Fatigue Scores (by Integration Level)

Following the 7km Hike under load (Defense trials), we found the distribution of males’ 

fatigue responses in High-Density Rifle Squads to be significantly different (in the 

direction of less fatigued) with more responses (40.7%) in the “1-Fully Alert” to “2-Very 

Lively” range, compared to Control groups (33.3%), despite peaks for both at “3-Okay”. 

One potential reason for this shift could be the slower average pace typically seen in 

High-Density groups for the 7km Hike (see Annex A). However, this does not appear to 

be universal for all males because we still see a (non-trivial) number of male responses 

for both groups in the “4-A Little Tired” and “5-Moderately Tired” (32.1% in Control 

groups versus 29.9% in High-Density groups). 

Regardless, with a majority of female responses (53.8%, representing five of the nine 

females) in integrated groups falling in the higher levels post-hike (“5-Moderately Tired”, 

“6-Extremely Tired”, and “7-Exhausted”), it does appear that a substantial number of 

female 0311 volunteers were “pushing it” to maintain the pace set by their unit (see 

Table 2 above). 

N.4.2.1.2.2 Final Fatigue Scores (by Integration Level)

Post-trial fatigue results by Integration Level proved to be mixed—males’ responses 

were significantly different between the two groups (Control and High-Density) for the 

Defense, but not for the Offense, scenario. 

As with the distributions seen following the 7km Hike, for post-Defense trials we see a 

slight increase in the number of male responses in the “1-Fully Alert” to “2-Very Lively” 

range for High-Density groups (42.9%) compared to Control groups (32.4%), along with 

a corresponding (and slight) decrease in their responses at “3-Okay” and above. 

However, if a slower pace could be the mechanism driving some males towards less 

fatigue post-7km hike, and post-trial on Defense trials, why is this not seen for Offense 

trials, which also found slower speeds (on average) for integrated groups on a number 

of tasks (see Annex A)? 

MOS Fatigue Location / Day IL N Median / 

Mode

χ2 

Statistic

χ2 pValue

0311

Post-7km

(Mid-Trial)

29Palms/2 

“Defense”

C 246 3 / 3

3.6 0.06*

HD 204 3 / 3

Final

(Post-Trial)

29Palms/1 

“Offense”

C 235 3 / 3

0.34 0.56

HD 204 3 / 3

29Palms/2 

“Defense”

C 247 3 / 3

6.0 0.01*

HD 204 3 / 3
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It may be that it’s not simply pace, but the period over which it’s maintained (i.e., a 

cumulative effect)—possibly in combination with the higher pack-weight found in 

Defense trials—that drives a shift in fatigue for some males. Should relative pace and 

duration be the factor driving this difference in fatigue reports, we might expect a similar 

pattern to present—or strengthen—for tasks of greater duration and/or which drive a 

greater difference in pace (e.g., longer hikes). If pack-weight is a contributing factor, 

lighter pack-weights (or those scaled to a Marine’s relative body-mass) over a similar 

7km hike distance, might reduce the number of males in Control groups reporting “6-

Extremely Tired” or “7-Exhausted”, while maintaining the same pace. 

Table 4 – Males’ Mid-Trial and Final Fatigue Score Distributions (by Integration Level) - 0311

N.4.2.2 Workload Results

For the 0311 volunteers at Twentynine Palms, we have maximum workload self-reports 

from 34 males and nine females3. Because workload survey responses were ordinal in 

nature, we restricted our statistical analysis to the non-parametric Kruskal-Wallis (rank 

sum) test to check for significance between factors, using the criteria of p ≤ 0.10 for 

statistical significance (*). 

N.4.2.2.1 Workload Results by Gender

We first looked at how maximum workload self-reports compared between males and 

females, for both days in their run-cycle. Results are summarized in the table below 

(Table 5). 

 

3 One male and two females only participated in two trials (each). 
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Table 5 - Summary of Maximum Workload Scores (by Gender) – 0311

We found a significant difference between female and male 0311 volunteers’ maximum 

workload scores for both days (Offense and Defense scenarios). In both cases, we 

found males slightly more likely (44.4%) to report lower maximum workload levels (“3-

Active but Easy” and lower) than females (26.8%), although both groups had their peak 

at “4-Challenging” (Table 6). 

We found few of the highest max workload scores for either group (i.e., “6-Overloaded” 

or “7-Unmanageable”)—only 2.0 percent of male responses4 and 2.4 percent of female 

responses (a single response). This suggests most Marines (regardless of gender) felt 

capable of accomplishing, if not always easily, the workload assigned them. 

The difference seen between the two groups may be due to females having less time in 

the MOS; if so, we would expect the difference between the two groups to gradually

disappear over time as they became more skilled—and hence more comfortable—in 

their responsibilities. Additionally, females’ higher representation at “4-Challenging” and 

“5-Extremely Busy” may have been influenced by their slightly higher levels of fatigue, 

since even relatively low levels of fatigue can degrade concentration and performance 

of non-rote skills. 

Table 6 – Maximum Workload Score Distributions (by Gender) - 0311

 

4 Eight 0311 males reported a max workload of “6-Overloaded” or “7-Unmanageable”, though most did so only 

once or twice. One Marine reported a max workload in the range ten times—split between both scenarios.

MOS Workload Location / 

Day Gender N Median / 

Mode

χ2 

Statistic

χ2 pValue

0311

Final

(Max Workload 

for Trial)

29Palms/1

“Offense”

M 448 4 / 4

4.1 0.04*

F 41 4 / 4

29Palms/2

“Defense”

M 452 4 / 4

4.5 0.03*

F 40 4 / 4
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N.4.2.2.2 Workload Results by Integration Level

In addition to looking at how maximum workload self-reports compared between males 

and females, we also examined whether males’ fatigue responses remained consistent 

at different integration levels. For 0311s, we compared males’ responses in Control (i.e., 

all-male) and High-Density (i.e., 2 females) Rifle Squads. We have maximum workload 

self-reports from 34 males (33 in the Control group and 34 in the High-Density group); 

statistical results are summarized in the table below (Table 7). 

Table 7 - Summary of Males’ Maximum Workload Scores (by Integration Level) – 0311

We saw a significant difference between males’ responses in Control and High-Density 

groups. For both days, we saw a slight depression in their reported maximum workload 

levels (towards more manageable) in the High-Density group—with more reports at “3-

Active but Easy” (Table 8)—than the number seen in the Control group. 

It may be that the slightly slower times associated—on average—with High-Density 

squads (see Annex A) allowed some males to have an easier time addressing the 

workload demands of the scenario. However, without greater fidelity as to what tasks 

elicited their max scores, we can’t say whether this is a viable theory.

Alternatively, integrated groups may have showed greater collaboration between 

members (i.e., spreading the “load”) than Control groups. However, as most tasks were 

collected at the unit—and not at the individual—level, this would need to be explored 

through follow-on work.

Table 8 - Males’ Maximum Workload Score Distributions (by Integration Level) - 0311

MOS Workload Location / 

Day IL N Median / 

Mode

χ2 

Statistic

χ2 pValue

0311

Final

(Max Workload for 

Trial)

29Palms/1

“Offense”

C 239 4 / 4 3.3 0.07* HD 209 4 / 4

29Palms/2

“Defense”

C 248 4 / 4 8.5 <0.01* HD 204 4 / 4
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N.4.2.3 Cohesion Results

For the 0311 volunteers at Twentynine Palms, we have Unit Cohesion survey results 

(with five statements per survey) from 34 males and nine females5. Cohesion responses 

for each statement were set on a nine-point, Likert scale (one indicating “Strongly 

Disagree” and nine indicating “Strongly Agree”). 

Because the cohesion responses consistently violated the normality and independence 

assumptions for parametric data, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). 

N.4.2.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five responses, which scaled between 5 and 45)—compared between 

males and females, following the conclusion of their unit’s run-cycle. Statistical results 

are summarized in the table below (Table 9).

Table 9 - Summary of Unit Cohesion Scores (by Gender) – 0311

We found mixed results; males and females had significantly different responses on 

only two statements, “Q4-Help” (i.e., the group’s willingness to help a struggling 

member) and “Q5-Comm” (i.e., the group communicating freely about responsibilities), 

with females reporting more pessimistic responses than males for both.

When we looked more closely at the response distributions of both statements, we 

found females responses for both tended to cluster more strongly between “4” and “6” 

 

5 Two females and one male only participated in two units (each).

MOS Cohesion Gender N Mean SD χ2 

Statistic

χ2 pValue

0311

Q1: Group was united in trying to 

reach goals

M 453 6.18 1.71

0.64 0.43

F 39 6.06 1.96

Q2: We all take responsibility for 

task success of the group

M 453 6.15 1.82

1.06 0.30

F 39 5.92 1.99

Q3: Group members have similar 

aspirations for success

M 453 5.92 1.90

0.12 0.72

F 39 5.92 1.91

Q4: If members had problems 

with a task, all wanted to help

M 453 6.02 1.84

4.53 0.03*

F 39 5.56 1.79

Q5: Members communicated 

freely about responsibilities

M 453 6.34 1.82

4.18 0.04*

F 39 5.85 1.86

Composite Score (sum of Q1-Q5)

Lowest: 5 | Highest 45 

M 453 30.59 8.16

1.71 0.19

F 39 29.31 9.04
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(71.8% for “Q4-Help” and 61.5% for “Q5-Comm”)—straddling both sides of neutral. On 

the other hand, males’ responses to both statements tended to cluster between “5” to 

“8” (78.6% for “Q4-Help” and 80.6% for “Q5-Comm”)—spanning neutral to strong 

agreement.

One potential reason for the difference in perceptions between males and females for 

just these two components could have been differences in relative experience within the 

MOS. Females could have been seeking a greater degree of cooperation and 

communication to offset their inexperience than the more experienced males might 

have felt necessary. 

We did not, however, find a significant difference in perceptions for the other three 

statements (“Q1-Unity”, “Q2-Responsibility”, and “Q3-Aspirations”), nor between their 

overall composite cohesion scores, suggesting a general agreement in the range of 

their groups’ respective cohesiveness in terms of goals and motivation. 

We also graphed the means for each statement as a percentage of how strongly the 

volunteers agreed (positive) or disagreed (negative) with each survey statement (Figure 

1). For the 0311 volunteers, we can see how both genders—while more positive than 

negative—appeared to be somewhat neutral in their perceptions of unit cohesion (with 

sharper divergence for “Q4-Help” and “Q5-Comm”).

Figure 1 - Perception of Unit Cohesion (by Gender) – 0311

N.4.2.3.2 Cohesion Results by Integration Level

In addition to looking at how unit cohesion scores compared between males and 

females, we also examined whether males’ cohesion responses remained consistent at 

different integration levels. For 0311s, we compared males’ responses in Control (i.e., 

all-male) and High-Density (i.e., 2 females) Rifle Squads. We have Unit Cohesion 
GCEITF EAR ANNEX N

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survey results (five statements per survey) from 34 males (33 in the Control group and 

34 in the High-Density group); statistical results are summarized in the table below 

(Table 10).

Table 10 - Summary of Males' Unit Cohesion Scores (by Integration Level) - 0311

We found a statistical difference—by integration level—between all five cohesion 

statements, as well as for the overall composite cohesion score. When we looked at the 

distributions for each statement, we saw a slight shift towards more agreement

(responses ranging between “5” and “8”) in the Control group (79.5% to 87.2%) over 

those found in the High-Density group (74.4% to 78.9%) along with a corresponding dip 

in the Control group’s representation in the lower levels (below “5”). 

We also graphed the means for each statement as a percentage of how strongly males 

agreed (positive) or disagreed (negative) with each question’s statement while in each 

group (Figure 2). While the figure is consistent with our statistical results—i.e., males in 

Control groups in slightly stronger agreement about unit cohesion than males in HighDensity groups—we can see that, regardless of integration level, males were fairly 

neutral overall. 

Unfortunately, the survey did not provide for reasons as to why males were more likely 

to choose lower cohesion scores when in an integrated group. Differences in relative 

experience may have been a driver—creating a perception of unequal contribution to 

the group effort. Incidentally, the average values for the integrated groups appear to 

align well with how females rated their perceptions of unit cohesiveness.

MOS Cohesion IL N 

(scores) Mean SD χ2 

Statistic

χ2 pValue

0311

Q1: Group was united in trying to 

reach goals

C 249 6.31 1.69

4.86 0.03*

HD 204 6.02 1.72

Q2: We all take responsibility for 

task success of the group

C 249 6.28 1.78

3.70 0.05*

HD 204 5.98 1.86

Q3: Group members have similar 

aspirations for success

C 249 6.04 1.89

3.04 0.08*

HD 204 5.77 1.92

Q4: If members had problems 

with a task, all wanted to help

C 249 6.15 1.85

4.60 0.03*

HD 204 5.87 1.81

Q5: Members communicated 

freely about responsibilities

C 249 6.47 1.81

4.22 0.04*

HD 204 6.18 1.82

Composite Score (sum of Q1-Q5)

Lowest: 5 | Highest 45

C 249 31.24 8.15

4.82 0.03*

HD 204 29.78 8.12
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Figure 2 - Perception of Unit Cohesion (by Integration Level) – 0311

N.4.3 Infantry Machine Gunner (MOS 0331)

N.4.3.1 Fatigue Results

For the 0331 volunteers at Twentynine Palms, we have baseline, mid-trial, and final 

fatigue self-reports from six males and six females. Because Fatigue survey responses 

were ordinal in nature, we restricted our statistical analysis to the non-parametric 

Kruskal-Wallis (rank sum) test to check for significance between factors, using the 

criteria of p ≤ 0.10 for statistical significance (*). Where we had more than two groups to 

compare—and if the Kruskal-Wallis test showed significance for similarity—then we

conducted Wilcoxon pairwise comparisons (using p<0.033 to adjust for multiple 

comparisons). 

N.4.3.1.1 Fatigue Results by Gender

We first looked at how fatigue self-reports compared between males and females, 

including their baseline (pre-trial), final (post-trial, for both days in the run-cycle), and 

post-7km Hike (mid-trial, Defense trials) fatigue levels. Results are summarized in the 

table below (Table 11). 
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Table 11 - Summary of Pre-Trial, Mid-Trial, and Final Fatigue Scores (by Gender) - 0331

N.4.3.1.1.1 Pre-Trial Fatigue Scores

We found a significant difference between female and male 0331 volunteers’ pre-trial 

fatigue scores. Males’ responses were heavily clustered around “1-Fully Alert” (53.8%) 

and “2-Very Lively” (41.5%), whereas females’ scores showed a more shallow 

distribution spanning “1-Fully Alert” (22.0%), “2-Very Lively” (38.1%), and “3-Okay” 

(25.4%) before the start of a trial (Table 12). 

In addition, we found very few of the higher fatigue scores for either gender (i.e., “5-

Moderately Tired”, “6-Extremely Tired”, or “7-Exhausted”)—only a single male response

(0.4%), and six female responses (5.1%) of which all but one were driven by a single 

Marine. There was no obvious pattern of increasing scores over time, suggesting 

volunteers had sufficient recovery time between trials. 

N.4.3.1.1.2 Final Fatigue Scores

In looking at the volunteers’ post-trial responses, we found a significant differences in 

the distribution of male and female scores for only one scenario—Offense trials. For 

these trials, both genders showed a relatively shallow distribution of scores in the low to 

medium range (Table 12). Males clustered between “2-Very Lively” and “4-A Little Tired” 

(peaking at “3-Okay” with 31.3% of responses), while and females clustered across a 

slightly broader range between “2-Very Lively” and “5-Moderately Tired” (but also 

peaking at “3-Okay” with 24.1% of their responses). The results for Defense trials were 

not significant. 

For both days and genders, we did see some final fatigue scores in the higher “5-

Moderately Tired” to “6-Extremely Tired” range. Unlike pre-trial results—where the 

handful of higher-than-average scores were driven primarily by two Marines (one male 

and one female)—these higher post-trial fatigue scores were distributed across all 12 

volunteers over the course of the experiment, suggesting all Marines had been highly 

fatigued, on occasions. But, this appears to have been relatively rare, since we also see 

MOS Fatigue Location / 

Day Gender N Median / Mode χ2 

Statistic χ2 p-Value

0331

Baseline 

(Pre-Trial) 29Palms/1,2

M 236 1 / 1

60.2 <0.01*

F 118 2 / 2

Post-7km

(Mid-Trial)

29Palms/2

“Defense”

M 117 3 / 3

1.4 0.24

F 59 3 / 3

Final

(Post-Trial)

29Palms/1

“Offense”

M 115 3 / 3

3.8 0.05*

F 58 3.5 / 3

29Palms/2

“Defense”

M 118 3 / 3

2.5 0.11

F 59 3 / 3
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greater representation by both genders, and among most of the volunteers (six males 

and five females), in the lower fatigue levels (i.e., “3-Okay” and lower). 

N.4.3.1.1.3 Post-7km Hike Fatigue Scores

For the Defense scenario, 0331 volunteers also completed a fatigue survey following 

the completion of their 7km Hike under load; we did not find a significant difference in 

male and female responses; both groups had peak responses at “3-Okay”. 

Table 12 - Pre-Trial, Mid-Trial, and Final Fatigue Score Distributions (by Gender) - 0331

N.4.3.1.2 Fatigue Results by Integration Level

Next, we looked at whether males fatigue responses remained consistent at different 

integration levels. For 0331s, we compared males’ responses in Control (i.e., all-male),

Low-Density (i.e., 1 female), and High-Density (i.e., 2 females) Machine Gun Teams.

We have mid-trial and final fatigue self-reports from six males (six in the Control and 

Low-Density groups, and five males for High-Density groups); statistical results are 

summarized in the table below (Table 13). 
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Table 13 – Summary of Males’ Mid-Trial and Final Fatigue Scores (by Integration Level) - 0331

N.4.3.1.2.1 Post-7km Hike Fatigue Scores (by Integration Level)

Following the 7km Hike, we found the distribution of males’ fatigue responses in Control 

teams to be significantly different from both Low-Density and High-Density MG Teams. 

For both integrated groups, males’ fatigue scores were shifted lower (towards less 

fatigue), with a much higher number of responses at “2-Very Lively” fatigue level (54.3% 

and 66.7%, for Low-Density and High-Density groups, respectively) compared to the 

Control group (16.4%). At the same time, we also saw a corresponding drop in their 

responses in integrated groups at the medium to high range levels (between “4-A Little 

Tired” and “6-Extremely Tired”), which suggests males were less fatigued when 

participating in an integrated group (Table 14). 

One potential reason for the decrease in males’ post-hike fatigue scores for integrated 

groups is their slower (on average) pace on the hike compared to Control groups (see 

Annex C). However, it is possible motivation or willingness to “push it” also differed 

between integrated and non-integrated groups. 

As we saw in the fatigue results by gender, the majority of female responses following 

the 7km hike were “4-A Little Tired” or below (83.1%)—suggesting many female 

respondents might have been able to handle a more aggressive pace and/or were 

deliberately choosing a level of exertion that would allow for a greater energy reserve 

for follow-on tasks. 

MO

S Fatigue Location / 

Day IL N Median 

/ Mode

χ2 

Statistic

χ2 pValue

Z-Test 

Statisti

c

Z-Test 

p-Value

0331

Post-7km

(Mid-Trial)

29Palms/2 

“Defense”

C 61 3 / 3

25.3 <0.01*

(LD-C)

-3.6 <0.01*

LD 35 2 / 2 (HD-C)

-4.3 <0.01*

HD 21 2 / 2 (HD-LD)

-1.8 0.07

Final

(Post-Trial)

29Palms/1 

“Offense”

C 59 3 / 3

12.3 <0.01*

(LD-C)

-0.87 0.39

LD 36 3 / 3 (HD-C)

-3.6 <0.01*

HD 20 2 / 2 (HD-LD)

-2.4 0.02*

29Palms/2 

“Defense”

C 62 3 / 3

8.7 0.01*

(LD-C)

-1.2 0.23

LD 35 3 / 2,3 (HD-C)

-2.8 <0.01* 

HD 21 2 / 2 (HD-LD)

-2.2 0.03*
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Conversely, all-male groups appear more willing to push a pace that results—on 

occasion—in some males (11.5%) reporting themselves to be “5-Moderately Tired” or 

“Extremely Tired” following the conclusion of the hike, compared to integrated groups 

(only 2.9% of responses in Low-Density groups; zero responses in High-Density 

groups). 

N.4.3.1.2.2 Final Fatigue Scores (by Integration Level)

Post-trial fatigue results by Integration Level for 0331s proved to be mixed—males’ 

responses were significantly different between Control groups and High-Density groups, 

and between High-Density and Low-Density groups, regardless of day in the trial-cycle. 

However, we found no significant difference in males’ fatigue responses between 

Control groups and Low-Density groups for either day in the run-cycle. 

For High-Density groups—similar to the post-7km hike results—we saw the distribution 

of males’ scores shifting left (i.e., towards less fatigued), with a sharp rise (65.0%) in the 

number of scores in the lowest levels (“1-Fully Alert”, “2-Very Lively”), compared to 

Control (22.0%) and Low-Density groups (30.6%). 

As was hypothesized for the 7km hike results, it may be that this decrease in males’ 

fatigue responses in integrated groups is tied to the slower tempo typically seen for 

integrated units performing movement-related tasks (see Annex C). 

However, as we also saw for the post-7km Hike results, female final fatigue scores in 

integrated units were also still largely distributed in the lower levels (“4-A Little Tired” 

and below)—for both Offense (70.7%) and Defense (94.9%)—with representation from 

all six female 0331 volunteers. This raises the potential that integrated units were 

setting tempos that neither gender found particularly taxing (i.e., not “pushing it”)—

perhaps because they lacked sufficient motivation or were attempting to reserve energy 

for follow-on tasks. 

Alternatively, it may be that all or some volunteers in integrated units were underrepresenting their physical fatigue levels on the surveys, and the trial tempos achieved 

properly reflect physical ability. Given the relatively small size of the 0331 volunteer pool 

(six males and six females), we should be cautious in extrapolating their results to the 

larger Marine Corps 0331 community. 
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Table 14 – Males’ Mid-Trial and Final Fatigue Score Distributions (by Integration Level) - 0311

N.4.3.2 Workload Results

For the 0331 volunteers at Twentynine Palms, we have maximum workload self-reports 

from six males and six females. Because workload survey responses were ordinal in 

nature, we restricted our statistical analysis to the non-parametric Kruskal-Wallis (rank 

sum) test to check for significance between factors, using the criteria of p ≤ 0.10 for 

statistical significance (*). Where we had more than two groups to compare—and if the 

Kruskal-Wallis test showed significance for similarity—then we conducted Wilcoxon 

pairwise comparisons (using p<0.033 to adjust for multiple comparisons).

N.4.3.2.1 Workload Results by Gender

We first looked at looking at how maximum workload self-reports compared between 

males and females, for both days in their run-cycle. Statistical results are summarized in 

the table below (Table 15) 

Table 15 - Summary of Maximum Workload Scores (by Gender) – 0331

We found a significant difference between female and male 0331 volunteers’ maximum 

workload scores for both days (Offense and Defense scenarios). In both cases, we 

MOS Workload Location / 

Day Gender N Median / 

Mode

χ2 

Statistic

χ2 pValue

0331

Max 

Workload for 

Trial

29Palms/1

“Offense”

M 116 4 / 4

28.8 <0.01*

F 58 4 / 4

29Palms/2

“Defense”

M 120 4 / 4

15.8 <0.01*

F 60 4 / 5
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found males more likely to report maximum scores between “3-Active but Easy” and “4-

Challenging” (79.3% and 79.2%, for Offense and Defense, respectively) than females, 

who favored scores between “4-Challenging” and “5-Extremely Busy” for both days 

(84.5% and 78.3%, respectively) (Table 16). 

For both genders, we also saw a very small number of reports of “6-Overloaded”—three 

from each group, though only one female reported in this range more than once (and 

only for a fraction of her total trials). This suggests most 0331 Marines—regardless of 

gender—felt capable of accomplishing (if not always easily) their assigned workload. 

Table 16 - Maximum Workload Score Distributions (by Gender) - 0331

The difference between the two groups may be due to females having less time in the 

MOS; if so, we would expect the difference between males and females to gradually 

disappear over time. It may have also been influenced by the slightly higher levels of 

fatigue reported by female 0331s, since even relatively low levels of fatigue can 

degrade concentration and performance on non-rote skills. 

N.4.3.2.2 Workload Results by Integration Level

In addition to looking at how maximum workload self-reports compared between males 

and females, we also examined whether males workload responses remained 

consistent at different integration levels. For 0331s, we compared males’ responses in 

Control (i.e., all-male), Low-Density (i.e., 1 female), and High-Density (i.e., 2 females) 

Machine Gun Teams. We have maximum workload self-reports from six males (six in 

the Control and Low-Density groups, and five in the High-Density group); statistical 

results are summarized in the table below (Table 17). 
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Table 17 - Summary of Males' Maximum Workload Scores (by Integration Level) - 0331

We saw a significant difference in males’ responses between Control and both Lowand High-Density groups (but not between integrated groups). In the integrated groups, 

we see a shift in males’ responses toward lower maximum workload scores (i.e., 

towards more manageable), centered more strongly at “3-Active but Easy”—instead of 

“4-Challenging”—for both days (Table 18). 

As we saw in the analysis by gender above, we found very few of the highest maximum 

workload scores at any Integration Level—only three male responses in total. But, 

among the next lower level (i.e., “5-Extremely Busy”), which is on the border for 

managing the workload, we see both the number of contributors—and the number of 

responses per contributor—decrease in the integrated groups (i.e., more males 

persistently found their workload to be more manageable in an integrated group). 

As far as possible mechanisms, it may be that Control groups, with their slightly faster 

times (on average) were more likely to set tempos that every volunteer struggled with 

on occasion (see Annex C). However, perhaps the slower tempos of integrated MG 

Teams allowed more males to have an easier time addressing the workload demands of 

the scenario. However, without greater fidelity as to what tasks tended to elicit the 

Marines’ maximum workload reports, it’s difficult to say whether this is a viable theory. 

Alternatively, it may be that integrated groups showed greater collaboration (i.e., 

spreading the “load”) than Control groups. However, as most tasks were collected at the 

unit—and not at the individual—level, this would need to be explored through follow-on 

work, with a larger 0331 volunteer pool than what was used in this study. 

MOS Workload Location 

/ Day IL N Median 

/ Mode

χ2 

Statisti

c

χ2 pValue

Z-Test 

Statisti

c

Z-Test 

p-Value

0331 

Max 

Workload 

for Trial

29Palms/

1 

“Offense”

C 60 4 / 4

15.6 <0.01*

(LD-C)

-2.2 0.03*

LD 36 3.5 / 3 (HD-C)

-3.8 <0.01*

HD 20 3 / 3 (HD-LD)

-1.9 0.06

29Palms/

2 

“Defense”

C 63 4 / 4

28.3 <0.01*

(LD-C)

-4.8 <0.01*

LD 36 3 / 3 (HD-C)

-3.7 <0.01*

HD 21 3 / 3 (HD-LD)

-0.47 0.64
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Table 18 - Males’ Maximum Workload Score Distributions (by Integration Level) - 0331

N.4.3.3 Cohesion Results

For the 0331 volunteers at Twentynine Palms, we have Unit Cohesion survey results 

(five statements per survey) from six males and six females. Cohesion responses for 

each statement were set on a nine-point, Likert scale (one indicating “Strongly 

Disagree” and nine indicating “Strongly Agree”). 

Because the cohesion responses consistently violated the normality and independence

assumptions for parametric data, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). Where we had more than two 

groups to compare—and if the Kruskal-Wallis test showed significance for similarity—

then we conducted Wilcoxon pairwise comparisons (using p<0.033 to adjust for multiple 

comparisons).

N.4.3.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five responses, which scaled between 5 and 45)—compared between 

males and females, following the conclusion of their unit’s run-cycle. Statistical results

are summarized in the table below (Table 19).
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Table 19 - Summary of Unit Cohesion Scores (by Gender) - 0331

We found significant differences between genders for four of the five cohesion 

statements (“Q1-Unity”, “Q2-Responsibility”, “Q3-Aspirations”, and “Q5-Comm”), as well 

as for the overall composite cohesion score. When we look more closely at the 

distribution of 0331 responses for each statements, we see females tending to be a bit 

more optimistic (i.e., higher scores) than males, though both groups tended towards 

rather strong agreement in their units’ cohesiveness.

For all of the statements (Q1-Q5), we see a majority of scores from both genders at 

level “9”—the strongest agreement with each statement, and a high indicator of unit 

cohesion. For the four questions where we saw a significant difference between the 

genders (“Q1-Unity”, “Q2-Responsibility”, “Q3-Aspirations”, and “Q5-Comm”), a small 

but visible percentage of responses were present in the “6” to “8” range for males 

(representing between 24.4% and 31.1% of their responses). By comparison, female 

scores in this same range were fewer, only representing between 8.3% and 16.7% of 

their responses, respectively. 

For the one question where we did not see a significant difference (i.e., “Q4-Help”), both 

males and females showed the same pattern as seen among the males’ responses to 

other questions: the majority of responses (71.4% and 73.3%, for males and females, 

respectively) at the strongest level of agreement, “9”, with a small but visible percentage 

in that same “6” to “8” range (23.5% and 23.3%, respectively).The increase in these 

lower levels among females suggest they felt a bit more pessimistic—at least on 

occasion—about their units’ willingness to help those who struggled. 

We also graphed the means for each survey statement as a percentage of how strongly 

the volunteers agreed (positive) or disagreed (negative) with each survey statement 

MOS Cohesion Gender N 

(scores) Mean SD χ2 

Statistic

χ2 pValue

0331

Q1: Group was united in trying to 

reach goals

M 119 8.08 1.73

8.08 <0.01*

F 60 8.45 1.69

Q2: We all take responsibility for 

task success of the group

M 119 8.38 1.25

4.38 0.04*

F 60 8.53 1.50

Q3: Group members have similar 

aspirations for success

M 119 7.92 1.80

7.01 0.01*

F 60 8.47 1.56

Q4: If members had problems 

with a task, all wanted to help

M 119 8.39 1.37

0.02 0.88

F 60 8.40 1.36

Q5: Members communicated 

freely about responsibilities

M 119 8.34 1.39

6.28 0.01*

F 60 8.65 1.38

Composite Score (sum of Q1-Q5)

Lowest: 5 | Highest 45

M 119 41.12 6.77

6.64 0.01*

F 60 42.50 6.80
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(Figure 3). The average values (by gender) are reflective of our statistical results—with 

generally high perceptions of unit cohesion across the board, but with males slightly 

more pessimistic than females on the majority of survey statements. 

Figure 3 - Perception of Unit Cohesion (by Gender) – 0331

N.4.3.3.2 Cohesion Results by Integration Level

In addition to looking at how unit cohesion scores compared between males and 

females, we also examined whether males’ cohesion responses remained consistent at 

different integration levels. For 0331s, we compared males’ responses in Control (i.e., 

all-male), Low-Density (i.e., 1 female), and High-Density (i.e., 2 females) Machine Gun 

Teams. We have unit cohesion survey results (five statements per survey) from six 

males (six in the Control and Low-Density groups, and five in the High-Density group); 

statistical results are summarized in the table below (Table 20).
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Table 20 - Summary of Males' Unit Cohesion Scores (by Integration Level) - 0331

We found significant differences between the Control and both Low- and High-Density 

groups for all five cohesion statements, as well as for their overall composite cohesion 

scores. However, we did not see a statistically significant difference between the Lowand High-Density groups. 

When we look more closely at the distributions for all three groups, we see very sharp 

peaks at level “9” (i.e., Strongly Agree) across all statements for Control groups (from 

90% to 97% of all responses). By comparison, the integrated groups have only a 

fraction of “9s” (ranging from 33% to 45% for Low-Density groups, and from 19% to 

MOS Cohesion Gender N Mean SD χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test 

p-Value

0331

Q1: Group was united 

in trying to reach goals

C 62 8.77 1.09

46.60 <0.01*

(LD-C)

-6.04 <0.01*

LD 36 7.58 1.70 (HD-C)

-6.21 <0.01*

HD 21 6.90 2.36 (HD-LD)

-0.93 0.35

Q2: We all take 

responsibility for task 

success of the group

C 62 8.94 0.40

42.96 <0.01*

(LD-C)

-6.09 <0.01*

LD 36 7.94 1.17 (HD-C)

-5.98 <0.01*

HD 21 7.48 2.04 (HD-LD)

-0.49 0.63

Q3: Group members 

have similar aspirations 

for success

C 62 8.69 1.21

45.98 <0.01*

(LD-C)

-5.88 <0.01*

LD 36 7.31 1.77 (HD-C)

-6.11 <0.01*

HD 21 6.71 2.26 (HD-LD)

-0.91 0.36

Q4: If members had 

problems with a task, 

all wanted to help

C 62 8.92 0.52

38.92 <0.01*

(LD-C)

-6.07 <0.01*

LD 36 7.94 1.33 (HD-C)

-5.28 <0.01*

HD 21 7.62 2.29 (HD-LD)

0.28 0.78

Q5: Members 

communicated freely 

about responsibilities

C 62 8.94 0.31

39.30 <0.01*

(LD-C)

-5.68 <0.01*

LD 36 7.94 1.33 (HD-C)

-5.74 <0.01*

HD 21 7.29 2.33 (HD-LD)

-0.70 0.48

Composite Score 

(sum of Q1-Q5)

Lowest: 5 | Highest 45

C 62 44.26 3.35

47.95 <0.01*

(LD-C)

-6.25 <0.01

LD 36 38.72 6.10 (HD-C)

-6.31 <0.01

HD 21 36.00 10.12 (HD-LD)

-0.78 0.44
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48% for High-Density groups), with more (though sporadic) representation between the 

“5” and “8” levels. In other words, males appear to have felt strongly cohesive when in 

an all-male unit, but their perceptions dropped to neutral to moderate levels when in an 

integrated group. 

We also graphed the means for each statement as a percentage of how strongly males 

agreed (positive) or disagreed (negative) with each question’s statement while in each 

group (Figure 4). 

Figure 4 - Perception of Unit Cohesion (by Integration Level) - 0331

The average values (by integration level) are generally consistent6 with what we saw 

with regards to males’ very high perceptions of unit cohesion within the Control group, 

along with the more pessimistic scores they reported while in Low-Density and HighDensity groups. 

Unfortunately, the survey did not provide for reasons as to why males were more likely 

to choose lower cohesion scores when in an integrated group—especially for a shift so 

large—but the experiential differential between males and females may have been a 

factor. We should also keep in mind that these are the result of only six Marines, who 

may or may not be representative for the larger 0331 community. 

Incidentally, these are profoundly different perceptions—especially for the High-Density 

group—from the average values reported by females (see Figure 3). Given the very 

small unit size, and that females would have represented a significant (or even major) 

 

6 While there appears to be a large difference between the Low-Density and High-Density groups’ medians, we 

cannot say this is a significant difference using the Kruskal-Wallis (rank sum) test. We did not find a statistical 

difference between the two integrated groups’ responses. 
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percentage of the total unit, it may be some of the males’ perceptions may have been 

adversely affected by a different (vice a truly non-cohesive) group dynamic.

N.4.4 Infantry Mortarman (MOS 0341)

N.4.4.1 Fatigue Results

For the 0341 volunteers at Twentynine Palms, we have baseline, mid-trial, and final 

fatigue self-reports from eight males7 and four females. Because fatigue survey 

responses were ordinal in nature, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). 

N.4.4.1.1 Fatigue Results by Gender

We first looked at how fatigue self-reports compared between males and females, 

including their baseline (pre-trial), final (post-trial, for both days in the run-cycle), and 

post-7km Hike (mid-trial, Day 2) fatigue levels. Results are summarized in the table 

below (Table 21). 

Table 21 - Summary of Pre-Trial, Mid-Trial, and Final Fatigue Scores (by Gender) – 0341

N.4.4.1.1.1 Pre-Trial Fatigue Scores (by Gender)

We did not find a significant difference between female and male 0341 volunteers’ pretrial fatigue scores. However, we did observe a few peculiarities between the two 

populations (Table 22). 

For example, where female pre-trial responses were tightly clustered at “2-Very Lively” 

and “3-Okay” (90.1%), males had a more shallow distribution spread between “1-Fully 

Alert” and “3-Okay” (64.8%) with a secondary, smaller peak at “7-Exhausted” (14.5%).

 

7 One male only participated in two trials.

MOS Fatigue Day Gender N 

(scores)

Median 

/ Mode

χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

0341

Baseline 

(Pre-Trial) 1,2

M 256 3 / 1

1.9 0.17 (F-M) 

-1.4 0.17

F 91 2 / 2

Post-7km

(Mid-Trial)

2 

“Defense”

M 128 3 / 3,4

0.02 0.88 (F-M) 

0.15 0.88

F 43 4 / 4

Final

(Post-Trial)

1 

“Offense”

M 130 4 / 4

8.08 <0.01* (F-M) 

-2.84 <0.01*

F 46 4 / 4

2 

“Defense”

M 128 4 / 3

0.28 0.60 (F-M) 

-0.52 0.60

F 45 3 / 3 
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Looking more closely at the source of this secondary peak in males, we found that four 

males (out of eight) repeatedly reported baseline fatigue scores of “6-Extremely Tired” 

or “7-Exhausted” (18.8%) throughout the course of the study. In comparison, female 

reports in this same range represented only 1.1%--or a single response. This suggests 

that a substantial number of males in this MOS felt they were seriously fatigued (at 

times) before they even began a trial. 

In a cursory exam of discrete trials where volunteers reported being “6-Extremely Tired” 

or “7-Exhausted” during the pre-trial survey, we found that two-thirds (66.7%) of the time 

they reported being only “5-Moderately Tired” or less by the final fatigue survey—i.e., 

they felt more energized after the trial. However, even the nearly8 one-third (31.3%) of 

the time when they also reported being highly fatigued (i.e., “6” or “7”) after a trial, they 

had obviously completed it. This suggests these males’ high-fatigue scores may have 

had a major mental component, rather than being purely physical9 in nature. 

N.4.4.1.1.2 Final Fatigue Scores (by Gender)

In looking at the volunteers’ post-trial responses, we found mixed results. We found a 

significant difference between genders following the Offense scenario, but not for the 

Defense scenario. The majority of female post-trial responses for Offense trials were 

clustered between “3-Okay” and “4-A Little Tired” (76.1%), whereas the corresponding 

male responses were more loosely spread between “3-Okay” and “5-Moderately Tired” 

(68.8%). We also found a number of male responses (15.6%) at the highest range (“6-

Extremely Tired” and “7-Exhausted”) that were not reported for females. 

It is unclear why males may have been more likely to feel a bit more fatigued than 

females, but only for the Offense scenario. It may be that the circumstances that led to 

half of the males reporting very high pre-trial fatigue levels (“6-Extremely Tired”, “7-

Exhausted”)—be they physical or mental—were compounded by the more rapid pace 

required by the Offense scenario. 

For both males and females, we saw the majority of post-trial fatigue responses for Day 

2/Defense largely at “3-Okay” or “4-A Little Tired”. 

N.4.4.1.1.3 Post-7km Hike Fatigue Scores

For the Defense trial scenario, 0341 volunteers also completed a fatigue survey 

following the completion of their 7km Hike under load; we did not find a significant 

difference in the distributions of male and female responses for survey. 

 

8 One volunteer who reported a pre-trial fatigue of “7-Exhausted” did not complete a final survey. 9 In bio-mechanical terms, “fatigue” typically refers a temporary (i.e., non-pathological) reduction in the ability of 

muscle fibers to generate force (i.e., contract), such as after vigorous exercise.
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Table 22 - Pre-Trial, Mid-Trial, and Final Fatigue Score Distributions (by Gender) - 0341

N.4.4.1.2 Fatigue Results by Integration Level

Next, we looked at whether males fatigue responses remained consistent at different 

integration levels. For 0341s, we compared males’ responses in Control (i.e., all-male) 

and High-Density (i.e., 2 females) Mortar Teams or Squads. We have mid-trial and final 

fatigue self-reports from eight males; statistical results are summarized in the table 

below (Table 23). 

Table 23 – Summary of Males’ Mid-Trial and Final Fatigue Scores (by Integration Level) - 0341 

N.4.4.1.2.1 Post-7km Hike Fatigue Scores

Following the 7km Hike under load (Defense scenario trials), we found the distribution of 

males’ fatigue responses in High-Density Mortar Squads to be significantly different

from those in Control groups—towards less fatigued. 

Instead of a fairly even spread in the “3-Okay” to “5-Moderately Tired” range seen in 

Control units, males in the integrated group were slightly more likely to respond with just

“3-Okay” or “4-A Little Tired” (up to 51.1% from 47.0%), with an additional bump in 

responses in the lowest ranges (up to 24.4% from 10.8%). Males in the Control group 

MOS Fatigue Location / 

Day IL N 

(scores)

Median / 

Mode

χ2 

Statistic

χ2 pValue

0341

Post-7km

(Mid-Trial)

29Palms/2

“Defense”

C 83 4 / 4

8.2 <0.01*

HD 45 3 / 3

Final

(Post-Trial)

29Palms/1

“Offense”

C 84 4 / 4

0.54 0.46

HD 46 4 / 4

29Palms/2

“Defense”

C 83 4 / 3

6.0 0.02*

HD 45 3 / 4
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were also much more likely to report being “6-Extremely Tired” or “7-Exhausted” 

(20.5%), than those in the integrated group (6.6%)

One potential reason for this difference might be the relative paces set by the two 

groups. High-Density groups typically took more time to complete the 7km hike (see 

Annex D)—perhaps setting a more manageable speed than some Control groups, for 

some of the males. 

N.4.4.1.2.2 Final Fatigue Scores

Post-trial fatigue results by Integration Level for 0341s proved to be mixed—males’ 

responses were significantly different between the two groups (Control and HighDensity) for the Defense, but not for the Offense, scenario. 

As with the distributions seen following the 7km Hike, for post-Defense trials we see a 

generalized shift towards lower fatigue levels for males in integrated groups—more 

likely to respond with a fatigue score of “3-Okay” or lower (62.2%) than Control (42.2%). 

Within the Defense scenario, the 7km Hike seems the mostly likely candidate driving the 

post-trial difference between Control and High-Density groups. However, if a slower 

pace could result in some males feeling less fatigued post-7km hike (and hence posttrial) within the Defense scenario, we might expect to see a similar effect for Offense 

trials, which also showed slower movements (on average) for integrated groups (see 

Annex D)—but we don’t.

It may be that the slower movements for Offensive trials were too short—as well as 

interspersed by non-movement tasks—to sufficiently influence males’ fatigue levels. If 

relative pace and duration was driving this difference, we might expect a similar pattern 

to present—or strengthen—for tasks of greater duration and/or which drive a greater 

difference in pace (e.g., longer hikes). 

Pack-weight may also have been a contributing factor (which included the 81-mm 

mortar system split between the unit), so lighter pack-weights (or those scaled to a 

Marine’s relative body-mass) over a similar 7km hike distance, might reduce the number 

of males in Control groups reporting “6-Extremely Tired” or “7-Exhausted”.
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Table 24 – Males’ Mid-Trial and Final Fatigue Score Distributions (by Integration Level) - 0341 

N.4.4.2 Workload Results

For the 0341 volunteers at Twentynine Palms, we have max workload self-reports from 

eight males10 and four females. Because workload survey responses were ordinal in 

nature, we restricted our statistical analysis to the non-parametric Kruskal-Wallis (rank 

sum) test to check for significance between factors, using the criteria of p ≤ 0.10 for 

statistical significance (*). If we had more than two groups to compare—and if the 

Kruskal-Wallis test showed significance for similarity—then we conducted Wilcoxon 

pairwise comparisons (using p<0.033 to adjust for multiple comparisons).

N.4.4.2.1 Workload Results by Gender

We first looked at looking at how maximum workload self-reports compared between 

males and females, for both days in their run-cycle. Results are summarized in the table 

below (Table 25) 

Table 25 - Summary of Maximum Workload Scores (by Gender) – 0341

We did not find a significant difference between female and male 0341 volunteers’ 

maximum workload scores for either day. Both groups typically had maximum workload 

 

10 One male only participated in only two trials.

MOS Workload Location / Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

0341

Max 

Workload for 

Trial

29Palms/1

“Offense” 

M 130 4 / 4 1.5 0.22

F 46 4 / 4

29Palms/2

“Defense”

M 129 4 / 4 0.79 0.37

F 45 4 / 4
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scores clustering between “3-Active by Easy” and “5-Extremely Tired” (77.5% to 83.8% 

and 88.9% to 93.5% for males and females, respectively Table 26). 

For the highest maximum workload scores (i.e., “6-Overloaded”, “7-Unmanageable”), 

we also found a small, but not inconsequential number of reports (12.3% to 14.7% 

among males, and 6.5% to 11.1% among females) suggesting some Marines felt 

overwhelmed by their workload. When we looked more closely at the contributors to 

these scores, we see that three of the five male11 contributors had quite a few reports 

(eight to 16 reports each), as did the sole female contributor (eight reports). 

Given both the small size of this volunteer pool (only eight males and four females), and 

the signs that a substantial number may have struggled—at times—to accomplish the

necessary workload, we should be cautious in extrapolating the 0341 study results to 

the larger Marine Corps community. 

Table 26 - Maximum Workload Score Distributions (by Gender) - 0341

N.4.4.2.2 Workload Results by Integration Level

In addition to looking at how maximum workload self-reports compared between males 

and females, we also examined whether males’ responses remained consistent at 

different integration levels. For 0341s, we compared males’ responses in Control (i.e., 

all-male) and High-Density (i.e., 2 females) Mortar Teams and Squads. We have 

maximum workload self-reports from eight males; statistical results are summarized in 

the table below (Table 27). 

 

11 One of the male contributors who only reported a single max workload score in the highest range only 

participated in a single run-cycle.
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Table 27 - Summary of Males' Max Workload Scores (by Integration Level) - 0341

We found mixed results when we looked at males’ maximum workload responses 

between Control and High-Density groups—statistically significant for Defense trials but 

not for Offense trials. 

For the Defense trials, males in a High-Density group were more likely to have 

maximum workload responses clustered at the slightly lower “3-Active but Easy” and “4-

Challenging” range (54.3%), than males in Control groups, who more responded in the 

“4-Challenging” and “5-Extremely Busy” range (66.3%) (Table 28). 

As for possible mechanisms, it is unlikely that a slower tempo is a factor, since the more 

workload-intensive portion of the Defense scenario (i.e., 81-mm Mortar Engagement) 

did not reveal any difference in times between Control and integrated groups (Annex D). 

However, the difference in reported maximum workloads trials for Defense trials is 

consistent with the higher fatigue results reported by males in Control groups—for 

Defense (and not Offense) trials (see Table 24)—given that even relatively low 

increases in fatigue levels can degrade concentration and performance. 

Table 28 - Males’ Max Workload Score Distributions (by Integration Level) - 0341

MOS Workload Location / 

Day IL N Median / 

Mode

χ2 

Statistic

χ2 pValue

0341

Max 

Workload for 

Trial

29Palms/1

“Offense”

C 84 4 / 4

0.55 0.46

HD 46 4 / 4

29Palms/2

“Defense”

C 83 5 / 5

10.5 <0.01*

HD 46 4 / 3
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N.4.4.3 Cohesion Results

For the 0341 volunteers at Twentynine Palms, we have Unit Cohesion survey results 

(five statements per survey) from eight males and four females. Cohesion responses for 

each statement were set on a nine-point, Likert scale (one indicating “Strongly 

Disagree” and nine indicating “Strongly Agree”). 

Because the cohesion responses consistently violated the normality and independence 

assumptions for parametric data, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). 

N.4.4.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five responses, which scaled between 5 and 45)—compared between 

males and females, following the conclusion of their unit’s run-cycle. Statistical results

are summarized in the table below (Table 29).

Table 29 - Summary of Unit Cohesion Scores (by Gender) - 0341

We found a significant difference between 0341 males and females for all five cohesion

statements (“Q1-Unity”, “Q2-Responsibility”, “Q3-Aspirations”, “Q4-Help” and “Q5-

Comm”), as well as for the overall composite cohesion score. When we look more 

closely at the distribution of 0341 responses for each statement, we see males tending 

to be a bit more optimistic (i.e., higher scores) than females, though both groups have 

the majority of their responses in the top three levels (towards strongly agree). 

For males, their highest contributions occur at the highest level (ranging from 66.9% to 

68.5%) and tapering off quickly over the next few lower levels, but with non-zero 

MOS Cohesion Gender N Mean SD χ2 

Statistic

χ2 pValue

0341

Q1: Group was united in trying to 

reach goals

M 130 7.98 1.87

7.34 <0.01*

F 45 7.62 1.76

Q2: We all take responsibility for 

task success of the group

M 130 8.00 1.86

3.25 0.07*

F 45 8.02 1.22

Q3: Group members have similar 

aspirations for success

M 130 7.92 2.02

5.54 0.02*

F 45 7.69 1.58

Q4: If members had problems 

with a task, all wanted to help

M 130 8.01 1.90

4.39 0.04*

F 45 7.76 1.65

Q5: Members communicated 

freely about responsibilities

M 130 8.01 1.93

3.56 0.06*

F 45 8.02 1.14

Composite Score (sum of Q1-Q5)

Lowest: 5 | Highest 45

M 130 39.92 9.39

4.03 0.04*

F 45 39.11 6.18
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responses (1% to 2%) all the way down to “1” (i.e., Strongly Disagree). Females show 

far fewer contributions at level “9” (ranging from 35.6% to 46.7%) for any question—with 

much more shallow tapers at “7” and “8”—but fewer responses below “5”. 

We also graphed the means for each survey statement as a percentage of how strongly 

the volunteers agreed (positive) or disagreed (negative) with each survey statement

(Figure 5). 

The average values (by gender) shown reflect the generally high perception of unit 

cohesion we found across the board for both genders, with males a bit more optimistic 

than females for most statements. Where the means for males appear to be on par with 

females’ responses, we can see the influence of the relatively few (but profoundly) 

negative (i.e., towards Strongly Disagree) cohesion scores that males’ reported. 

Figure 5 - Perception of Unit Cohesion (by Gender) – 0341

N.4.4.3.2 Cohesion Results by Integration Level

In addition to looking at how unit cohesion scores compared between males and 

females, we also examined whether males’ cohesion responses remained consistent at 

different integration levels. For 0341s, we compared males’ responses in Control (i.e., 

all-male) and High-Density (i.e., 2 females) Mortar Teams and Squads. We have unit 

cohesion survey results (five statements per survey) from eight males; statistical results 

are summarized in the table below (Table 30).
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Table 30 - Summary of Males' Unit Cohesion Scores (by Integration Level) - 0341

We found a significant difference between the Control and High-Density groups for all 

five cohesion statements, as well as for the overall composite cohesion score. When we 

look more closely at the distributions, we see a single sharp peak at level “9” when in 

the Control group (76%, for all statements), and much shorter peaks (52% to 57%), 

though still largely singular, in the High-Density group. For the integrated group, we also 

see small, but steady responses (2% to 18%) all the way down to “1” not seen in 

Control groups. 

We also graphed the means for each statement as a percentage of how strongly males 

agreed (positive) or disagreed (negative) with each question’s statement while in each 

group (Figure 6).

Figure 6 - Males' Perception of Unit Cohesion (by Integration Level) - 0341

MOS Cohesion IL N Mean SD χ2 

Statistic

χ2 pValue

0341

Q1: Group was united in trying to 

reach goals

C 84 8.51 1.11

14.22 <0.01*

HD 44 7.11 2.38

Q2: We all take responsibility for 

task success of the group

C 84 8.51 1.12

13.13 <0.01*

HD 44 7.18 2.37

Q3: Group members have similar 

aspirations for success

C 84 8.51 1.12

12.43 <0.01*

HD 44 6.95 2.66

Q4: If members had problems 

with a task, all wanted to help

C 84 8.50 1.15

10.45 <0.01*

HD 44 7.22 2.46

Q5: Members communicated 

freely about responsibilities

C 84 8.54 1.10

11.85 <0.01*

HD 44 7.16 2.54

Composite Score (sum of Q1-Q5)

Lowest: 5 | Highest 45

C 84 42.57 5.58

13.91 <0.01*

HD 44 35.64 11.97
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The average values shown are consistent with what we saw with regards to males’ very 

high perceptions of unit cohesion within the Control group, along with the sharp decline 

in their perception of cohesion when in the High-Density group. 

Unfortunately, the survey did not provide for reasons as to why males were more likely 

to choose lower cohesion scores when in an integrated group, but differences in relative 

experience between males and females may have been a factor. We should also keep 

in mind that these are the result of only eight Marines, who may or may not be 

representative for the larger 0341 community. 

Incidentally, these results differ quite a bit from how females rated their perception of 

unit cohesiveness in integrated groups; they were quite a bit more optimistic (see Figure 

5). With the small unit size—and the fact that males would have had equal numbers 

with the females—some of their perceptions may have been colored by a different (vice 

a truly non-cohesive) group dynamic. 

N.4.5 Infantry Assaultman (0351) / Antitank Missileman (0352)

N.4.5.1 Fatigue Results

For the 035X volunteers at Twentynine Palms, we have baseline, mid-trial, and final 

fatigue self-reports from six males and six females12. Because fatigue survey responses 

were ordinal in nature, we restricted our statistical analysis to the non-parametric 

Kruskal-Wallis (rank sum) test to check for significance between factors, using the 

criteria of p ≤ 0.10 for statistical significance (*). 

N.4.5.1.1 Fatigue Results by Gender

We first looked at how fatigue self-reports compared between males and females, 

including their baseline (pre-trial), final (post-trial, for both days in the run-cycle), and 

post-7km Hike (mid-trial, Day 2) fatigue levels. Statistical results are summarized in the 

table below (Table 31). 

 

12 One female only participated in two trials.
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Table 31 - Summary of Pre-Trial, Mid-Trial, and Final Fatigue Scores (by Gender) – 035X

N.4.5.1.1.1 Pre-Trial Fatigue Scores (by Gender)

We found a significant difference between female and male 035X volunteers’ pre-trial 

fatigue scores, with males more likely to report being slightly less fatigued. Males’ 

responses typically clustered around “1-Fully Alert” (35.4%) and “2-Very Lively” (43.9%), 

whereas females were more likely to report being “2-Very Lively” (38.9%) or “3-Okay” 

(36.2%) before the start of a trial (Table 32).

We found very few of the higher fatigue scores (i.e., “5-Moderately Tired”, “6-Extremely 

Tired”, or “7-Exhausted”) for either gender—only 3.2 percent of male responses (driven 

largely by one Marine), and 2.0 percent of female responses (one response each by two 

Marines)—and no obvious pattern of increasing scores over time, suggesting volunteers 

largely had sufficient recovery time between trials. 

N.4.5.1.1.2 Final Fatigue Scores (by Gender)

In looking at the volunteers’ post-trial responses, we found significant differences in the 

distribution of scores for both days of the 035X run-cycle (i.e., Offense and Defense), in 

favor of generally lower fatigue scores for males. Most male responses were clustered 

within the “2-Very Lively” to “3-Okay” range for Offense trials (84.4%) and “1-Fully Alert” 

to “3-Okay” for Defense trials (95.8%). 

On the other hand, most females’ responses were shifted slightly higher, with postOffense scores strongly clustered from “3-Okay” to “5-A Little Tired” (91.8%) and postDefense scores from “2-Very Tired” to “A Little Tired” (84.5%). Female also had greater

(though not a lot of) representation in the highest ranges (i.e., “6-Extremely Tired” and 

“7-Exhausted”) on both days—with 6.8% post-Offense, 4.2% post-Defense—than males 

(2.1% and zero, respectively). 

N.4.5.1.1.3 Post-7km Hike Fatigue Scores (by Gender)

For the Defense trial scenario, 035X volunteers also completed a fatigue survey 

following the completion of their 7km Hike under load. As with post-trial results, males 

MOS Fatigue Day Gender N Median / 

Mode

χ2 

Statistic

χ2 pValue

035X

Baseline 

(Pre-Trial) 1,2

M 189 2 / 2

65.8 <0.01*

F 149 3 / 2

Post-7km

(Mid-Trial)

2 

“Defense”

M 94 3 / 3

38.5 <0.01*

F 70 4 / 4

Final

(Post-Trial)

1 

“Offense”

M 96 3 / 2

68.1 <0.01*

F 73 4 / 4

2 

“Defense”

M 95 2 / 2

49.5 <0.01*

F 71 3 / 3
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were more likely to report lower fatigue levels post-hike, clustered between “2-Very 

Lively” and “4-A Little Tired” (85.1%); females had a much smaller majority in this same 

range (64.3%), with a sizeable percentage at “5-Moderately Tired” and above (35.7%). 

Both genders’ responses post-Defense appear shifted to the left (towards lower fatigue) 

compared to their post-7km Hike surveys for that same day. This suggests many 

Marines felt more fatigued by the 7km Hike than by the follow-on Defensive tasks (e.g., 

TOW live-fire engagement and mounting/dismounting TOW). 

Table 32 - Pre-Trial, Mid-Trial, and Final Fatigue Score Distributions (by Gender) – 035X

N.4.5.1.2 Fatigue Results by Integration Level

Next, we looked at whether males fatigue responses remained consistent at different 

integration levels. For 035Xs, we compared males’ responses in Control (i.e., all-male) 

and High-Density (i.e., 2 or 3 females) Assault or Anti-Armor Squads. We have mid-trial 

and final fatigue self-reports from six males; statistical results are summarized in the 

table below (Table 33). 
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Table 33 – Summary of Mid-Trial and Final Fatigue Scores (by Integration Level) – 035X

N.4.5.1.2.1 Post-7km Hike Fatigue Scores (by Integration Level)

Following the 7km Hike under load, we found males’ fatigue responses in High-Density 

squads to be significantly different (towards less fatigued)—with a majority of responses 

in the “1-Fully Alert” to “2-Very Lively” range (58.3%) compared to the Control group 

(23.2%) (Table 34). 

Both groups had a sizeable percentage in the mid-range levels (“3-Okay” to “5-

Moderately Tired”), but this was more pronounced in Control responses (73.2%) than in 

High-Density responses (41.7%). The Control groups also had a small number of 

responses (3.7%) in the highest levels (“6-Extremely Tired”, “7-Exhausted”), suggesting 

some males in Control groups were significantly fatigued (at times). 

One potential reason for the shift in males’ responses in integrated groups could be 

their (typically) slower hike times (see Annex E). Combined with the presence of more 

higher-end fatigue levels (“5-Moderately Tired” to “7-Exhausted) in the Control group 

(13.4%), this would suggest some 035X males were not comfortable with the faster 

pace almost always seen among all-male groups. 

From the gender results above—where a substantial number of female responses 

(35.7%) fell in the higher-end levels (“5-Moderately Tired” and above), we should note 

that most of these responses (19 out of 25) occurred in “high-density” units composed 

entirely of females. 

When we re-evaluate the gender results above—but looking only at High-Density 

squads with at least one male (i.e., same trials used in Table 33)—then we find that the 

number of females responding with higher-end scores drops (to 25% of total 

responses), with most responses at “3-Okay” and “4-A Little Tired”. In other words, 

females in High-Density squad with at least one male (i.e., not all-female) have fewer 

reports of very high fatigue levels. This suggests that males in integrated groups may 

have been providing some type of compensation that also reduced females’ fatigue 

levels (to a degree). 

MOS Fatigue Location / Day IL N Median / 

Mode

χ2 

Statistic

χ2 pValue

035X

Post-7km

(Mid-Trial)

29Palms/2

“Defense”

C 82 3 / 3

7.8 <0.01*

HD 12 2 / 2

Final

(Post-Trial)

29Palms/1

“Assault”

C 83 2 / 2

1.1 0.31

HD 13 3 / 3

29Palms/2

“Defense”

C 83 2 / 2

10.1 <0.01*

HD 13 1 / 2
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N.4.5.1.2.2 Final Fatigue Scores (by Integration Level)

Post-trial fatigue results by Integration Level proved to be mixed—males’ responses 

were significantly different between the two groups (i.e., Control and High-Density) for 

the Defense scenario trials, but not for the Offense scenario. Similar to the post-7km 

Hike results—but stronger—males executing Defense trials in High Density groups 

reported more “1-Fully Alert” responses (66.7%) than Control groups (18.1%). 

A comparison of each volunteer’s responses for both the post-7km Hike and post-trial 

surveys reveal that males were overwhelmingly less fatigued by the end of the trial than 

after the hike (77.7%), with the remaining (22.3%) indicating they were as tired (i.e., no 

more tired) by the end of the trial, regardless of which integration level of their group. 

This suggests that the 7km Hike was the primary fatiguing event for the Defense 

scenario for males, and as such, the significantly lower post-trial fatigue levels found for 

High-Density groups could well be an extension of the 7km Hike driver—i.e., perhaps 

slower pace—rather than the result of an additional (or alternate) mechanism. 

Table 34 – Males’ Mid-Trial and Final Fatigue Score Distributions (by Integration Level) – 035X

N.4.5.2 Workload Results

For the 035X volunteers at Twentynine Palms, we have maximum workload self-reports 

from six males and six females13. Because workload survey responses were ordinal in 

nature, we restricted our statistical analysis to the non-parametric Kruskal-Wallis (rank 

sum) test to check for significance between factors, using the criteria of p ≤ 0.10 for 

statistical significance (*). 

 

13 One female only participated in only two trials. 
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N.4.5.2.1 Workload Results by Gender

We first looked at looking at how maximum workload self-reports compared between 

males and females, for both days in their run-cycle. Statistical results are summarized in 

the table below (Table 35) 

Table 35 - Summary of Maximum Workload Scores (by Gender) – 035X

We found a significant difference between female and male 035X volunteers’ maximum 

workload scores. For both days, males heavily favored scores between “3-Active but 

Easy” and “4-Challenging” (91.4% and 87.2% for Offense and Defense, respectively), 

whereas females most often reported in a slightly higher workload range, between “4-

Challenging” and “5-Extremely Busy” (73.6% and 76.7%).

Females were also more likely to report peak scores in the highest range (i.e., “6-

Overloaded” and “7-Unmanageable”), with five out of six Marines contributing at least 

once, and a few multiple times); by comparison, only one male Marine reported in this 

high-end range. However, all instances of female reports14 of “6-Overloaded” and 

above—indeed most female responses overall—were in all-female “High-Density” units. 

As such, it may well be that lack of experience within their unit was a major influence in 

females’ perception of workload demands, and in the gender difference seen here. 

Table 36 - Max Workload Score Distributions (by Gender) – 035X

 

14 Incidentally, the one male that reported max workload scores of “6-Overloaded” or higher did so while in a 

Control (i.e., all-male), unit. 

MOS Workload Location / Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

035X

Max 

Workload for 

Trial

29Palms/1

“Offense” 

M 93 3 / 3 55.7 <0.01*

F 72 4 / 4

29Palms/2

“Defense”

M 94 4 / 3 44.0 <0.01*

F 73 4 / 4
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N.4.5.2.2 Workload Results by Integration Level

In addition to looking at how maximum workload self-reports compared between males 

and females, we also examined whether males’ responses remained consistent at 

different integration levels. For the 035Xs, we compared males’ responses in Control 

(i.e., all-male) and High-Density (i.e., 2 - 3 females) Assault and Anti-Armor Squads. We 

have maximum workload self-reports from six males; statistical results are summarized 

in the table below (Table 37). 

Table 37 - Summary of Maximum Workload Scores (by Integration Level) – 035X

We found mixed results when we looked at males’ max workload responses between 

Control and High-Density groups—statistically significant for Defense trials but not for 

Offense trials. When we examine the distribution of workload scores for the two groups

during Defense trials (Table 38), we see a slight increase in representation at “2-Little to 

Do”, and a lack of any representation at the higher “5-Extremely Busy” and higher, for 

High-Density groups (i.e., towards more manageable) not seen for Control groups. 

Table 38 - Males’ Maximum Workload Score Distributions (by Integration Level) – 035X

As for possible mechanisms, It’s is unlikely that a slower tempo is a factor—as has been 

proposed for some units showing reduced workload perceptions in integrated groups. 

From our quantitative results (see Annex E), High Density groups consistently showed 

slower times for both days. If tempo were the primary factor in shifting males’ maximum

workload reports between Control and High-Density groups, then we’d also expect to 

see a difference in reports for Offense trails—which we didn’t see. 

MOS Workload Location / 

Day IL N Median / 

Mode

χ2 

Statistic

χ2 pValue

035X

Max 

Workload for 

Trial

29Palms/1

“Offense”

C 82 3 / 3

1.5 0.23

HD 11 3 / 3

29Palms/2

“Defense”

C 80 4 / 3

4.4 0.04*

HD 13 3 / 3
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However, males’ maximum workload scores are consistent with differences seen 

between integration levels with fatigue responses (see Table 33 and Table 34). Males’ 

showed significantly lower fatigue levels for Defense trials—but not Offense trials—

when in a High-Density group, compared with Control responses. Since even relatively 

low levels of fatigue can degrade concentration and performance, the lower fatigue 

levels for High-Density groups could shift their perception of their ability to manage their 

workload towards lower scores. 

However, we should also note that these results are based on both a small volunteer 

pool (six males), and on a very small number of High-Density results (11-13 total) 

compared to the number available for Control groups (82-81 total). As such, we should 

be cautious in extrapolating these results to the larger Marine Corps. 

N.4.5.3 Cohesion Results

For the 035X volunteers at Twentynine Palms, we have Unit Cohesion survey results 

(five statements per survey) from six males and six females15. Cohesion responses for 

each statement were set on a nine-point, Likert scale (one indicating “Strongly 

Disagree” and nine indicating “Strongly Agree”). 

Because the cohesion responses consistently violated the normality and independence 

assumptions for parametric data, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). 

N.4.5.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five responses, which scaled between 5 and 45)—compared between 

males and females, following the conclusion of their unit’s run-cycle. Statistical results

are summarized in the table below (Table 39).

 

15 One female only participated in only one run-cycle. 
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Table 39 - Summary of Unit Cohesion Scores (by Gender) - 035X

We found a significant difference between 035X males and females for all five cohesion 

statements (“Q1-Unity”, “Q2-Responsibility”, “Q3-Aspirations”, “Q4-Help” and “Q5-

Comm”), as well as for the overall composite cohesion score. When we look more 

closely at the distribution of responses for each statement, we see that females tend to 

be a lot more optimistic (i.e., higher scores) than males, though both groups have the 

majority of their responses in the top three levels (towards strongly agree).

The shapes of the distributions, however, are quite different between the two groups. 

Females have a heavy majority of responses in the highest level, “9”, for all five 

questions (64.8% to 74.7%), compared to the number of responses at that same level 

for males (33.7% to 40.0%). Males, in addition to a more shallow clustering of 

responses between “7” to “9”, are also more likely to have scores (in each statement) in 

the more neutral “5” to “6” range (12% to 13%) compared to females (1% to 4%). 

We also graphed the means for each statement as a percentage of how strongly the 

volunteers agreed (positive) or disagreed (negative) with each question’s statement 

(Figure 7). 

The average values—by gender—reflect the pronounced differences we saw in unit 

cohesion perceptions of males versus females. It’s unclear why male 035X’s might have 

such a reduced perception of cohesion compared to females. 

One potential reason for the difference may be the influence of small group size and 

relative experience. Females—who were on par with one another with regards to 

experience—were more likely to be paired with another female (especially at the twoman team level that many tasks were conducted). This might have fostered an 

increased sense of cooperation—leading to the many “9” scores reported. 

MOS Cohesion Gender N Mean SD χ2 

Statistic

χ2 pValue

035X

Q1: Group was united in trying to 

reach goals

M 95 7.91 1.22

15.80 <0.01*

F 71 8.48 1.01

Q2: We all take responsibility for 

task success of the group

M 95 7.76 1.42

22.25 <0.01*

F 71 8.54 0.92

Q3: Group members have similar 

aspirations for success

M 95 7.76 1.39

13.32 <0.01*

F 71 8.44 0.97

Q4: If members had problems 

with a task, all wanted to help

M 95 7.76 1.50

16.81 <0.01*

F 71 8.49 0.97

Q5: Members communicated 

freely about responsibilities

M 95 7.80 1.48

18.31 <0.01*

F 71 8.48 1.26

Composite Score (sum of Q1-Q5)

M 95 39.98 6.69

20.28 <0.01*

F 71 42.42 4.52
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If equality of experience can act as a positive influence on cohesion, a difference in 

experience—such as what males might have felt in integrated groups—might have a 

corresponding dampening effect, which might also explain males’ more pessimistic 

results. 

Figure 7 - Perception of Unit Cohesion (by Gender) - 035X

N.4.5.3.2 Cohesion Results by Integration Level

In addition to looking at how unit cohesion scores compared between males and 

females, we also examined whether males’ cohesion responses remained consistent at 

different integration levels. For 035Xs, we compared males’ responses in Control (i.e., 

all-male) and High-Density (i.e., 2 - 3 females) Assault and Anti-Armor Squads. We 

have unit cohesion survey results (five statements per survey) from six males; statistical 

results are summarized in the table below (Table 40).
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Table 40 - Summary of Males' Unit Cohesion Scores (by Integration Level) - 0341

We found a significant difference between the Control and High-Density groups for all 

five cohesion statements, as well as for the overall composite cohesion score. When we 

look more closely at the distributions, we see males’ responses clustering largely 

around the two highest levels, “8” and “9”, across all questions when in the Control 

group (ranging between 72% and 79%), suggesting high perceptions of cohesion 

among all-male groups. 

In the High-Density group, perceptions are not so universal and we see two variations in 

their response pattern. For the “Q1-Unity” and “Q4-Help” questions, we actually see a 

sharper (85%) or comparable (77%) peak—for Q1 and Q4, respectively—within this 

same range, but with slower tapers (i.e., slightly greater representation) spanning “7” 

and “6”. 

For the remaining questions (“Q2-Responsibility”, “Q3-Aspirations”, and “Q5-Comm”), 

we see slightly less representation in the highest two levels (62% to 69%), but with 

similar slow tapers to “6”. This suggests that males in integrated groups—while feeling 

relatively strong with regards to unity and helping members that struggle (though not as 

strong as in Control groups)—are less convinced with regards to taking equal 

responsibility, similar aspirations, or open communication. 

We also graphed the means for each survey statement as a percentage of how strongly 

the volunteers agreed (positive) or disagreed (negative) with each survey statement

(Figure 8). The average values (by integration level) shown are consistent with what we 

saw with regards to males’ higher perceptions of unit cohesion within the Control group, 

along with the decline in their perception of cohesion when in the High-Density group. 

MOS Cohesion IL N Mean SD χ2 

Statistic

χ2 pValue

035X

Q1: Group was united in trying to 

reach goals

C 82 7.99 1.24

6.07 0.01*

HD 13 7.38 0.96

Q2: We all take responsibility for 

task success of the group

C 82 7.88 1.43

8.30 <0.01*

HD 13 7.00 1.15

Q3: Group members have similar 

aspirations for success

C 82 7.89 1.39

8.97 <0.01*

HD 13 6.92 1.12

Q4: If members had problems 

with a task, all wanted to help

C 82 7.88 1.54

10.28 <0.01*

HD 13 7.00 0.91

Q5: Members communicated 

freely about responsibilities

C 82 7.99 1.42

13.86 <0.01*

HD 13 6.62 1.32

Composite Score (sum of Q1-Q5)

Lowest: 5 | Highest 45

C 82 39.62 6.77

8.30 <0.01*

HD 13 34.92 4.55
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Figure 8 - Males' Perception of Unit Cohesion (by Integration Level) - 035X

Unfortunately, the survey did not provide for reasons as to why males were more likely 

to choose lower cohesion scores when in an integrated group—especially for a shift so 

pronounced—but differences in experience levels may have been a factor. We should 

also keep in mind that these are the result of only six Marines, with a very small number 

of reports from integrated groups (i.e., only 13, compared to the 82 reports from the 

Control group). As such, these results may shift with the addition of a more balanced 

data set, or with a different mix of Marines from the larger 035X community. 

Incidentally, these results are quite different from how females rated their perception of 

unit cohesiveness within these same integrated groups (though, as discussed above, 

females’ responses may have been influenced by being paired with another female of 

comparable experience). Also, with the small unit size—and the fact that males may 

often have been outnumbered by females, some of their perceptions may have been 

colored by a different (vice a non-cohesive) group dynamic. 

N.4.6 Provisional Infantry (PI)

N.4.6.1 Fatigue Results

For the Provisional Infantry (PI) volunteers at Twentynine Palms, we have baseline, 

mid-trial, and final fatigue self-reports from 32 males and eight females. Because fatigue 

survey responses were ordinal in nature, we restricted our statistical analysis to the 

non-parametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). Where we had more than two 

groups to compare—and if the Kruskal-Wallis test showed significance for similarity—

then we conducted Wilcoxon pairwise comparisons (using p < 0.033 to adjust for 

multiple comparisons). 
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N.4.6.1.1 Fatigue Results by Gender

We first looked at how fatigue self-reports compared between males and females, 

including their baseline (pre-trial), final (post-trial, for both days in the run-cycle), and 

post-7km Hike (mid-trial, Defense) fatigue levels. Statistical results are summarized in 

the table below (Table 41). 

Table 41 - Summary of Pre-Trial, Mid-Trial, and Final Fatigue Scores (by Gender) - PI

N.4.6.1.1.1 Pre-Trial Fatigue Scores (by Gender)

We found a significant difference between female and male PI volunteers’ pre-trial 

fatigue scores, with males more often reporting lower fatigue levels than females. 

Males’ responses typically clustered around “1-Fully Alert” (31.1%) and “2-Very Lively” 

(41.4%), whereas females most often reported with the slightly higher “3-Okay” (44.7%) 

or “2-Very Lively” (21.2%) before the start of a trial (Table 42). 

We found very few of the higher fatigue scores for either sex (i.e., “5-Moderately Tired”, 

“6-Extremely Tired”, or “7-Exhausted”)—only 0.5 percent of male responses (six 

responses by six different Marines), and 7.1 percent of female responses (driven largely

by three Marines)—and no obvious pattern of increasing scores over time, suggesting 

volunteers largely had sufficient recovery time between trials. 

N.4.6.1.1.2 Final Fatigue Scores (by Gender)

For post-trial responses, we found significant differences for both days of the PI runcycle (i.e., Defense, Offense), with males generally reporting lower fatigue levels than 

females (Table 42). Both genders tended toward relatively consistent, shallow 

distributions—males mostly between “2-Very Lively” and “4-A Little Tired” for both days 

(79.3% and 79.2%, for Defense and Offense, respectively), and females slightly higher, 

between “3-Okay” and “5-Moderately Tired” for both days (85.2%, 81.5%). 

N.4.6.1.1.3 Post-7km Hike Fatigue Scores

For the Defense scenario, PI volunteers also completed a fatigue survey following the 

completion of their 7km Hike under load; we found a significant difference between male 

and female responses for this as well, with the same pattern and general clustering 

MOS Fatigue Day Gender N Median / 

Mode

χ2 

Statistic

χ2 pValue

PI

Baseline 

(Pre-Trial) 1,2

M 1135 2 / 2

123.7 <0.01*

F 226 3 / 3

Post-7km

(Mid-Trial)

1 

“Defense”

M 564 3 / 2

36.0 <0.01*

F 109 4 / 3,5

Final

(Post-Trial)

2 

“Offense”

M 565 3 / 4

33.4 <0.01*

F 110 4 / 4

1 

“Defense”

M 559 3 / 2

38.4 <0.01*

F 108 4 / 5
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found post-trial (i.e., the distribution of males’ responses shifted a bit left of females, 

centered largely between “2-Very Lively” and “4-A Little Tired”; females’ responses 

centered largely between “3-Okay” and “5-Moderately Tired”).

Table 42 - Pre-Trial, Mid-Trial, and Final Fatigue Score Distributions (by Gender) - PI

N.4.6.1.2 Fatigue Results by Integration Level

Next, we looked at whether males fatigue responses remained consistent at different 

integration levels. For Provisional Infantry Rifle Squads, we compared males’ responses 

in Control (i.e., all-male), Low-Density (i.e., 2 females), and High-Density (i.e., 4-5 

females) units. We have mid-trial and final fatigue self-reports from 32 males; statistical 

results are summarized in the table below (Table 43). 
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Table 43 – Summary of Males’ Mid-Trial and Final Fatigue Scores (by Integration Level) - PI

N.4.6.1.2.1 Mid-Trial Fatigue Scores (by Integration Level)

Following the 7km Hike, we found males’ fatigue responses in High-Density Rifle 

Squads to be significantly different (towards less fatigue) from both Low-Density and 

Control squads, but Low-Density squads were not significantly different from Control.

When we look at the three groups respective distributions of post-hike scores (Table 

44), we see that males’ responses in High-Density units were more likely to fall within 

the lowest three fatigue levels (76.1%) than either Control (63.3%) or Low-Density 

(65.7%) units, along with fewer responses in any of the higher levels.

One potential reason for this shift in males’ responses in integrated units (towards lower 

fatigue reporting) following the 7km Hike has been the slower average pace typically 

seen in integrated groups (see Annex F). However, this does not really explain our 

results; both the Low- and High-Density groups were statistically slower than Control 

groups on the 7km Hike (and times between the two integrated groups were not), but 

only High-Density groups showed the lower shift in fatigue levels here. 

When we looked at how the range of responses varied among all male PIs—depending 

on Integration Level—we found that 12 (38%) showed no change in the range of values 

they’d reported over the course of the Twentynine Palms phase and six (19%) showed 

a shift up (towards a higher upper-bound) when in integrated units. In other words, even 

if some Marines might report a lower post-hike fatigue score for a particular, integrated 

trial, 56 percent of them had also reported values as high as (or higher) than highest 

value they’d reported in a Control group. 

MOS Fatigue Location / 

Day IL N Median 

/ Mode

χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

PI

Post-7km

(Mid-Trial)

29Palms/1 

“Defense”

C 248 3 / 2

4.9 0.08*

(LD-C)

-0.46 0.64

LD 178 3 / 3 (HD-C)

-2.2 0.03*

HD 138 3 / 3 (HD-LD)

-1.6 0.10

Final

(Post-Trial)

29Palms/2 

“Offense” 

C 246 3 / 2

LD 175 3 / 3 3.3 0.20

HD 138 3 / 2

29Palms/1 

“Defense”

C 249 3 / 4

4.9 0.09*

(LD-C)

-0.07 0.94

LD 180 3 / 3 (HD-C)

-2.1 0.04

HD 136 3 / 2 (HD-LD)

-1.8 0.07
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This suggests—at least for PI volunteers—that the slower pace typically seen with 

integrated groups does not necessarily confer reduced fatigue levels for males. Indeed, 

only 14 male PI volunteers (44%) showed any indication of consistency of this sort, with 

a shift down (towards a lower lower-bound and/or a lower upper-bound) when in an 

integrated group. As such, it’s likely that a number of factors beyond pace (e.g., intragroup dynamics, motivation, individual conditioning) might be influencing males’ fatigue 

responses, post-hike, leading to these seemingly contradictory results.

N.4.6.1.2.2 Final Fatigue Scores (by Integration Level)

Post-trial fatigue results by Integration Level proved to be mixed. On Offense scenario 

trials, we only saw a significant difference in post-trial fatigue levels in males between 

High-Density and Low-Density squads—with a slight shift towards lower fatigue levels 

(“1-Fully Alert”, “2-Very Lively”)—but not between Control and either integration group

On Defense trials, post-trial responses for males were similar to what we found for post7km Hike results: responses in High-Density Rifle Squads were significantly different 

(towards less fatigue) from both Control and Low-Density groups, with no difference 

found between Low-Density and Control groups. 

Since the majority of individuals reported being as tired or less tired (69.5%) at the end 

of the Defense trial as they had after the 7km hike, it’s likely whatever factors influenced

post-hike fatigue levels—resulting in any differences (or lack of differences) between 

groups—were also at work for post-trial reporting. 

Table 44 – Males’ Mid-Trial and Final Fatigue Score Distributions (by Integration Level) - PI 
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N.4.6.2 Workload Results

For the Provisional Infantry (PI) volunteers at Twentynine Palms, we have maximum

workload self-reports from 32 males and eight females. Because workload survey 

responses were ordinal in nature, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). Where we had more than two 

groups to compare—and if the Kruskal-Wallis test showed significance for similarity—

then we conducted Wilcoxon pairwise comparisons (using p<0.033 to adjust for multiple 

comparisons).

N.4.6.2.1 Workload Results by Gender

We first looked at how maximum workload self-reports compared between males and 

females, for both days in their run-cycle. Statistical results are summarized in the table 

below (Table 45) 

Table 45 - Summary of Maximum Workload Scores (by Gender) – PI

We found a significant difference between female and male Provisional Infantry (PI)

volunteers’ maximum workload scores for both days (Defense and Offense). Males

most often reported scores between “3-Active but Easy” and “4-Challenging” (70.7% 

and 68.0% for Defense and Offense, respectively), whereas females most often 

reported scores of “4-Challenging” and “5-Extremely Busy” (84.4% and 78.4%) (Table 

46). 

Table 46 - Maximum Workload Score Distributions (by Gender) - PI

MOS Workload Location / Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

PI

Max 

Workload for 

Trial

29Palms/2

“Offense” 

M 566 4 / 4 62.4 <0.01*

F 109 5 / 5

29Palms/1

“Defense”

M 568 4 / 4 32.6 <0.01*

F 111 4 / 4
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For both groups, we see a small, but visible, number of maximum workload scores at 

the highest range (i.e., “6-Overloaded” and “7-Unmanageable”) indicating that a sub-set 

of both genders felt unable to keep up with their workload demands (five of eight 

females, and 14 out of 32 males)—at least on occasion. Indeed, eight Marines reported 

in this range at least four times (and several in the double-digits). This suggests a 

sizeable number of all PI Marines felt (at times) overwhelmed operating in a Rifle 

Squad. 

The difference we see between the two groups is unlikely to be due to differences in 

experience, as none of the volunteers in the PI pool were 0311s. This may, however, be 

linked to the higher levels of fatigue reported by female PIs (nearly one-quarter to onethird of all female post-trial fatigue responses were “5-Moderately Tired” or higher—see 

Table 42), since even relatively low levels of fatigue can degrade concentration and 

performance of non-rote skills.

N.4.6.2.2 Workload Results by Integration Level

In addition to looking at how maximum workload self-reports compared between males 

and females, we also examined whether males’ responses remained consistent at 

different integration levels. For PI, we compared males’ responses in Control (i.e., allmale), Low-Density (i.e., 2 females), and High-Density (i.e., 4-5 females) Rifle Squads. 

We have maximum workload self-reports from 32 males; statistical results are 

summarized in the table below (Table 47). 

Table 47 - Summary of Males' Maximum Workload Scores (by Integration Level) - PI

We found mixed results when we looked at males’ max workload responses by 

Integration Level. For Defense trials, we saw a significant difference between HighDensity and Control or Low-Density groups. We did not see any difference for Offense 

trials. 

From a visual inspection of the scores reported by the different groups (Table 48), we 

see that males in High-Density groups (on Defense days) have slightly fewer reports 

MOS Workload Location / 

Day IL N 

(scores)

Median

/ Mode

χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

PI

Max 

Workload 

for Trial

29Palms/2

“Offense” 

C 248 4 / 4

LD 179 4 / 4 1.3 0.52

HD 139 4 / 4

29Palms/1

“Defense”

C 251 4 / 4

7.7 0.02*

(LD-C)

0.33 0.74

LD 179 4 / 4 (HD-C)

-2.4 0.02*

HD 138 4 / 4 (HD-LD)

-2.6 0.01*
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(15.2%) at the higher end (i.e., “5-Extremely Busy” and higher) than Control and LowDensity groups (26.3%), along with a corresponding (slight) increase in scores at the 

lower end (39.1% for HD groups, but only 32.3% and 29.6% for Control and LowDensity groups, respectively). In other words, males in High-Density groups appear to 

be slightly more optimistic in their ability to manage their workload.

Table 48 - Males’ Max Workload Score Distributions (by Integration Level) - PI

As for possible mechanisms, these results are unlikely to be driven by relative 

experience given that all volunteers—male and female—are not operating in their 

primary MOS. However, these mixed results are consistent with differences seen by 

Integration Level with fatigue above (see Table 43 and Table 44). 

Males’ showed significantly lower fatigue levels for Defense trials—but not Offense 

trials—when in a High-Density group, compared with Control and Low-Density 

responses. Since even relatively low levels of fatigue can degrade concentration and 

performance, the lower fatigue levels for High-Density groups on Defense trials could 

shift their perception of their ability to manage their workload towards lower scores. 

N.4.6.3 Cohesion Results

For the Provisional Infantry (PI) volunteers at Twentynine Palms, we have Unit 

Cohesion survey results (five statements per survey) from 32 males and eight females. 

Cohesion responses for each statement were set on a nine-point, Likert scale (one 

indicating “Strongly Disagree” and nine indicating “Strongly Agree”). 

Because the cohesion responses consistently violated the normality and independence 

assumptions for parametric data, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). Where we had more than two 

groups to compare—and if the Kruskal-Wallis test showed significance for similarity—
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then we conducted Wilcoxon pairwise comparisons (using p<0.033 to adjust for multiple 

comparisons).

N.4.6.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five responses, which scaled between 5 and 45)—compared between 

males and females, following the conclusion of their unit’s run-cycle. Statistical results

are summarized in the table below (Table 49).

Table 49 - Summary of Unit Cohesion Scores (by Gender) - PI

We did not find a significant difference between gender for any question (Q1-Q5), nor 

for the composite score. Only “Q4-Help” is on the border for significance, likely due to a 

mini-peak among female responses at “4” (towards Significantly Disagree)—driven 

largely by a single female—but which is not seen for any other questions, nor among 

males. 

We also graphed the means for each survey statement as a percentage of how strongly 

the volunteers agreed (positive) or disagreed (negative) with each survey statement 

(Figure 9). The average values—by gender—reflect the common perception (by 

statement and by composite score) of males and females regarding their units’ relatively 

high cohesion. The one borderline question (“Q4-Help”)—driven to a lower value due to 

a series of low responses by a single female Marine (i.e., ten “4” scores)—appears to 

be an outlier. 

MOS Location Cohesion Gender N 

(scores) Mean SD χ2 

Statistic

χ2 pValue

PI 29Palms

Q1: Group was united in trying 

to reach goals

M 556 8.14 1.16

0.27 0.60

F 111 8.12 1.26

Q2: We all take responsibility for 

task success of the group

M 556 8.15 1.18

0.01 0.77

F 111 8.04 1.31

Q3: Group members have similar 

aspirations for success

M 556 8.09 1.37

0.00 0.98

F 111 8.08 1.29

Q4: If members had problems 

with a task, all wanted to help

M 556 8.17 1.22

2.28 0.13

F 111 7.70 1.74

Q5: Members communicated 

freely about responsibilities

M 556 8.21 1.22

0.95 0.33

F 111 8.07 1.26

Composite Score (sum of Q1-Q5)

M 556 40.77 1.22

1.18 0.28

F 111 40.01 1.26
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Figure 9 - Perception of Unit Cohesion (by Gender) – PI

N.4.6.3.2 Cohesion Results by Integration Level

In addition to looking at how unit cohesion scores compared between males and 

females, we also examined whether males’ cohesion responses remained consistent at 

different integration levels. For Provisional Infantry (PI), we compared males’ responses 

in Control (i.e., all-male), Low-Density (i.e., 2 females), and High-Density (i.e., 4-5 

females) Rifle Squads. We have unit cohesion survey results (five statements per 

survey) from 32 males; statistical results are summarized in the table below (Table 50).
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Table 50 - Summary of Males' Unit Cohesion Scores (by Integration Level) - PI

We found a statistical difference between the Control group and both integration levels 

(i.e., High-Density, and Low-Density groups) for all five cohesion statements, as well as 

for the overall composite cohesion score. However, we did not see a difference between 

the two integration levels. 

When we looked at the distributions of each question, we see very similar patterns—the 

majority of responses are heavily skewed to the far right (i.e., “9”, at Significantly 

Agree), and taper off relatively quickly to the left. Where the differences occur is in the 

sharpness of the main peak at “9” and the span of the taper. For Control groups, we see 

MOS Cohesion IL N Mean SD χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test 

p-Value

PI

Q1: Group was united in 

trying to reach goals

C 248 8.33 0.88

8.67 0.01*

(LD-C)

-1.96 0.05*

LD 179 8.09 1.18 (HD-C)

-2.80 <0.01*

HD 139 7.88 1.47 (HD-LD)

-0.94 0.35

Q2: We all take 

responsibility for task 

success of the group

C 248 8.33 0.90

7.04 0.03*

(LD-C)

-1.50 0.13

LD 179 8.10 1.25 (HD-C)

-2.61 0.01*

HD 139 7.89 1.46 (HD-LD)

-1.13 0.26

Q3: Group members 

have similar aspirations 

for success

C 248 8.35 0.98

12.20 <0.01*

(LD-C)

-2.68 <0.01*

LD 179 7.92 1.60 (HD-C)

-3.15 <0.01*

HD 139 7.85 1.57 (HD-LD)

-0.62 0.54

Q4: If members had 

problems with a task, all 

wanted to help

C 248 8.39 0.86

11.66 <0.01*

(LD-C)

-2.19 0.03*

LD 179 8.09 1.28 (HD-C)

-3.29 <0.01*

HD 139 7.88 1.56 (HD-LD)

-1.19 0.23

Q5: Members 

communicated freely 

about responsibilities

C 248 8.40 0.91

9.20 0.01*

(LD-C)

-2.52 0.01*

LD 179 8.11 1.34 (HD-C)

-2.58 0.01*

HD 139 8.01 1.47 (HD-LD)

-0.28 0.78

Composite Score 

(sum of Q1-Q5)

Lowest: 5 | Highest 45

C 248 41.81 3.97

11.17 <0.01*

(LD-C)

-2.12 0.03*

LD 179 40.32 5.91 (HD-C)

-3.24 <0.01*

HD 139 39.50 7.08 (HD-LD)

-1.15 0.25
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the sharpest peak (53% to 63% across all five statements) that largely tapers off by “7”, 

with virtually no responses beyond that. 

For the two integrated groups, the peaks are a bit more shallow (42% to 50%), and the 

taper spans a wider (and more negative) set of responses; for the Low-Density group 

the taper ends around “6”, while it extends out (though at rather low values) to “5” for 

the High-Density group. 

We also graphed the means for each statement as a percentage of how strongly males 

agreed (positive) or disagreed (negative) with each question’s statement while in each 

group (Figure 10). The average values are consistent with what we saw with regards to 

males’ relatively high perceptions of unit cohesion within the Control group, along with 

the easy decline in their perception of cohesion when in the Low- and High-Density 

groups. 

Figure 10 - Males' Perception of Unit Cohesion (by Integration Level) - PI

Unfortunately, the survey did not provide for reasons as to why males were more likely 

to choose lower cohesion scores when in an integrated group. With the larger 

population pool (compared to some of the other 03XX MOS analyzed), we can likely 

have more faith that these trends might well persist. 

Differences in experience also appears to be a less likely driver, as all volunteers are 

operating outside of their PMOS, although we can’t rule it out completely as females 

have also operated under additional assignment limitations that might have minimized 

their exposure to the field environment. Incidentally, the average values for the 

integrated groups appear to align well with how females rated their perceptions of unit 

cohesiveness. 
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N.4.7 Provisional Infantry Machine Gunner (PIMG)

N.4.7.1 Fatigue Results

For the Provisional Infantry Machine Gunner (PIMG) volunteers at Twentynine Palms, 

we have baseline, mid-trial, and final fatigue self-reports from four males16 and four 

females. Because fatigue survey responses were ordinal in nature, we restricted our 

statistical analysis to the non-parametric Kruskal-Wallis (rank sum) test to check for 

significance between factors, using the criteria of p ≤ 0.10 for statistical significance (*). 

N.4.7.1.1 Fatigue Results by Gender

We first looked at looking at how fatigue self-reports compared between males and 

females, including their baseline (pre-trial), their final (post-trial, for both days in the runcycle), and post-7km Hike (mid-trial, Day 1) fatigue levels. Statistical results are 

summarized in the table below (Table 51). 

Table 51 - Summary of Pre-Trial, Mid-Trial, and Final Fatigue Scores (by Gender) - PIMG

N.4.7.1.1.1 Pre-Trial Fatigue Scores (by Gender)

We did not find a significant difference between female and male PIMG volunteers’ pretrial fatigue scores. Both males and females were most likely to report fatigue levels in 

the “2-Very Lively” to “3-Okay” range (84.5% and 72.6%, respectively) prior to the start 

of a trial (Table 52). 

We found very few of the higher fatigue scores for either sex (i.e., “5-Moderately Tired”, 

“6-Extremely Tired”, or “7-Exhausted”)—only 1.7 percent of male responses (two 

responses by different Marines), and 5.6 percent of female responses (driven almost 

entirely by a single Marine)—and no obvious pattern of increasing scores over time, 

suggesting volunteers largely had sufficient recovery time between trials. 

 

16 One male participated in only one run-cycle, and did not respond to the mid-trial or final surveys for Day 1.

MOS Fatigue Location / 

Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

PIMG 

Baseline 

(Pre-Trial) 29Palms/1,2

M 116 3 / 3

0.72 0.40

F 124 3 / 3

Post-7km

(Mid-Trial)

29Palms/1 

“Defense”

M 55 3 / 3

13.4 <0.01*

F 60 4 / 4

Final

(Post-Trial)

29Palms/2 

“Offense”

M 56 3 / 3 

12.1 <0.01*

F 59 4 / 4

29Palms/1 

“Defense”

M 55 3 / 3

9.3 <0.01*

F 59 4 / 4
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N.4.7.1.1.2 Final Fatigue Scores (by Gender)

In looking at the volunteers’ post-trial responses, we found significant differences in their 

responses—by gender—for both days of the PIMG run-cycle (i.e., Defense and 

Offense). For both days, males’ responses clustered largely between “3-Okay” and “4-A 

Little Tired” (76.4% and 76.8%, for Defense and Offense days, respectively), whereas

females’ post-trial responses tended towards a more shallow and wider distribution 

between “2-Very Lively” and “5-Moderately Tired” (86.4% for both days). 

N.4.7.1.1.3 Post-7km Hike Fatigue Scores (by Gender)

For the Defense scenario, PIMG volunteers also completed a fatigue survey following 

the completion of their 7km Hike under load. As with post-trial responses, we found a 

significant difference in male and female responses, with males most likely to report “3-

Okay” (43.6%) and females most likely to report “4-A Little Tired” (41.7%). 

However, given the “non-majority” of both of these peaks and the rather small number 

of contributing Marines, we also looked as the range of values each Marine reported—

post-hike—over the course of the study. For the males, two of the three volunteers 

reported values ranging between “3-Okay” and “5-Moderately Tired”; the third had a 

wider range between “1-Fully Alert” and “5-Moderately Tired”. 

For the females, two reported between “2-Very Lively” and “6-Extremely Tired” while the 

other two reported between “3-Okay” and “Extremely Tired”. Given the wide ranges 

within Marines for the same task and the small number of contributors, we should be

extremely cautious in drawing conclusions about propensity toward fatigue for this MOS 

from these results.

Table 52 - Pre-Trial, Mid-Trial, and Final Fatigue Score Distributions (by Gender) - PIMG
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N.4.7.1.2 Fatigue Results by Integration Level

For previous MOS, we looked at whether males’ fatigue responses remained consistent 

at different integration levels. However, for PIMG, there was only a single valid run-cycle 

(with one unit) that had an integrated unit (i.e., one male and two females). All other runcycles were either all-male or all-female.

N.4.7.2 Workload Results

For the PI Machine Gunner (PIMG) volunteers at Twentynine Palms, we have maximum

workload self-reports from four males17 and four females. Because workload survey 

responses were ordinal in nature, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). 

N.4.7.2.1 Workload Results by Gender

We first looked at how maximum workload self-reports compared between males and 

females, for both days in their run-cycle. Statistical results are summarized in the table 

below (Table 53). 

Table 53 - Summary of Maximum Workload Scores (by Gender) – PIMG

We found a significant difference between female and male Provisional Infantry 

Machine Gunner (PIMG) volunteers’ maximum workload scores for both days (Defense 

and Offense). Males most often reported scores between “3-Active but Easy” and “4-

Challenging” (80.7% and 73.2% for Defense and Offense, respectively), whereas 

females most often reported scores in the slightly higher range of “4-Challenging” and 

“5-Extremely Busy” (87.1% and 80.6%) (Table 54).

We also saw an increased likelihood of maximum workload scores of “6-Overloaded” or 

“7-Unmanageable” among females; all four female volunteers reported in this range at 

least once, but total numbers in this range were driven by one Marine. However, even 

among the males, two of the four male volunteers had also reported in this range at 

least once. 

 

17 One male only participated in two trials.

MOS Workload Location / Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

PIMG 

Max 

Workload for 

Trial

29Palms/2

“Offense” 

M 57 4 / 4 23.1 <0.01*

F 62 4 / 4

29Palms/1

“Defense”

M 56 4 / 4 16.7 <0.01*

F 62 4.5 / 4
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While relative experience is unlikely to be the driver in the difference we found between 

genders in maximum workload responses, there may be a tie to fatigue—which also 

tended to be higher, post-trial, among female PIMG volunteers. 

However, given the small size of this volunteer pool (four males—of which one only 

participated for one run-cycle—and four females) and the signs that most Marines may 

have struggled—on occasion—to accomplish the necessary workload of a Machine 

Gunner, we should be cautious in extrapolating the PIMG study results to the larger 

Marine Corps community. At the very least, the extent to which non-0331 Marines might 

be able to function at the same workload demands as an 0331 Machine Gunner

warrants further study. 

Table 54 - Maximum Workload Score Distributions (by Gender) - PIMG

N.4.7.2.2 Workload Results by Integration Level

For previous MOS, we looked at whether males’ fatigue responses remained consistent 

at different integration levels. However, for PIMG, there was only a single valid run-cycle 

(with one unit) that had an integrated unit (i.e., one male and two females). All other runcycles were either all-male or all-female.

N.4.7.3 Cohesion Results

For the Provisional Infantry Machine Gunner (PIMG) volunteers at Twentynine Palms, 

we have Unit Cohesion survey results (five statements per survey) from four males18

and four females. Cohesion responses for each statement were set on a nine-point, 

Likert scale (one indicating “Strongly Disagree” and nine indicating “Strongly Agree”). 

Because the cohesion responses consistently violated the normality and independence 

assumptions assumption for parametric data, we restricted our statistical analysis to the 

 

18 One male only participated in one run-cycle.
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non-parametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). 

N.4.7.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five statements, which scaled between 5 and 45)—compared between 

males and females, following the conclusion of their unit’s run-cycle. Statistical results

are summarized in the table below (Table 55).

Table 55 - Summary of Unit Cohesion Scores (by Gender) - PIMG

We found a significant difference between PIMG males and females for all five cohesion 

statements (“Q1-Unity”, “Q2-Responsibility”, “Q3-Aspirations”, “Q4-Help” and “Q5-

Comm”), as well as for the overall composite cohesion score. When we look more 

closely at the distribution of responses for each statement, we see that females tended

to be a bit more optimistic (i.e., higher scores) than males, though both groups have the 

majority of their responses in the top three levels (towards strongly agree).

For females, we see much more representation at the highest level, “9” (41.0% to 

45.9%), than we do among male responses (15.8% to 21.1%). However, it seems that 

this difference is relatively minor; when we look at the total contributions within the top 

three levels (i.e., “7” to “9”)—both males and females have more than 86% of all 

responses in this range with almost no responses below “5” for either group. This 

suggests that both males and females perceived their groups to possess fairly high 

cohesiveness. 

We also graphed the means for each survey statement as a percentage of how strongly 

the volunteers agreed (positive) or disagreed (negative) with each survey statement 

MOS Cohesion Gender N Mean SD χ2 

Statistic

χ2 pValue

PIMG

Q1: Group was united in trying to 

reach goals

M 57 7.77 0.91

7.21 <0.01*

F 61 8.18 0.90

Q2: We all take responsibility for 

task success of the group

M 57 7.81 0.77

6.95 <0.01*

F 61 8.16 0.88

Q3: Group members have similar 

aspirations for success

M 57 7.65 1.09

9.58 <0.01*

F 61 8.20 0.93

Q4: If members had problems 

with a task, all wanted to help

M 57 7.91 0.79

3.51 0.06*

F 61 8.13 0.99

Q5: Members communicated 

freely about responsibilities

M 57 7.81 0.90

5.91 0.02*

F 61 8.15 1.03

Composite Score (sum of Q1-Q5)

M 57 38.95 3.78

7.75 <0.01*

F 61 4.82 4.53
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(Figure 11). The average values—by gender—reflect the differences we saw in the 

distribution of unit cohesion scores—females tended towards more optimistic scores 

than males, but both are relatively solid towards positive cohesion. 

It is unclear why males might have lower perceptions of unit cohesion than females. 

This MOS did not have integrated groups per se—there being only a single “integrated” 

unit (i.e., one male and two females); all other units were either all-male (i.e., Control) or 

all-female. The slightly higher scores in the all-female groups may be a function of a 

common level of experience or a greater degree of cooperation. 

Figure 11 - Perception of Unit Cohesion (by Gender) - PIMG

Of course, we can only guess at the relative level of experience among the all-male 

groups. That some struggled19 (on occasion) suggests that there may have been some 

differences. However, some of the females struggled, too, so experience can’t be the 

entire answer—or at least it mattered less among females. But, given the small size of 

this volunteer pool (four males—of which one only participated for one run-cycle—and 

four females) we should be cautious in extrapolating the PIMG study results to the 

larger Marine Corps community. 

N.4.7.3.2 Cohesion Results by Integration Level

For previous MOS, we looked at whether males’ cohesion responses remained 

consistent at different integration levels. However, for PIMG, there was only a single 

valid run-cycle (with one unit) that had an integrated unit (i.e., one male and two 

females). All other run-cycles were either all-male or all-female.

 

19 Based upon two of the four males having reported—on occasion—max workload scores of “6-Overloaded”.
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N.4.8 Combat Engineer (MOS 1371)

N.4.8.1 Fatigue Results

For the 1371 volunteers at Twentynine Palms, we have baseline, mid-trial, and final 

fatigue self-reports from 18 males and eight females20. Because fatigue survey 

responses were ordinal in nature, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). Where we had more than two 

groups to compare—and if the Kruskal-Wallis test showed significance for similarity—

then we conducted Wilcoxon pairwise comparisons (using p < 0.033 to adjust for 

multiple comparisons). 

N.4.8.1.1 Fatigue Results by Gender

We first looked at how fatigue self-reports compared between males and females, 

including their baseline (pre-trial), final (post-trial, for both days in the run-cycle), and 

post-7km Hike (mid-trial, Defense) fatigue levels. Statistical results are summarized in 

the table below (Table 56). 

Table 56 - Summary of Pre-Trial, Mid-Trial, and Final Fatigue Scores (by Gender) - 1371

N.4.8.1.1.1 Pre-Trial Fatigue Scores (by Gender)

We did not find a significant difference between female and male 1371 volunteers’ pretrial fatigue scores. Both groups showed the highest clustering of pre-trial fatigue 

responses at “2-Very Lively” and “3-Okay” (Table 57). 

We found very few of the higher fatigue scores for either gender (i.e., “5-Moderately 

Tired”, “6-Extremely Tired”, or “7-Exhausted”)—only 7.3 percent of male responses 

(driven overwhelmingly by two Marines), and 2.0 percent of female responses (three 

 

20 One female only participated in a single run-cycle.

MOS Fatigue Location / 

Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

1371

Baseline 

(Pre-Trial) 29Palms/1,2

M 576 2 / 3

0.53 0.47

F 150 2 / 2

Post-7km

(Mid-Trial)

29Palms/2 

“Defense”

M 285 3 / 3

7.0 <0.01*

F 73 4 / 4

Final

(Post-Trial)

29Palms/1 

“Offense”

M 286 3 / 2

0.05 0.82

F 73 3 / 2

29Palms/2 

“Defense”

M 286 3 / 2

0.03 0.86

F 75 3 / 3
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reports by two Marines)—and no obvious pattern of increasing scores over time, 

suggesting volunteers largely had sufficient recovery time between trials. 

N.4.8.1.1.2 Final Fatigue Scores (by Gender)

In looking at the volunteers’ post-trial responses, we did not find a significant difference 

for either day. Similar to pre-trial distributions, both males and females were most likely 

to report fatigue levels of either “2-Very Lively” or “3-Okay”, although we did see a 

respectable representation for both groups at “4-A Little Tired (21% for females, and 12-

16% for males) not see in pre-trial scores. 

For the small number of post-trial responses we saw in the higher ranges (“5-

Moderately Tired” or higher), most contributions by individual were sparse (i.e., one to 

four responses over the course of the study). However, the two male Marines who 

contributed substantially more fatigue scores in this range (seven and 21 reports) had 

also been the major contributors to pre-trial fatigue levels in this range. 

N.4.8.1.1.3 Post-7km Hike Fatigue Scores (by Gender)

The one area where we did see significant difference between the genders for 1371s 

was the post-7km Hike in the Defense scenario. Following the hike under load, females 

showed a slight shift in fatigue levels (towards more fatigue)—more often clustering 

around “3-Okay” and “4-A Little Tired” (60.3%)—than males, whose responses more 

often fell around “2-Very Lively” and “3-Okay” (57.9%). In both groups, however, we did 

see relatively shallow distributions covering the “2-Very Lively” to “5-Moderately Tired” 

span (89.8% and 91.8%, for males and females, respectively).

When we looked at the responses within individual Marines, we saw that most Marines’ 

ranges (84%)—for both males and females—fell across all or most of this span (i.e., 

three or more levels), suggesting a great degree of intra-subject variability within the 

1371 volunteer pool. 

 
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Table 57 - Pre-Trial, Mid-Trial, and Final Fatigue Score Distributions (by Gender) - 1371

N.4.8.1.2 Fatigue Results by Integration Level

Next, we looked at whether males fatigue responses remained consistent at different 

integration levels. For 1371s, we compared males’ responses in Control (i.e., all-male), 

Low-Density (i.e., 2 females), and High-Density (i.e., 4 females) Engineer Squads. We 

have mid-trial and final fatigue self-reports from 18 males for the Control and LowDensity units, and from 15 males in the High-Density units; statistical results are 

summarized in the table below (Table 58). 

Table 58 – Summary of Males’ Mid-Trial and Final Fatigue Scores (by Integration Level) - 1371

MOS Fatigue Location / 

Day IL N Median 

/ Mode

χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test 

p-Value

1371

Post-7km

(Mid-Trial)

29Palms/2

“Defense”

C 154 3 / 3

8.6 0.01*

(LD-C)

-0.21 0.84

LD 83 3 / 3 (HD-C)

-2.9 <0.01*

HD 48 3 / 3 (HD-LD)

-2.4 0.02*

Final

(Post-Trial)

29Palms/1

“Offense” 

C 110 2 / 2

LD 84 2 / 2 1.3 0.52

HD 44 2 / 1

29Palms/2

“Defense”

C 114 2 / 2

LD 84 2 / 2 1.0 0.59

HD 46 2 / 2
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N.4.8.1.2.1 Post-7km Hike Fatigue Scores (by Integration Level)

Following the 7km Hike under load (Defense scenario), we found the distribution of 

males’ fatigue responses in High-Density squads to be significantly different (towards 

less fatigue) from both Control and Low-Density squads. We did not see a statistical 

difference between Control and Low-Density groups. 

Looking more closely at the distributions of the various groups (Table 59), we saw a 

shift to the left (i.e., less fatigue) for males in the High-Density groups—clustering more 

strongly around “2-Very Lively” and “3-Okay” (72.9%) than those same levels for Control 

(56.5%) and Low-Density (51.8%) squads, which tended towards broader (and more 

shallow) distributions spanning “2-Very Lively” to “4-A Little Tired”. Control and LowDensity Groups also had higher (though still relatively small) representations in the 

higher range (“5-Moderately Tired” to “7-Exhausted”)—with 15.6% and 14.5%, 

respectively—compared to the High-Density group (4.2%). 

One potential reason for this relatively minor shift towards less fatigue in High-Density 

groups could be their (typically) slower hike times (see Annex K). However, given that 

we also saw a relatively wide degree of intra-subject variability across all Marines’ 

fatigue responses for the 7km Hike, we also looked to see if this variability changed by 

integration level. 

For the 15 males that contributed fatigue scores for a High-Density squad, most (73%) 

showed both a narrowing and depression in the range of fatigue values they reported 

compared with their ranges while in a Control or even Low-Density squad (with some 

indications of this pattern emerging in Low-Density groups as well, for some Marines). 

This suggests that a number of males were persistently—though maybe only slightly—

less fatigued while in a High-Density squad, potentially because the slower pace was 

less physically demanding.

Another potential influence might be group dynamics. Males in all-male groups are more 

likely to report scores at the highest levels (i.e., “6-Extremely Tired”, “7-Exhausted”), 

female responses in this range (see Table 57) are from Low-Density groups only. Well 

not definitive, we might also be seeing some group dynamic in terms of how hard allmale versus integrated units will press. All-male groups may be more willing to push a 

faster pace (even if it heavily fatigues some members) than an integrated group might. 

N.4.8.1.2.2 Final Fatigue Scores (by Integration Level)

For 1371s, we did not see any significant difference in post-trial fatigue results based on 

Integration Level for either of the two trial scenarios (i.e., Day 1/Offense and Day 

2/Defense). Across all integration levels and locations, we see males’ responses largely 

clustering around “2-Very Lively” and “3-Okay” (ranging between 59.0% and 77.1%), 

with smaller percentages tapering off to either side (Table 59). 
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Table 59 – Males’ Mid-Trial and Final Fatigue Score Distributions (by Integration Level) - 1371

 

N.4.8.2 Workload Results

For the 1371 volunteers at Twentynine Palms, we have max workload self-reports from 

18 males and eight females21. Because workload survey responses were ordinal in 

nature, we restricted our statistical analysis to the non-parametric Kruskal-Wallis (rank 

sum) test to check for significance between factors, using the criteria of p ≤ 0.10 for 

statistical significance (*). Where we had more than two groups to compare—and if the 

Kruskal-Wallis test showed significance for similarity—then we conducted Wilcoxon 

pairwise comparisons (using p<0.033 to adjust for multiple comparisons).

N.4.8.2.1 Workload Results by Gender

We first looked at how maximum workload self-reports compared between males and 

females, for both days in their run-cycle. Statistical results are summarized in the table 

below (Table 60). 

 

21 One female only participated in a single run-cycle.
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Table 60 - Summary of Maximum Workload Scores (by Gender) – 1371

We found a significant difference between female and male 1371 volunteers’ maximum 

workload scores for both days (Offense and Defense), with males showing slightly 

higher representation at the lower workload levels—i.e., “3-Active but Easy” and below 

(Table 61). 

Table 61 - Maximum Workload Score Distributions (by Gender) - 1371

However, we also noticed the presence of some “1-No Demands” scores, for both 

genders, as the maximum workload a Marine experienced during a trial. This seems 

highly unlikely, given the design of the 1371 Scheme of Maneuver. When we looked 

more closely at the contributors of these scores, we see that they represent one female 

response and three male contributors—one reporting in this range seven times (for all of 

the last-half of his trials). This suggests the possibility of that some type of “survey 

fatigue” or reporting bias may have been introduced, though exclusion of these trials 

does not change the overall statistical result by gender—i.e., a statistical difference

exists between males and females for max workload reports. 

As for this difference between the two genders, it’s unlikely that this can be explained 

through differences in fatigue levels (which we didn’t find post-trial). Plus, since all 1371 

volunteers were operating in their primary MOS, familiarity with the tasks performed 

shouldn’t differ. 

However, it is possible that the historical assignment restrictions on female 1371s could 

have introduced an experience bias in our population, especially in field-related tasks. 

MOS Workload Location / Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

1371

Max 

Workload for 

Trial

29Palms/1

“Offense” 

M 275 3 / 3 5.9 0.02*

F 72 4 / 4

29Palms/2

“Defense”

M 287 4 / 4 10.5 <0.01*

F 75 4 / 4
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Unfortunately, without knowing what tasks elicited each peak workload report, we 

cannot estimate how likely the latter theory might be. 

N.4.8.2.2 Workload Results by Integration Level

In addition to looking at how maximum workload self-reports compared between males 

and females, we also examined whether males’ responses remained consistent at 

different integration levels. For 1371s, we compared males’ responses in Control (i.e., 

all-male), Low-Density (i.e., 2 females), and High-Density (i.e., 4 females) Engineer

Squads. We have max workload self-reports from 18 males (18 in the Control and LowDensity groups, and 15 in the High-Density group); statistical results are summarized in 

the table below (Table 62). 

Table 62 - Summary of Males’ Max Workload Scores (by Integration Level) – 1371

We found mixed results when we looked at males’ maximum workload responses by 

Integration Level. For Defense trials, we saw a significant difference between HighDensity and Control groups, but not between any other pairing—although it’s borderline 

between High- and Low-Density groups. We also did not see any differences for 

Offense trials. 

When we look at the scores reported by the different groups (Table 63), we see that 

males in High-Density groups (on Defense days) have fewer reports (10.4%) at the 

higher end (i.e., “5-Extremely Busy” and higher) than Control groups (22.4%), along with 

a corresponding increase in scores (58.3%) at the lower end (i.e., “3-Active but Easy” 

and lower) compared to Control (41.0%). Low-Density scores fall somewhere in 

between the other two groups—hence the lack of significance. 

MOS Workload Location / 

Day IL N 

(scores)

Median

/ Mode

χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

1371

Max 

Workload 

for Trial

29Palms/1

“Offense” 

C 149 3 / 3

LD 78 3 / 3 2.9 0.23

HD 48 3 / 3

29Palms/2

“Defense”

C 156 4 / 4

5.2 0.08*

(LD-C)

-0.31 0.59

LD 83 4 / 4 (HD-C)

-1.8 0.02*

HD 48 3 / 3 (HD-LD)

-1.6 0.10
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Table 63 - Males’ Maximum Workload Score Distributions (by Integration Level) - 1371

As for possible mechanisms, these results have some factors in common with what we 

saw with fatigue surveys above, following the 7km Hike on Day Defense—except posthike fatigues scores differed between both integration groups and Control, and not just 

between High-Density and Control groups. Plus, the differences in fatigue seen posthike did not appear to extend to post-trial fatigue scores. 

Without knowing what tasks in the Defense scenario might have been driving males’ 

maximum workload scores, it’s not possible to know if the decrease in fatigue from the 

7km Hike could really have influenced males’ to report lower maximum workload scores 

when in High Density groups. Fatigue is a plausible driver, since even relatively low 

levels of fatigue can degrade concentration and performance, but results are too 

mixed—and we have too little fidelity on why males chose the scores they did. 

Alternatively, it may be that the High-Density group encouraged greater collaboration 

(i.e., spreading the “load”) than the Control group, though this doesn’t explain why we 

see an effect for Defense, and not for Offense, trials. 

N.4.8.3 Cohesion Results

For the 1371 volunteers at Twentynine Palms, we have Unit Cohesion survey results 

(five statements per survey) from 18 males and eight females22. Cohesion responses 

for each statement were set on a nine-point, Likert scale (one indicating “Strongly 

Disagree” and nine indicating “Strongly Agree”).

Because the cohesion responses consistently violated the normality and independence 

assumptions for parametric data, we restricted our statistical analysis to the non-

 

22 One female only participated in a single run-cycle.
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parametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). Where we had more than two 

groups to compare—and if the Kruskal-Wallis test showed significance for similarity—

then we conducted Wilcoxon pairwise comparisons (using p < 0.033 to adjust for 

multiple comparisons).

N.4.8.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five responses, which scaled between 5 and 45)—compared between 

males and females, following the conclusion of their unit’s run-cycle. Statistical results

are summarized in the table below (Table 64).

Table 64 - Summary of Unit Cohesion Scores (by Gender) - 1371

We found significant differences between genders for only one the five cohesion 

statements (“Q2-Responsibility”), but not for the others or the overall composite 

cohesion score. When we look more closely at the distributions of each statement, most 

(for both genders) display a relatively sharp peak at “9” that tapers off over “7” and “8”, 

with only a couple (two to four) responses below “5”. 

For “Q2-Responsibility”, however, we see a very slight variation—the peak is split 

almost equally between “8” and “9”. Since the non-parametric Kruskal-Wallis looks at 

rank order, this is likely sufficient to drive the statistical difference we found. However, 

it’s hard to see how this represents a practical difference in overall perception of unit 

cohesion, nor what group dynamic might lead females to report a slightly lower score for 

just one statement (and this one in particular) out of five. 

We also graphed the means for each survey statement as a percentage of how strongly 

the volunteers agreed (positive) or disagreed (negative) with each survey statement

MOS Cohesion Gender N 

(scores) Mean SD χ2 

Statistic

χ2 pValue

1371

Q1: Group was united in trying to 

reach goals

M 287 8.21 1.33

2.25 0.13

F 75 7.80 2.01

Q2: We all take responsibility for task

success of the group

M 287 8.16 1.43

4.72 0.03*

F 75 7.79 1.82

Q3: Group members have similar 

aspirations for success

M 287 8.05 1.54

1.12 0.29

F 75 7.72 2.05

Q4: If members had problems with a 

task, all wanted to help

M 287 8.08 1.48

1.58 0.21

F 75 7.60 2.22

Q5: Members communicated freely 

about responsibilities

M 287 8.18 1.43

0.45 0.50

F 75 7.88 1.92

Composite Score (sum of Q1-Q5)

M 287 40.68 6.83

1.12 0.29

F 75 38.79 9.63
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(Figure 12). While the average values appear to show females with slightly lower unit 

cohesion scores than males—this would be overstating our results. Indeed, based upon 

the lack of significance for most questions—and the similarity of distributions we saw 

between the one statement that did show a significant difference (“Q2-Responsibility”)—

we might expect male and female averages to converge with the addition of more trials.

Figure 12 - Perception of Unit Cohesion (by Gender) – 1371

N.4.8.3.2 Cohesion Results by Integration Level

In addition to looking at how unit cohesion scores compared between males and 

females, we also examined whether males’ cohesion responses remained consistent at 

different integration levels. For 1371s, we compared males’ responses in Control (i.e., 

all-male), Low-Density (i.e., 2 females), and High-Density (i.e., 4 females) Engineer 

Squads. We have unit cohesion survey results (five statements per survey) from 18 

males (18 in the Control and Low-Density groups, and 15 in the High-Density group); 

statistical results are summarized in the table below (Table 65).
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Table 65 - Summary of Males' Unit Cohesion Scores (by Integration Level) - 1371

We found a statistical difference between the Control group and both integration levels 

(i.e., High-Density, and Low-Density groups) for all five cohesion statements, as well as 

for the overall composite cohesion score. However, we did not see a difference between 

the two integration levels. 

When we looked at the distributions of each question, we see very similar patterns—the 

majority of responses are heavily skewed to the far right (i.e., “9”, at Significantly 

Agree), and taper off relatively quickly to the left. Where the differences occur is in the 

sharpness of the main peak at “9” and the span of the taper. For Control groups, we see 

MOS Cohesion IL N 

(scores) Mean SD χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

1371

Q1: Group was united in 

trying to reach goals

C 158 8.53 0.89

16.55 <0.01*

(LD-C)

-3.24 <0.01*

LD 82 7.90 1.45 (HD-C)

-3.41 <0.01*

HD 47 7.68 1.96 (HD-LD)

-0.41 0.68

Q2: We all take 

responsibility for task 

success of the group

C 158 8.47 0.94

11.26 <0.01*

(LD-C)

-2.73 <0.01*

LD 82 7.93 1.43 (HD-C)

-2.73 <0.01*

HD 47 7.53 2.32 (HD-LD)

-0.33 0.74

Q3: Group members have 

similar aspirations for 

success

C 158 8.39 1.05

14.08 <0.01*

(LD-C)

-3.24 <0.01*

LD 82 7.73 1.60 (HD-C)

-2.85 <0.01*

HD 47 7.47 2.37 (HD-LD)

-.10 0.92

Q4: If members had 

problems with a task, all 

wanted to help

C 158 8.42 0.98

15.35 <0.01*

(LD-C)

-3.00 <0.01*

LD 82 7.80 1.50 (HD-C)

-3.34 <0.01*

HD 47 7.40 2.31 (HD-LD)

-0.71 0.48

Q5: Members 

communicated freely about 

responsibilities

C 158 8.48 0.97

11.82 <0.01*

(LD-C)

-2.74 <0.01*

LD 82 7.96 1.34 (HD-C)

-2.85 <0.01*

HD 47 7.53 2.37 (HD-LD)

-0.43 0.67

Composite Score 

(sum of Q1-Q5)

Lowest: 5 | Highest 45

C 158 42.30 4.51

14.01 <0.01*

(LD-C)

-3.29 <0.01*

LD 82 39.33 6.62 (HD-C)

-2.81 <0.01*

HD 47 37.62 11.06 (HD-LD)

-0.08 0.94
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the sharpest peak (59% to 65% across all five questions) that tapers off, predominantly, 

by “7” with virtually no responses beyond that. 

For the two integrated groups, the peaks are more shallow (39% to 51%), and the taper 

spans a wider (and more negative) set of responses; for the Low-Density group the 

taper ends around “6”, while it extends out (though at rather low values) to “4” for the 

High-Density group (along with a few sporadic reports at “2” and “1”. 

We also graphed the means for each statement as a percentage of how strongly males 

agreed (positive) or disagreed (negative) with each question’s statement while in each 

group (Figure 13). The average values (by integration level) shown are consistent with 

what we saw with regards to males’ relatively high perceptions of unit cohesion within 

the Control group, along with the easy decline in their perception of cohesion when in 

the Low- and High-Density groups. 

Figure 13 - Males' Perception of Unit Cohesion (by Integration Level) - 1371

Unfortunately, the survey did not provide for reasons as to why males were more likely 

to choose lower cohesion scores when in an integrated group. Differences in 

experience also appear to be a less likely, as all volunteers were operating within their 

PMOS, but we can’t rule it out completely as females 1371s have also operated under 

additional assignment limitations that might have minimized their exposure to the field 

environment. Incidentally, males’ average values for the integrated groups appear to 

align well with how females rated their perceptions of unit cohesiveness. 
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N.4.9 Mountaineering assessment (closed MOSs only)

N.4.9.1 Fatigue Results

For the Closed MOS (03XX) volunteers at Bridgeport, we have baseline, mid-trial, and 

final fatigue self-reports from 43 males and 19 females. Because fatigue survey 

responses were ordinal in nature, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). 

N.4.9.1.1 Fatigue Results by Gender

We first looked at how fatigue self-reports compared between males and females, 

including their baseline (pre-trial), their post-5km Hike (mid-trial), and final (post-trial) 

fatigue levels. Results are summarized in the table below (Table 66). 

Table 66 - Summary of Pre-Trial, Mid-Trial, and Final Fatigue Scores (by Gender) – Closed MOS

N.4.9.1.1.1 Pre-Trial Fatigue Scores (by Gender)

We found a significant difference between female and male 03XX volunteers’ pre-trial 

fatigue scores at Bridgeport. Males’ responses typically clustered around “1-Fully Alert” 

and “2-Very Lively” (75.7%), whereas females had smaller numbers—though still a 

majority—in this range (56.4%), with a more substantial number at “3-Okay” (37.2%) 

compared to males (17.6%). 

However, we found only three reports in the higher fatigue scores (i.e., “5-Moderately 

Tired”, “6-Extremely Tired”, or “7-Exhausted”) for males (1.4%) and none among the 

females’ responses. Given the short duration of this phase of the study, and the 

relatively small number of trials per individual, it’s not possible to determine whether 

there might be a pattern over time. However, with most pre-trial scores falling at “4-A 

Little Tired” or below, we believe most volunteers had sufficient recovery time between 

trials. 

MOS Fatigue Location / 

Day Gender N Median / 

Mode χ2 Statistic χ2 p-Value

03XX

Baseline 

(Pre-Trial)

Bridgeport/1

“Mountain”

M 222 2 / 2

18.3 <0.01*

F 78 3 / 3

Post-5km

(Mid-Trial)

Bridgeport/1

“Mountain”

M 214 2 / 3

13.4 <0.01*

F 72 4 / 3

Final

(Post-Trial)

Bridgeport/1

“Mountain”

M 220 2.5 / 2

15.5 <0.01*

F 78 3 / 3
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N.4.9.1.1.2 Final Fatigue Scores (by Gender)

In looking at the volunteers’ post-trial responses at Bridgeport, we found significant 

differences in the distribution of scores by gender. Males showed a majority—and 

nearly flat distribution—across the first three levels (75.2%) before tapering sharply from 

“4-A Little Tired” to “7-Exhausted” (8.4%) (Table 67). Females showed a very similar 

pattern, but shifted to the right (towards slightly higher fatigue) by one level (i.e., “2-Very 

Lively” to “4-A Little Tired”, accounting for 69.4%), with a sharp (and shorter) taper from 

“5-Moderately Tired” to “6-Extremely Tired” (22.2%). 

In looking more closely at the higher range scores for both genders (i.e., “5-Moderately 

Tired”, “6-Extremely Tired”, and “7-Exhausted”), we see that these scores represent 

only a relatively small sub-set of each group (i.e., seven of 19 females and eight of 43 

males), with most contributions to this range being only one or two reports per Marine; 

only two females and four males had more than two reports each.

However, as each Marine—male or female—only participated in a very few number of 

trials at Bridgeport (an average of four trials for females, and five for males), and only 

small sub-populations ever reported a post-trial fatigue greater than “4-A Little Tired”, 

we should be cautious in trusting the robustness of this difference between males and 

females. 

N.4.9.1.1.3 Post-5km Hike Fatigue Scores (by Gender)

The 03XX volunteers also completed a fatigue survey following the completion of their 

5km Hike under load at Bridgeport; we found a significant difference in the distributions 

of male and female responses for this as well. Most post-5km Hike scores for males 

were at “3-Okay” and below (81.8%), whereas females had a slightly flatter profile that 

spanned a wider range, from “2-Very Lively” to “5-Moderately Tired” (88.9%). 

As with the post-trial results, when we looked more closely at who contributed to the 

scores for both groups at “5-Moderately Tired” and above, only five of 19 females 

contributed (but only two—the same two who had reported multiple scores in this range 

after the 5km Hike—did so more than once). 

For the males, we saw 17 out of 43 volunteers report at least once in this higher range, 

but only three had done so more than once. As such—with so few trials and a handful of 

Marines that reported in this range more than once—it’s difficult to say whether the 

difference between males and females in this range is persistent and meaningful. 
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Table 67 - Pre-Trial, Mid-Trial, and Final Fatigue Score Distributions (by Gender) – 03XX

N.4.9.1.2 Fatigue Results by Integration Level

Next, we looked at whether males fatigue responses remained consistent at different 

integration levels. For the 03XXs at Bridgeport, we compared males’ responses in 

Control (i.e., all-male) versus High-Density (i.e., 6 females) Rifle Squads. We have midtrial and final fatigue self-reports from 43 males in total—42 in the Control group and 36 

in the High-Density group; statistical results are summarized in the table below (Table 

68). 

Table 68 – Summary of Males’ Mid-Trial and Final Fatigue Scores (by Integration Level) – 03XX

N.4.9.1.2.1 Post-5km Hike Fatigue Scores (by Integration Level)

Following the 5km Hike, we found the distribution of males’ fatigue responses in HighDensity Squads to be significantly different from those in Control Squads (towards less 

fatigue). In both groups, we saw relatively shallow distributions, predominantly clustered 

in the lower range (“3-Okay” and below). However, for the High-Density group, we saw 

a heavier representation in the first two levels (62.0%) compared to the Control group 

(46.9%), suggesting males were more likely to be less tired, post-hike, in the integrated 

group.

For the higher range (“5-Moderately Tired”, “6-Extremely Tired”, and “7-Exhausted”), we 

also see more scores—though still relatively low numbers—in the Control group 

MOS Fatigue Location / Day IL N Median / 

Mode χ2 Statistic χ2 p-Value

03XX

Post-5km

(Mid-Trial)

Bridgeport/1

“Mountain”

C 143 3 / 3

7.3 <0.01*

HD 71 2 / 1

Final

(Post-Trial)

Bridgeport/1

“Mountain”

C 142 3 / 3

12.7 <0.01*

HD 72 2 / 1
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(14.7%) than in the High-Density group (1.4%). In the Control group, this percentage 

represents mostly one-off responses by a significant number of the male volunteers (17 

out of 42); only three actually responded more than once in this range, while the HighDensity results are the result of a single response.

Given the small numbers of both contributors and trials in this phase of the study, we 

cannot say at this time whether the higher-end scores represent a meaningful pattern 

between integration levels, but it does seem clear that there’s a consistent (though 

relatively slight) depression in the fatigue responses by males in the High-Density group 

from that seen in all-male groups. 

At the very least, 12 of the 13 Marines who had been in both groups and who had 

reported at least once (while in the Control group) a fatigue level of “5-Moderately Tired” 

or higher did not report any scores in this range when in the High-Density group. This is 

hardly definitive, since the number of trials any individual male might have participated 

in ranged from only one to five, but it is suggestive that this is a pretty consistent 

pattern. 

As was proposed in a number of the Infantry results above for the 7km Hike under 

load—which frequently showed a similar reduction in fatigue for males in certain 

integrated groups—one potential reason for this shift after the 5km Hike could be the 

slower pace typically seen by High-Density groups (see Annex A). 

N.4.9.1.2.2 Final Fatigue Scores (by Integration Level)

Post-trial fatigue results by Integration Level are very similar to those seen in the post5km Hike above—the two groups are significantly different, with High-Density 

participants showing a higher representation (63.9%) in lowest fatigue levels (i.e., “1-

Fully Alert” or “2-Very Lively”) compared to males in the Control group (41.5%), with a 

corresponding decrease in the three higher-end scores (4.2% and 10.6%, for HighDensity and Control groups, respectively).

When we looked more closely at the contributors to these higher scores (“5-Moderately 

Tired” to “7-Exhausted”) in the Control group, we see a smaller sub-population (eight 

out of 42) compared to the 5km hike results. Indeed, seven of these eight had also 

contributed higher-end scores following the hike, which suggests—given the constraints 

of a relatively small number of trials—that this is not a universal trait (i.e., not 

representative of the majority of volunteers). 

Conversely, of the 36 males who participated in both High-Density and Control groups, 

only two failed to show a general lowering of their post-trial fatigue range while in an 

integrated group (or were not already consistently reporting scores of “2-Very Lively” or 

less). Of course, we still suffer from a small number of trials for the Bridgeport phase), 
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but this does suggest that the shift (though minor) towards less fatigue in the HighDensity group is persistent. 

As discussed in the post- hike section, one potential mechanism for this shift may be the 

generally slower pace of integrated squads, compared to Control squads. Of the 

thirteen integrated trials that were executed at Bridgeport, eleven had at least one 

female reporting a score of “5-Moderately Tired” or higher, although the majority of 

females (12 out of 19) never reported a fatigue score in this range.

If pace is the mechanism driving the difference between Control and integrated 

groups—and assuming that the Marines who are most tired (i.e., “5-Moderately Tired” or 

higher) drive the slower pace—then we might see different results if we didn’t include 

the same subjects multiple times. In other words, because we had a sub-population that 

repeatedly reported high fatigue levels, including them over and over within a small set 

of trials may have over-inflated their contribution compared to the larger Marine Corps 

population.

It may also be that the slower pace in integrated groups could be influenced by group 

dynamics. The increased representation of the higher-end scores (“5-Moderately Tired” 

or higher) in all-male groups could mean a greater willingness to push a pace despite it 

being fatiguing to some members. 

Table 69 – Males’ Mid-Trial and Final Fatigue Score Distributions (by Integration Level) – 03XX

N.4.9.2 Workload Results

For the Closed MOS (i.e., 03XX) volunteers at Bridgeport, we have maximum workload 

self-reports from 43 males and 19 females23. Because workload survey responses were 

ordinal in nature, we restricted our statistical analysis to the non-parametric Kruskal-

 

23 Two Marines—one male and one female—only participated in two trials (each).
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Wallis (rank sum) test to check for significance between factors, using the criteria of p ≤ 

0.10 for statistical significance (*). 

N.4.9.2.1 Workload Results by Gender

We first looked at how maximum workload self-reports compared between males and 

females. Statistical results are summarized in the table below (Table 70). 

Table 70 - Summary of Max Workload Scores (by Gender) – Closed MOS (03XX) 

We found a significant difference—by gender—among Closed MOS (i.e., 03XX) 

volunteers at Bridgeport. Males’ responses were typically clustered around “3-Active but 

Easy” or “4-Challenging” (75.0%), whereas females’ responses appear more broadly 

spread between “3-Active but Easy”, “4-Challenging”, and “5-Extremely Busy” (88.9%).

Table 71 - Max Workload Score Distributions (by Gender) – 03XX

For this scenario, we saw a rather wide range of responses for both genders (spanning 

from six to seven—out of seven possible—levels), yet nothing about the scenario could 

be said to be “MOS-specific” in nature and very little opportunity for compensation 

mechanisms—making it a bit difficult to ascertain what “workload” might mean in this 

context.

As such, we can’t rule out that the differences we saw in maximum workload scores 

between male and female 03XXs may have been closely tied to fatigue, which we had 

previously found to be significantly different between males and female. Even relatively 

low levels of fatigue can degrade concentration and performance of non-rote skills. 

Although we don’t have great fidelity as to what tasks or elements elicited a particular 

max workload report, we do know that all “max” scores were reported in the final survey 

(as opposed to the post-5km Hike survey)—which suggests that peak “loading” 

MOS Workload Location / Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

03XX

Max 

Workload for 

Trial

Bridgeport

“Mountain” 

M 212 4 / 4

14.1 <0.01*

F 72 4 / 4
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occurred during either the gorge crossing, cliff ascent, or return hike. If females were—

in general—a bit more tired following the 5km hike, then it would be understandable that 

(potentially) unfamiliar techniques associated with crossing a gorge and/or rock climbing 

might be more challenging, even if the actual work “load” remained constant from trial to 

trial. 

N.4.9.2.2 Workload Results by Integration Level

In addition to looking at how maximum workload self-reports compared between males 

and females, we also examined whether males’ responses remained consistent at 

different integration levels. For the 03XXs, we compared males’ responses in Control 

(i.e., all-male) and High-Density (i.e., 6 females) squads. We have maximum workload 

self-reports from 43 males (42 in the Control group, and 36 in the High-Density group); 

statistical results are summarized in the table below (Table 72). 

Table 72 - Summary of Males' Maximum Workload Scores (by Integration Level) - 03XX

We saw a significant difference between males’ responses in Control and High-Density 

groups at Bridgeport, likely the result of the pronounced shift towards lower maximum

workload scores in the High-Density group (mostly “3-Active but Easy”) compared to 

Control (mostly “4-Challenging”), as illustrated by the differences in their respective

medians and modes. 

Table 73 - Males’ Max Workload Score Distributions (by Integration Level) – Closed MOS

This might be driven by a couple of factors, including the lower fatigue scores often 

seen (by males) in High Density groups or a shift towards greater collaboration (i.e., a 

“spreading of the load”) in integrated groups. Given the lack of much “MOS-specific” 

tasks at Bridgeport—and that the non-hiking tasks (i.e., the Gorge Crossing and Cliff 

Ascent tasks) aren’t really conducive to collaboration between individuals, the influence 

MOS Workload Location / Day IL N Median / 

Mode χ2 Statistic χ2 p-Value

03XX

Max 

Workload for 

Trial

Bridgeport

“Mountain”

C 140 4 / 4

15.3 <0.01*

HD 72 3 / 3
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of reduced fatigue (perhaps do to the slower pace typically seen in High Density 

groups—see Annex L) seems like the most plausible theory. 

N.4.9.3 Cohesion Results

For the Close MOS (03XX) volunteers at Bridgeport, we have Unit Cohesion survey 

results (five statements per survey) from 43 males and 19 females24. Cohesion

responses for each statement were set on a nine-point, Likert scale (one indicating 

“Strongly Disagree” and nine indicating “Strongly Agree”). 

Because the cohesion responses consistently violated the normality and independence 

assumptions for parametric data, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). 

N.4.9.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five responses, which scaled between 5 and 45)—compared between 

males and females, following the conclusion of their unit’s run-cycle. Statistical results

are summarized in the table below (Table 74).

Table 74 - Summary of Unit Cohesion Scores (by Gender) - Closed MOS (03XX)

We found a significant difference between 03XX males and females for all five cohesion 

statements (“Q1-Unity”, “Q2-Responsibility”, “Q3-Aspirations”, “Q4-Help” and “Q5-

Comm”), as well as for the overall composite cohesion score. When we look more 

 

24 Two Marines—one male and one female—only participated in two run-cycles (each).

MOS Cohesion Gender N Mean SD χ2 

Statistic

χ2 pValue

03XX

Q1: Group was united in trying to 

reach goals

M 213 7.13 2.32

7.32 <0.01*

F 72 6.28 2.69

Q2: We all take responsibility for 

task success of the group

M 213 7.12 2.30

5.73 0.02*

F 72 6.38 2.58

Q3: Group members have similar 

aspirations for success

M 213 7.09 2.45

7.53 <0.01*

F 72 6.29 2.59

Q4: If members had problems with a 

task, all wanted to help

M 213 7.17 2.30

15.09 <0.01*

F 72 5.82 2.70

Q5: Members communicated freely 

about responsibilities

M 213 7.22 2.28

8.81 <0.01*

F 72 6.22 2.64

Composite Score (sum of Q1-Q5)

M 213 35.73 11.35

9.17 <0.01*

F 72 30.99 12.62
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closely at the distribution of responses for each statement, we see that females tended 

to be quite a bit more pessimistic (i.e., lower scores) than males. 

Where males tended to have responses that cluster between “7” and “9” for all five 

questions (ranging from 69.5% to 72.8% of all responses) with a scattering of responses 

below “6” (towards Significantly Disagree), females had fewer contributions in the top 

three levels (45.8% to 58.3%), with a corresponding increase in representation below 

“6”—including roughly 10% at the lowest level, “1”. 

We also graphed the means for each statement as a percentage of how strongly the 

volunteers agreed (positive) or disagreed (negative) with each question’s statement 

(Figure 14).

Figure 14 - Perception of Unit Cohesion (by Gender) - Closed MOS (03XX)

In looking at the average values for the 03XX volunteers, we can see how both 

genders—while more positive than negative—appeared to be somewhat neutral in their 

perceptions of unit cohesion, with females consistently showing a more pessimistic 

outlook on unit cohesion. 

As nothing about the Mountaineering scenario was MOS-specific (and it’s unlikely that 

most—if any—of the Marines had previous exposure to the more technical tasks of 

crossing the gorge, or conducting a cliff ascent), relative experience is not likely a factor. 

Since Bridgeport occurred at the end of an already long study, it may be that the 

general depression of cohesion (from the levels experienced by each constituent MOS, 

from their Twentynine Palms tenure)—and the sharper drop among females—may be a 

reflection of suddenly working with new individuals (i.e., different 03XX MOS) and/or 

falling morale. 
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N.4.9.3.2 Cohesion Results by Integration Level

In addition to looking at how unit cohesion scores compared between males and 

females, we also examined whether males’ cohesion responses remained consistent at 

different integration levels. For the Closed MOS (03XX) at Bridgeport, we compared 

males’ responses in Control (i.e., all-male) and High-Density (i.e., 6 females) Squads. 

We have unit cohesion survey results (five statements per survey) from 43 males (42 in 

the Control group, and 36 in the High-Density group); statistical results are summarized 

in the table below (Table 75).

Table 75 - Summary of Males' Unit Cohesion Scores (by Integration Level) – Close MOS (03XX)

We found a significant difference between the Control and High-Density groups for all 

five cohesion statements, as well as for the overall composite cohesion score. When we 

look more closely at the distributions, we see two very different patterns. 

For the Control Group, we see the single most common response at “9” (48% to 55%), 

with a rather rapid drop off spanning from “8” to “7”—and only sporadic reports below 

that. With the High-Density groups, however, we see a very pronounced “triple peak”, 

with peaks at the two extrema (21% to 22% at “9” and 13% to 17% at “1), and a “bulge” 

around the mid-point. This suggests pronounced difference of opinion by males—

perhaps an artifact of a multi-MOS unit that had never worked together towards a 

common goal. 

We also graphed the means for each statement as a percentage of how strongly males 

agreed (positive) or disagreed (negative) with each question’s statement while in each 

group (Figure 15). The average values (by integration level) shown are consistent with 

what we saw with regards to males’ more coherent, and relatively high perceptions of 

MOS Cohesion IL N Mean SD χ2 

Statistic

χ2 pValue

03XX

Q1: Group was united in trying to 

reach goals

C 141 7.79 1.78

32.57 <0.01*

HD 72 5.83 2.69

Q2: We all take responsibility for 

task success of the group

C 141 7.82 1.69

34.93 <0.01*

HD 72 5.74 2.69

Q3: Group members have similar 

aspirations for success

C 141 7.87 1.78

39.78 <0.01*

HD 72 5.56 2.83

Q4: If members had problems with a 

task, all wanted to help

C 141 7.83 1.82

33.86 <0.01*

HD 72 5.89 2.60

Q5: Members communicated freely 

about responsibilities

C 141 7.88 1.73

33.29 <0.01*

HD 72 5.93 2.66

Composite Score (sum of Q1-Q5)

Lowest: 5 | Highest 45

C 141 39.20 8.60

34.57 <0.01*

HD 72 28.94 12.98
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unit cohesion within the Control group, against the disjointed, and highly negative point 

scores in the High-Density group. 

Unfortunately, the survey did not provide for reasons as to why males were so much 

more likely to choose such profoundly lower cohesion scores when in an integrated 

group. Given the nature of the scenario, it seems relative experience should not be a 

factor. 

However, the 03XX pool was also composed of an assortment of various “03” MOS—

who’d operated in parallel for several months, but not really together. Add to this, the 

Bridgeport phase taking place after a very long and tiring Twentynine Palms section, it’s 

no wonder cohesion may have suffered. The unknown is why that effect seems to have 

been so heavily asymmetrical against integrated groups. Incidentally, these neutral 

results are consistent with females’ perception of unit cohesiveness for these trials. As 

such, there may have well been a serious morale issues at play. 

Figure 15 - Males' Perception of Unit Cohesion (by Integration Level) - 03XX

N.4.10 Mountaineering assessment (open MOSs only)

N.4.10.1 Fatigue Results

For the Open MOS (i.e., Provisional Infantry and 1371) volunteers at Bridgeport, we 

have baseline, mid-trial, and final fatigue self-reports from 45 males and 17 females25. 

Because fatigue survey responses were ordinal in nature, we restricted our statistical 

analysis to the non-parametric Kruskal-Wallis (rank sum) test to check for significance 

between factors, using the criteria of p ≤ 0.10 for statistical significance (*). 

 

25 Four Marines, two males and two females only participated in two or fewer trials (each).
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N.4.10.1.1 Fatigue Results by Gender

We first looked at how fatigue self-reports compared between males and females, 

including their baseline (pre-trial), their post-5km Hike (mid-trial), and final (post-trial) 

fatigue levels. Results are summarized in the table below (Table 76). 

Table 76 - Summary of Pre-Trial, Mid-Trial, and Final Fatigue Scores (by Gender) – Open MOS

N.4.10.1.1.1 Pre-Trial Fatigue Scores (by Gender)

We found a significant difference between female and male PI and 1371 volunteers’ 

pre-trial fatigue scores at Bridgeport. Males’ responses typically clustered between “1-

Fully Alert” and “3-Okay” (91.1%), whereas females had smaller numbers—though still 

a majority—in this range (76.7%), with more representation at “4-A Little Tired” (15.0%) 

compared to males (3.4%). 

We found few reports in the higher fatigue scores (i.e., “5-Moderately Tired”, “6-

Extremely Tired”, or “7-Exhausted”) for either gender—5.6 percent for males (by five 

Marines, but mostly driven by one), and 8.3 percent for females (by three Marines, but 

mostly driven by one). Given the short duration of this phase of the study, and the 

relatively small number of trials per individual, it’s not possible to determine whether 

there might be a pattern over time. However, with most pre-trial scores falling at “4-A 

Little Tired” or below, we believe most volunteers had sufficient recovery time between 

trials. 

N.4.10.1.1.2 Final Fatigue Scores (by Gender)

In looking at the open MOS volunteers’ post-trial responses at Bridgeport, we found 

significant differences in the distribution of scores by gender. Males showed a (scarce) 

majority clustered around “2-Very Lively” and “3-Okay” (53.6%), with shallow “tails” at 

“1-Fully Alert” and “4-A Little Tired” (Table 77). Females showed a very similar pattern, 

but shifted to the right by one level (i.e., centered at “3-Okay” and “4-A Little Tired”, 

accounting for 65.0%), with the same shallow “tails” to either side. Both groups show a 

small representation at the two highest levels (“6-Extremelly Tired” and “7-Exhausted”).

In looking more closely at these higher scores, we see that these scores represent only 

a relatively small sub-set of each group (i.e., two of 17 females and six of 45 males), 

MOS Fatigue Location / 

Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

PI & 

1371

Baseline 

(Pre-Trial)

Bridgeport/1

“Mountain”

M 179 2 / 2

18.3 <0.01*

F 60 3 / 3

Post-5km

(Mid-Trial)

Bridgeport/1

“Mountain”

M 176 3 / 3

14.2 <0.01*

F 59 4 / 3

Final

(Post-Trial)

Bridgeport/1

“Mountain”

M 179 3 / 2,3

15.5 <0.01*

F 60 3 / 4
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with most contributions to this range being only one report per Marine; only one females 

and two males had more. However, as all but one male Marine had response ranges 

that fall within the “2-Very Lively” and “5-Moderately Tired” span, the shift we see 

towards slightly more fatigued results in the female group is likely reliable.

N.4.10.1.1.3 Post-5km Hike Fatigue Scores (by Gender)

The PI & 1371 volunteers also completed a fatigue survey following the completion of 

their 5km Hike under load at Bridgeport; we found a significant difference in the 

distributions of male and female responses for this as well. For both males and females 

we saw the same pattern of distributions as found post-trial (i.e., males clustered around 

“2-Very Lively” and “3-Okay” and females shifted a bit higher around “3-Okay” and “4-A 

Little Tired”, with both groups having shallow “tails” to either side). 

As with the post-trial results, when we looked more closely at who contributed to the 

scores for both groups at “6-Extremely Tired” and “7-Exhausted”, only three of 17 

females and five of 45 males contributed (but only one Marine per group did so more 

than once). Similar to the final fatigue results, since we only see two Marines (one male 

and one female) who don’t have a range of responses within the “2-Very Lively” and “5-

Moderately Tired” span, the post-hike shift towards slightly higher fatigue levels found in 

females is likely reliable.

Table 77 - Pre-Trial, Mid-Trial, and Final Fatigue Score Distributions (by Gender) – Open MOS

N.4.10.1.2 Fatigue Results by Integration Level

Next, we looked at whether males fatigue responses remained consistent at different 

integration levels. Open MOS (i.e., Provisional Infantry and 1371) volunteers at 

Bridgeport, we compared males’ responses in Control (i.e., all-male) and High-Density 

(i.e., 6 females) squads. We have unit cohesion survey results (five statements per 
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survey) from 45 males (45 in the Control group, and 34 in the High-Density group); 

statistical results are summarized in the table below (Table 78). 

Table 78 – Summary of Males’ Mid-Trial and Final Fatigue Scores (by Integration Level) – Open MOS

N.4.10.1.2.1 Post-5km Hike Fatigue Scores (by Integration Level)

Following the 5km Hike under load at Bridgeport, we did not find any significant 

difference in males’ fatigue responses by Integration Level. In both groups, we see a 

(close) majority of responses falling between “2-Very Lively” and “3-Okay” (54.7% and 

64.4% for Control and High-Density groups, respectively), although the Control group 

showed an increased likelihood of responses at “4-A Little Tired” (23.1%) than the HighDensity group (6.8%). We also see a slightly greater representation in the higher range 

(“5-Moderately Tired” and higher) for High-Density group (15.3%) than in the Control 

group (10.3%).

When we look more closely at the contributors to these higher scores, we see that the 

Control group has a broader base (10 out of 45 Marines—most contributing a single 

response) than the High-Density group (four out of 35 Marines, largely driven by only 

two Marines). This suggests that the High-Density results in this range may largely be 

an artifact caused by a couple of Marines and not a pattern that would persist if we had 

the opportunity to run more trials without repeating subjects. 

N.4.10.1.2.2 Final Fatigue Scores (by Integration Level)

Post-trial fatigue results by Integration Level were significantly different between groups, 

with Control groups showing a more shallow cluster between “2-Very Lively” and “3-

Okay” tapering to “1-Fully Alert” and “4-A Little Tired” than the High-Density group that 

has a much sharper distribution peaking at “3-Okay” and skewing slightly to the left. 

However, at the macro level, both groups are very similar in the total representation of 

scores at “4-A Little Tired” and below (83.4% for Control group, 86.7% for High Density 

group), which suggests there may be little practical difference between the two groups.

As with the post-hike results, the higher-end scores seen at the end of the trial were 

more broadly supported within the Control group volunteers (one to two responses by 

17 Marines out of 45) compared to the sparse contributions within the High-Density 

group (four Marines out of 35). As such, we might expect the shape of the upper 

distribution in the Control group to be preserved (if we had the opportunity to run more 

MOS Fatigue Day IL N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

PI & 

1371

Post-5km

(Mid-Trial)

Bridgeport/1

“Mountain”

C 117 3 / 3

0.48 0.49

HD 59 3 / 3

Final

(Post-Trial)

Bridgeport/1

“Mountain”

C 143 3 / 3

7.3 <0.01*

HD 71 2 / 1
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trials), whereas the High-Density upper distribution might become less prominent. This 

would be more consistent with a pattern we saw frequently among Infantry—males in 

highly-integrated groups typically showing a lower distribution of fatigue scores than allmale groups when there was a task involving a long-duration hike under load, perhaps 

due to slower paces (see Annex M). However, without additional trials to clarify, this is 

only theoretical. 

Table 79 – Males’ Mid-Trial and Final Fatigue Score Distributions (by Integration Level) – Open MOS

N.4.10.2 Workload Results

For the Open MOS (i.e., Provisional Infantry and 1371) volunteers at Bridgeport, we 

have maximum workload self-reports from 45 males and 17 females26. Because 

workload survey responses were ordinal in nature, we restricted our statistical analysis 

to the non-parametric Kruskal-Wallis (rank sum) test to check for significance between 

factors, using the criteria of p ≤ 0.10 for statistical significance (*). 

N.4.10.2.1 Workload Results by Gender

We first looked at how maximum workload self-reports compared between males and 

females. Statistical results are summarized in the table below (Table 80). 

Table 80 - Summary of Max Workload Scores (by Gender) – Open MOS

As in the Closed MOS results, we found a significant difference—by gender—among 

Open MOS (i.e., PI and 1371) volunteers at Bridgeport. Males’ responses typically 

 

26 Four Marines—two males and two females—only participated in two or fewer trials (each).

MOS Workload Location / Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

PI & 

1371

Max 

Workload for 

Trial

Bridgeport/1

“Mountain”

M 178 4 / 4

11.0 <0.01*

F 60 4 / 4
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spanned from “2-Little to Do” to “5-Extremely Busy” (89.9%), and peaking at “4-

Challenging”. Female responses appeared to be more tightly clustered between “3-

Active but Easy” and “5-Extremely Busy”, with a sharper peak at “4-Challenging” 

(96.7%). 

As discussed in the Closed MOS section (see N.5.9.2), it’s difficult to determine what 

“workload” might mean within the context of the Bridgeport Scheme of Maneuver, given 

that the tasks required were not specific to any particular MOS and the Scheme of 

Maneuver did not generally allow for compensation mechanisms. It’s possible that the 

differences we saw in max workload scores between Open MOS males and females 

may have been closely linked with fatigue, which were also significantly different 

between males and female. Even relatively low levels of fatigue can degrade 

concentration and performance of non-rote skills. 

Table 81 - Max Workload Score Distributions (by Gender) – Open MOS (PI & 1371)

Although we don’t have great fidelity as to what tasks or elements elicited a particular 

maximum workload report, we do know that all “max” scores were reported in the final 

survey (as opposed to the post-5km Hike survey)—which suggests that peak “loading” 

occurred during either the gorge crossing, cliff ascent, or return hike. If females were—

in general—a bit more tired following the 5km hike, then it would understandable that 

(potentially) unfamiliar techniques associated with crossing a gorge and/or rock climbing 

might be more challenging, even if the actual work “load” remained constant from trial to 

trial. 

N.4.10.2.2 Workload Results by Integration Level

In addition to looking at how maximum workload self-reports compared between males 

and females, we also examined whether males’ responses remained consistent at 

different integration levels. For PI and 1371s, we compared males’ responses in Control 

(i.e., all-male) and High-Density (i.e., 6 females) Squads. We have max workload selfreports from 45 males (45 in the Control group, and 34 in the High-Density group); 

statistical results are summarized in the table below (Table 82). 
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Table 82 - Summary of Males' Max Workload Scores (by Integration Level) - Open MOS

We did not see a significant difference between males’ responses in Control and HighDensity groups at Bridgeport for Open MOS (i.e., PI and 1371) volunteers. For both 

groups, males tend to favor maximum workload scores between “3-Active but Easy” and 

“4-Challenging”, though there is also some representation at all levels. 

Table 83 - Males’ Max Workload Score Distributions (by Integration Level) – Open MOS

N.4.10.3 Cohesion Results

For the Open MOS (PI and 1371) volunteers at Bridgeport, we have Unit Cohesion 

survey results (five statements per survey) 45 males and 17 females27. Cohesion

responses for each statement were set on a nine-point, Likert scale (one indicating 

“Strongly Disagree” and nine indicating “Strongly Agree”). 

Because the cohesion responses consistently violated the normality and independence 

assumptions for parametric data, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). 

N.4.10.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five responses, which scaled between 5 and 45)—compared between 

males and females, following the conclusion of their unit’s run-cycle. Statistical results

are summarized in the table below (Table 84).

 

27 Four Marines—two males and two females—only participated in two of fewer trials (each).

MOS Workload Location / Day IL N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

PI & 

1371

Max 

Workload for 

Trial

Bridgeport/1

“Mountain”

C 118 4 / 4

0.70 0.40

HD 60 4 / 4
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Table 84 - Summary of Unit Cohesion Scores (by Gender) - Open MOS (PI & 1371)

We found a significant difference between 03XX males and females for all five cohesion 

statements (“Q1-Unity”, “Q2-Responsibility”, “Q3-Aspirations”, “Q4-Help” and “Q5-

Comm”), as well as for the overall composite cohesion score. When we look more 

closely at the distribution of responses for each statement, we a couple of competing 

patterns. 

On one hand, males’ responses tend to cluster a bit more strongly at the two highest 

levels, “8” and “9” (78.1% to 82.6%) than females, who have slightly more shallow but 

broad (and inclusive) clustering between “7” and “9” (88.3% to 94.9%). Males were also

(slightly) more likely to report scores at the lowest three levels, “1” to “3” (3.9% to 5.1%) 

compared to females (0%). 

However, when we look more closely at the contributors to these strongly negative 

scores (i.e., “1” to “3”) among the males, we see that they are from only five Marines 

(out of 45), and so it’s unlikely this is a universal viewpoint (or at least a relatively rare 

one)—though their exclusion does not change our statistical results. This suggests the 

significance difference we found is driven by these relatively few (and non-universal) 

responses—a difference that seems unlikely to be practically relevant, given that we 

can’t be certain all Marines used the same internal criteria for judging cohesion. 

We also graphed the means for each survey statement as a percentage of how strongly 

the volunteers agreed (positive) or disagreed (negative) with each survey statement 

(Figure 16). In looking at the average values for the Open MOS volunteers, we can see 

how both genders—despite some nuances as to their specific distributions—appear to 

be largely consistent (and positive) in their relative perceptions of unit cohesion

MOS Cohesion Gender N 

(scores) Mean SD χ2 

Statistic

χ2 pValue

PI & 

1371

Q1: Group was united in trying to 

reach goals

M 178 7.98 1.79

3.46 0.06*

F 60 8.03 0.99

Q2: We all take responsibility for task 

success of the group

M 178 7.99 1.75

4.34 0.04*

F 60 7.90 1.17

Q3: Group members have similar 

aspirations for success

M 178 7.93 1.79

3.84 0.05*

F 60 7.87 1.19

Q4: If members had problems with a 

task, all wanted to help

M 178 8.06 1.68

7.41 <0.01*

F 60 7.87 1.11

Q5: Members communicated freely 

about responsibilities

M 178 8.07 1.66

4.44 0.04*

F 60 8.05 0.94

Composite Score (sum of Q1-Q5)

M 178 40.02 8.38

4.39 0.04*

F 60 39.64 5.07
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Figure 16 - Perception of Unit Cohesion (by Gender) - Open MOS (PI & 1371)

N.4.10.3.2 Cohesion Results by Integration Level

In addition to looking at how unit cohesion scores compared between males and 

females, we also examined whether males’ cohesion responses remained consistent at 

different integration levels. For Open MOS (i.e., PI and 1371), we compared males’ 

responses in Control (i.e., all-male) and High-Density (i.e., 6 females) Squads. We have 

unit cohesion survey results (five statements per survey) from 45 males (45 in the 

Control group, and 34 in the High-Density group); statistical results are summarized in 

the table below (Table 85).

Table 85 - Summary of Males' Unit Cohesion Scores (by Integration Level) Open MOS (PI & 1371)

MOS Cohesion IL N (scores) Mean SD χ2 

Statistic

χ2 pValue

PI & 

1371

Q1: Group was united in trying to 

reach goals

C 118 8.16 1.36

0.40 0.53

HD 60 7.62 2.40

Q2: We all take responsibility for 

task success of the group

C 118 8.10 1.40

0.17 0.68

HD 60 7.77 2.28

Q3: Group members have similar 

aspirations for success

C 118 8.08 1.48

0.59 0.44

HD 60 7.62 2.26

Q4: If members had problems with a 

task, all wanted to help

C 118 8.21 1.29

0.11 0.74

HD 60 7.75 2.23

Q5: Members communicated freely 

about responsibilities

C 118 8.20 1.32

0.09 0.77

HD 60 7.82 2.17

Composite Score (sum of Q1-Q5)

Lowest: 5 | Highest 45

C 118 40.76 6.53

0.14 0.70

HD 60 38.57 11.09
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Unlike the Closed MOS, we did not see a significant difference between the two 

integration levels, regardless of the question. For both groups, we see the single most 

represented score at “9”, which drops off rather quickly by “6”—across all questions. For

the High-Density group, we do see a slight variation in the form of a small, but visible, 

percentage of responses at the lowest level (7% to 10%)—though this is not enough to 

significantly diverge the two sets of response. 

We also graphed the means for each statement as a percentage of how strongly the 

volunteers agreed (positive) or disagreed (negative) with each question’s statement 

(Figure 17). The average values (by integration level) shown are consistent with what 

we saw with regards to comparable representation for the vast majority of responses, 

but with a slight dip in the High-Density means due to the presence of some responses 

at “1”. These responses are consistent with what females reported above. 

Figure 17 - Males' Perception of Unit Cohesion (by Integration Level) - Open MOS (Bridgeport)

N.4.11 Field Artillery Cannoneer (MOS 0811)

N.4.11.1 Fatigue Results

For the 0811 volunteers at Twentynine Palms, we have baseline, mid-trial, and final 

fatigue self-reports from 28 males and twelve females28. Because fatigue survey 

responses were ordinal in nature, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). If we had more than two 

groups to compare—and if the Kruskal-Wallis test showed significance for similarity—

 

28 One male and one female only participated in a single run-cycle.
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then we conducted Wilcoxon pairwise comparisons (using p<0.033 to adjust for multiple 

comparisons). 

N.4.11.1.1 Fatigue Results by Gender

We first looked at how fatigue self-reports compared between males and females, 

including their baseline (pre-trial), post-ROSP (mid-trial), and final (post-trial) fatigue 

levels. Results are summarized in the table below (Table 86). 

Table 86 - Summary of Pre-Trial, Mid-Trial, and Final Fatigue Scores (by Gender) - 0811

N.4.11.1.1.1 Pre-Trial Fatigue Scores (by Gender)

We did not find a significant difference between female and male 0811 volunteers’ pretrial fatigue scores. In both gender groups, pre-trial responses typically clustered 

between “1-Fully Alert” and “3-Okay” (80.2% and 83.0% for males and females, 

respectively) (Table 87). 

We also found a relatively small, but persistent, number of reports in the higher fatigue 

levels for both genders (i.e., “5-Moderately Tired”, “6-Extremely Tired”, and “7-

Exhausted”)—representing 13 percent of male responses (spread across 20 Marines), 

and 9.2 percent of female responses (almost exclusively by a single Marine). In many 

instances, these higher values represented only 1-3 responses for most Marines (15 out 

of 23) over the course of the entire study. 

However, a small number of Marines (seven males and one female) frequently reported 

such high pre-trial fatigue levels (ranging from six to 18 responses each), over a period 

of 29 run-cycles. This suggests some sub-set of 0811 Marines were struggling with very 

high levels of fatigue before beginning a trial.

We should also note, however, that due to a reduction in the number of male 0811s

available—either due to medical restrictions or through dropping from the study 

entirely—males were more likely to participate on a “test” howitzer (i.e., a 6-man crew) 

MOS Fatigue Location / 

Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

0811

Baseline 

(Pre-Trial)

29Palms/1 

“Live-Fire”

M 698 3 / 3

0.004 0.95

F 153 2 / 2

Post-RSOP

(Mid-Trial)

29Palms/1 

“Live-Fire”

M 689 3 / 3

2.8 0.09*

F 152 3 / 3

Final

(Post-Trial)

29Palms/1 

“Live-Fire”

M 686 3 / 3

6.8 <0.01*

F 150 3.5 / 4
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than females29. While all Marines (on full-duty status) not assigned to a trial unit (i.e.,

“test” howitzer) were assigned to a spare howitzer in order to maintain consistent 

physical loading of the 0811 population, this “loading” gun often had more than six 

crewmembers. As such, some males may have been exposed to more physical stress 

over the course of the study, which might account for the presence of these higher pretrial scores. 

N.4.11.1.1.2 Post-RSOP Fatigue Scores (by Gender)

While not technically a part of the 0811 trial, volunteers participated in a series of 

Reconnaissance, Selection, and Occupation of Position (RSOP) tasks (see Annex H)

prior to beginning the trial proper. This served the dual purpose of allowing the assigned 

Section Chief (a direct assignment—not a volunteer) an opportunity to get familiar with 

his crew prior to the start of the test trial as well as introduce additional physical stress 

on a crew in order to more closely mimic a realistic scenario.

Upon completion of the RSOP phase, 0811 volunteers completed a fatigue survey. We 

found a significant difference in response distributions by gender, with a small shift to 

the right towards “4-A Little Tired” and “5-Moderately Tired” for females (up 10% from 

pre-trial results), compared to the much smaller rise in this same range for males (up 

2% from pre-trial results). 

When we looked at individual Marines’ responses to pre-trial and post-RSOP surveys 

for the same trial, we found a consistent results. Though not representing a majority, we 

found females were a bit more likely to report a higher scores post-RSOP (30.5%) than 

males (18.9%), though often an increase of only one. 

N.4.11.1.1.3 Final Fatigue Scores (by Gender)

In looking at the volunteers’ post-trial responses, we likewise found a significant 

difference between genders. While exactly half (50.0%) of female responses remained 

in lower range (“1-Fully Alert”, “2-Very Lively” or “3-Okay”), a sizeable percentage (46%) 

reported being “4-A Little Tired” or “5-Moderately Tired” compared to males (27.0%). 

Incidentally—and consistent across all three surveys (pre-trial, post-RSOP, and posttrial)—males led females (by a small margin) in the percentage of responses in the 

highest range (“6-Extremely Tired” and “7-Exhausted”), with 5.4 percent, compared to 

4.0 percent for females. However, this cannot be explained as a lack of movement in 

this highest range from pre-trial results. 

 

29 Females conducted, on average only 14 run-cycles (with the exclusion of one female who only participated in a 

single trial). Males, on the other had conducted, on average, 26 trials (with the exception of one male who only 

participated in one trial).
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When we looked at individual Marines’ responses, we saw a sizeable number of males 

who’d completed a trial with a fatigue score of “6-Extremely Tired” or “7-Exhausted” 

had actually started relatively fresh with a pre-trial score of “3-Okay” or lower (40.1%). 

Conversely, of the Marines that had started the day extremely fatigued (reporting a pretrial level of “6-Extremely Tired” or “7-Exhausted”), we saw a similar percentage of 

males (41.5%) who reported being only “4-A Little Tired” or less. Both subpopulations—i.e., fresh to extremely fatigued, and extremely fatigued to fresh—had 

representatives in all six billets.

Table 87 - Pre-Trial, Mid-Trial, and Final Fatigue Score Distributions (by Gender) - 0811

N.4.11.1.2 Fatigue Results by Integration Level

Next, we looked at whether males fatigue responses remained consistent at different 

integration levels. For 0811s, we compared males’ responses in Control units (i.e., allmale), Low-Density (i.e., 1 female), and High-Density (i.e., 2 females) Artillery Sections. 

We have post-RSOP and final fatigue self-reports from 28 males; statistical results are 

summarized in the table below (Table 88). 
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Table 88 – Summary of Males’ Mid-Trial and Final Fatigue Scores (by Integration Level) - 0811

N.4.11.1.2.1 Post-RSOP Fatigue Scores (by Integration Level)

Males’ responses following the completion of the RSOP phase did not show any 

significant difference between any of the three integration levels (i.e., Control, LowDensity, and High-Density). As we saw in the “by gender” results above, responses 

were predominantly clustered between “1-Fully Alert” and “3-Okay” for all three groups 

(79.4% to 80.9%) (Table 89). 

N.4.11.1.2.2 Final Fatigue Scores (by Integration Level)

Males’ post-trial responses likewise did not show any significant difference between any 

of the three integration levels (i.e., Control, Low-Density, and High-Density)—consistent 

with the “by gender” results above, with a slight shift towards “4-A Little Tired” and “5-

Moderately Tired” but largely clustered at “3-Okay” or below. This—like the last of 

difference for the post-RSOP results—is perhaps not surprising given that the roles to 

be performed by each billet were carefully controlled, with very little opportunity for the 

sharing or switching of tasks. 

It may be the fatiguing nature of each task within a trial—i.e., its contribution to total, 

post-trial fatigue—could be influenced by who is filling a particular critical billet. For 

example, a Marine who’s particularly slow performing their portion of a fire mission 

might allow the other members of the crew more time to recover, making them less 

fatigued than they might otherwise be if at a faster tempo. However, because we only 

have overall post-trial fatigue scores—and not post-task scores—we cannot determine if 

this holds true for this study. Alternatively, a different Scheme of Maneuver plan that 

allowed for sharing and/or swapping of duties might be able to tease out potential 

differences based upon critical billets. 

MOS Fatigue Day IL N Median 

/ Mode

χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

0811

Post-RSOP

(Mid-Trial)

29Palms/1 

“Live-Fire”

C 251 3 / 3

LD 226 3 / 3 1.3 0.53

HD 212 3 / 3

Final

(Post-Trial)

29Palms/1 

“Live-Fire”

C 255 3 / 3

LD 220 3 / 3 1.65 0.44

HD 211 3 / 3
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Table 89 – Males’ Mid-Trial and Final Fatigue Score Distributions (by Integration Level) - 0811

N.4.11.2 Workload Results

For the 0811 volunteers at Twentynine Palms, we have max workload self-reports from 

28 males and 12 females30. Because workload survey responses were ordinal in nature, 

we restricted our statistical analysis to the non-parametric Kruskal-Wallis (rank sum) 

test to check for significance between factors, using the criteria of p ≤ 0.10 for statistical 

significance (*). Where we had more than two groups to compare—and if the KruskalWallis test showed significance for similarity—then we conducted Wilcoxon pairwise 

comparisons (using p<0.033 to adjust for multiple comparisons).

N.4.11.2.1 Workload Results by Gender

We first looked at how maximum workload self-reports compared between males and 

females. Results are summarized in the table below (Table 90). 

Table 90 - Summary of Max Workload Scores (by Gender) – 0811

We found a significant difference between female and male 0811 volunteers’ maximum 

workload scores. While both males and females were found to be strongly clustered at 

“3-Active but Easy” and “4-Challenging” (79.1% and 77.9%, for males and females, 

respectively), males more strongly favored the former and females the latter (Table 91). 

 

30 One male and one female only participated in a single trial (each).

MOS Workload Location / Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

0811

Max 

Workload for 

Trial

29Palms/1 

“Live-Fire”

M 704 3 / 3

16.3 <0.01*

F 154 4 / 4
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We found few of the highest max workload scores for either group (i.e., “6-Overloaded” 

or “7-Unmanageable”)—only 5.3 percent of male responses and 5.2 percent of female 

responses. While a larger sub-population of males contributed to these higher max 

scores (thirteen out 28 males) than females—who had only two Marines contributing to 

this range—most Marines only did so a couple of times. This suggests most Marines felt 

capable of accomplishing (if not always easily) the workload assigned them. 

As for the difference between the two genders, this may be due to females having less 

time in the MOS—a distinct disadvantage on an Artillery Section, where all members of 

the crew must work smoothly together and there was little opportunities for 

compensation. If experience is a factor, we would expect the difference between the two 

groups to gradually disappear over time as they became more skilled. This may have 

also been influenced by the slightly higher levels of fatigue reported by female 0811s 

(both post-RSOP and post-trial), since even relatively low levels of fatigue can degrade 

concentration and performance of non-rote skills. 

Table 91 - Maximum Workload Score Distributions (by Gender) - 0811

N.4.11.2.2 Workload Results by Integration Level

In addition to looking at how max workload self-reports compared between males and 

females, we also examined whether males’ responses remained consistent at different 

integration levels. For 0811s, we compared males’ responses in Control (i.e., all-male), 

Low-Density (i.e., 1 female), and High-Density (i.e., 2 females) Artillery Sections. We 

have maximum workload self-reports from 28 males (28 males in the Control group, and 

27 males in the Low-Density and High-Density groups); statistical results are 

summarized in the table below (Table 92). 

Table 92 - Summary of Males' Maximum Workload Scores (by Integration Level) - 0811

MOS Workload Location / 

Day IL N 

(scores)

Median

/ Mode

χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

0811

Max 

Workload 

for Trial

29Palms/1 

“Live-Fire”

C 258 3 / 3

LD 230 3 / 3 0.21 0.90

HD 216 3 / 3
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We did not see a significant difference between males’ responses, regardless of the 

integration level of the unit they were in. For all three groups, males tend to favor 

maximum workload scores between “3-Active but Easy” and “4-Challenging”, though 

there is also some representation at all levels. 

However, we should also note that the design of Artillery Scheme of Maneuver, which 

largely prohibited either collaboration or compensation between members of the same 

crew. As such, we are unable to conclude whether this result would hold under 

conditions where members would be allowed more leeway in their respective division of 

labor. 

Table 93 - Males’ Max Workload Score Distributions (by Integration Level) – 0811

N.4.11.3 Cohesion Results

For the 0811 volunteers at Twentynine Palms, we have Unit Cohesion survey results 

(five statements per survey) 28 males and 12 females31. Cohesion responses for each 

statement were set on a nine-point, Likert scale (one indicating “Strongly Disagree” and 

nine indicating “Strongly Agree”). 

Because the cohesion responses consistently violated the normality and independence 

assumptions for parametric data, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). If we had more than two 

groups to compare—and if the Kruskal-Wallis test showed significance for similarity—

then we conducted Wilcoxon pairwise comparisons (using p<0.033 to adjust for multiple 

comparisons).

N.4.11.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five responses, which scaled between 5 and 45)—compared between 

 

31 One male and one female only participated in a single run-cycle (each).
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males and females, following the conclusion of their unit’s run-cycle. Statistical results

are summarized in the table below (Table 94).

Table 94 - Summary of Unit Cohesion Scores (by Gender) - 0811

We found a significant differences between 0811 males and females for four of the five 

cohesion statements (“Q1-United”, “Q2-Responsibility”, “Q3-Aspirations”, and “Q5-

Comm”), but not for “Q4-Help” or the overall composite cohesion score (although the 

latter is borderline). Overall, females tended towards being a bit more optimistic than 

males in their perception of their units’ cohesion. 

When we look more closely at the distributions of each question, we see that males 

reported a scant majority at the highest level possible, “9” (51.7% to 56.7%), for all 

questions but one (“Q4-Help”), but then taper off fairly quickly by “6” only to extend out 

to the lowest level “1” with low-level contributions that, in total, represent 20.4% to 

23.7% of all of males’ responses. 

On the other hand, females tend to peak even more sharply at “9” (52.0% to 56.0%), 

and taper off much more completely—leaving only 8.0% to 9.3% spread across “1” to 

“6” for all questions except “Q4-Help”. For the latter—the one question that is not 

significantly different from males—we see a more pessimistic spread (17.3%) in 

between “1” to “6”. 

We also graphed the means for each survey statement as a percentage of how strongly 

the volunteers agreed (positive) or disagreed (negative) with each survey statement 

(Figure 18). 

MOS Location Cohesion Gender N 

(scores) Mean SD χ2 

Statistic

χ2 pValue

0811 29Palms

Q1: Group was united in trying 

to reach goals

M 691 7.59 1.92

7.05 <0.01*

F 150 8.15 1.37

Q2: We all take responsibility for 

task success of the group

M 691 7.58 1.93

3.63 0.06*

F 150 8.01 1.58

Q3: Group members have similar 

aspirations for success

M 691 7.57 1.94

4.54 0.03*

F 150 8.07 1.42

Q4: If members had problems 

with a task, all wanted to help

M 691 7.52 2.01

0.00 0.98

F 150 7.69 1.77

Q5: Members communicated 

freely about responsibilities

M 691 7.70 1.89

2.82 0.09*

F 150 8.15 1.37

Composite Score (sum of Q1-Q5)

M 691 37.95 9.36

2.55 0.11

F 150 40.07 6.84
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The average values—by gender—reflect the differences we saw in the distribution of 

unit cohesion scores—females tend towards slightly more optimistic scores than males, 

though both are positive. 

Figure 18 - Perception of Unit Cohesion (by Gender) – 0811

N.4.11.3.2 Cohesion Results by Integration Level

In addition to looking at how unit cohesion scores compared between males and 

females, we also examined whether males’ cohesion responses remained consistent at 

different integration levels. For 0811s, we compared males’ responses in Control (i.e., 

all-male), Low-Density (i.e., 1 female), and High-Density (i.e., 2 females) Artillery 

Sections. We have unit cohesion survey results (five statements per survey) from 28 

males (28 males in the Control group, and 27 males in the Low-Density and HighDensity groups); statistical results are summarized in the table below (Table 95).
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Table 95 - Summary of Males' Unit Cohesion Scores (by Integration Level) - 0811

We found a statistical difference between the Control group and both integration levels 

(i.e., High-Density, and Low-Density groups) for all five cohesion statements, as well as 

for the overall composite cohesion score. We also saw mixed results between HighDensity and Low-Density groups; significant for “Q1-Unity”, “Q2-Responsibility”, and 

“Q3-Aspirations”, but not for the other two statements, nor the overall composite score. 

When we looked at the distributions of each question, we see very similar patterns—the 

majority of responses are heavily skewed to the far right (i.e., “9”, at Significantly 

Agree), and taper off relatively quickly to the left. Where the differences appear to come 

MOS Cohesion IL N 

(scores) Mean SD χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

0811

Q1: Group was united in 

trying to reach goals

C 256 7.95 1.90

33.49 <0.01*

(LD-C)

-3.20 <0.01*

LD 223 7.57 1.84 (HD-C)

-5.81 <0.01*

HD 212 7.18 1.95 (HD-LD)

-2.47 0.01*

Q2: We all take 

responsibility for task 

success of the group

C 256 7.95 1.88

34.56 <0.01*

(LD-C)

-3.06 <0.01*

LD 223 7.55 1.89 (HD-C)

-5.96 <0.01*

HD 212 7.17 1.96 (HD-LD)

-2.59 0.01*

Q3: Group members have 

similar aspirations for 

success

C 256 7.93 1.89

27.68 <0.01*

(LD-C)

-3.27 <0.01*

LD 223 7.45 1.96 (HD-C)

-5.30 <0.01*

HD 212 7.25 1.94 (HD-LD)

-1.63 0.10

Q4: If members had 

problems with a task, all 

wanted to help

C 256 7.85 2.01

27.98 <0.01*

(LD-C)

-2.95 <0.01*

LD 223 7.44 2.03 (HD-C)

-5.37 <0.01*

HD 212 7.19 1.94 (HD-LD)

-2.07 0.04

Q5: Members 

communicated freely about 

responsibilities

C 256 8.00 1.90

26.92 <0.01*

(LD-C)

-3.27 <0.01*

LD 223 7.61 1.89 (HD-C)

-5.17 <0.01*

HD 212 7.42 1.83 (HD-LD)

-1.67 0.10

Composite Score 

(sum of Q1-Q5)

Lowest: 5 | Highest 45

C 256 39.68 9.40

34.49 <0.01*

(LD-C)

-3.71 <0.01*

LD 223 37.61 1.89 (HD-C)

-5.87 <0.01*

HD 212 36.22 9.06 (HD-LD)

-1.96 0.05
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in is the “thickness” within the middle ranges (i.e., “7” to “3”) that appears to get slightly 

more pronounced with integration density. The High-Density group is also slightly more 

likely to have some of the lowest scores, “1” or “2” (4% to 5%). 

We also graphed the means for each statement as a percentage of how strongly the 

volunteers agreed (positive) or disagreed (negative) with each question’s statement 

(Figure 19). The average values (by integration level) shown are consistent with what 

we saw with regards to males’ somewhat higher perceptions of unit cohesion within the 

Control group, along with the easy decline in their perception of cohesion when in the 

Low- and High-Density groups. 

Unfortunately, the survey did not provide for reasons as to why males were more likely 

to choose lower cohesion scores when in an integrated group, although given the fast 

pace and relatively locked-in responsibilities-by-billet, anyone weaker in key skills might 

well create an more negative group dynamic. 

Since the scenario did not allow for much compensation or collaboration between group 

members, it wouldn’t be too surprising for deficits in skill/deficits in empathy with such 

struggles to translate (for some) into lack of motivation and/or unity. 

Incidentally, males’ perceptions in the integrated units are a bit more depressed 

compared to how females perceived unit cohesiveness in the integrated units.

Figure 19 - Males' Perception of Unit Cohesion (by Integration Level) - 0811

N.4.12 LAV Crewman (0313)

N.4.12.1 Fatigue Results

For the 0313 volunteers at Twentynine Palms, we have baseline and final fatigue selfreports from 14 males and seven females. Because fatigue survey responses were 
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ordinal in nature, we restricted our statistical analysis to the non-parametric KruskalWallis (rank sum) test to check for significance between factors, using the criteria of p ≤ 

0.10 for statistical significance (*). Where we had more than two groups to compare—

and if the Kruskal-Wallis test showed significance for similarity—then we conducted 

Wilcoxon pairwise comparisons (using p<0.033 to adjust for multiple comparisons). 

N.4.12.1.1 Fatigue Results by Gender

We first looked at how fatigue self-reports compared between males and females, 

including their baseline (pre-trial) and final (post-trial, for both days in the run-cycle) 

fatigue levels. Results are summarized in the table below (Table 96). 

Table 96 - Summary of Pre-Trial and Final Fatigue Scores (by Gender) - 0313

N.4.12.1.1.1 Pre-Trial Fatigue Scores (by Gender)

We found a significant difference between female and male 0313 volunteers’ pre-trial 

fatigue scores, with males more likely than females to report being a bit less fatigued. 

The males’ primary responses were “1-Fully Alert” (52.7%), with “2-Very Lively” (32.4%) 

a strong second; this pattern was flipped for females (33.3% and 51.5%, respectively) 

(Table 97). 

However, given the closeness in verbiage between “1-Fully Alert” and “2-Very Lively”—

and that for both genders these two levels encompass approximately 85% of all 

scores—this difference doesn’t reflect any practical difference. From this, we conclude 

that all 0313 Marines had sufficient recovery time between trials, with no discernable 

decrease over time. 

N.4.12.1.1.2 Final Fatigue Scores (by Gender)

In looking at the volunteers’ post-trial responses, we found mixed results: we found no 

significant difference in scores for non-live fire (i.e., Maintenance) trials (p=0.45), but a 

significant difference for live-fire trials (p=0.07). On the face of it, these results seem 

somewhat counter-intuitive. The Non-Live Fire scenario contained a number of 

physically demanding tasks, including evacuation of a 204-lb, combat-loaded test 

dummy from the Vehicle Commander’s station, as well as the removal and remounting 

of scout hatch and side-armor panels and the spare tire assembly. 

MOS Fatigue Location / Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

0313

Baseline 

(Pre-Trial) 29Palms/1,2

M 336 1 / 1

11.5 <0.01*

F 165 2 / 2

Final

(Post-Trial)

29Palms/1 

“Non-Live Fire” 

M 171 2 /1

0.56 0.45

F 84 2 / 2

29Palms/2 

“Live-Fire”

M 165 2 / 1

3.29 0.07*

F 81 2 / 2
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However, with the exception the CASEVAC event (which was conducted by the Gunner 

and Driver), all of the Non-Live Fire scenario tasks were conducted by the entire LAV 

crew, whereas the Live-Fire scenario (which had some physically demanding tasks 

associated with prepping the vehicle for combat) required many of the tasks to be 

completed by a single Marine (often the Gunner). As such, the Live-Fire scenario 

provided much less opportunity for compensation across the trial by crewmembers who 

might otherwise struggle. 

In either event, the difference in distributions for the Live-Fire trials between males and 

females mirrors the pattern seen with pre-trial results: males predominately reported a 

final fatigue score of “1-Fully Alert” (49.1%) followed by “2-Very Lively” (33.9%); and 

females predominately reported “2-Very Lively” (50.6%) followed by “1-Very Lively” 

(33.3%). We saw little to no representation in the highest levels (“5-Moderately Tired”, 

“6-Extremely Tired”, or “Exhausted”) for either gender. This suggests that—despite the 

statistical difference between the genders for the Live-Fire trials—0313 Marines of 

either sex were not greatly fatigued by either scenario32. 

Table 97 - Pre-Trial and Final Fatigue Score Distributions (by Gender) - 0313

N.4.12.1.2 Fatigue Results by Integration Level

Next, we looked at whether males fatigue responses remained consistent at different 

integration levels. For 0313s, we compared males’ responses in Control (i.e., all-male) 

versus Low-Density (i.e., 1 female) and High-Density (i.e., 2 females) crews. We have 

 

32 The 0313 Scheme of Maneuver for the Live-Fire scenario rarely permitted administering a fatigue survey 

immediately after the conclusion of the last task, Engaging Offensive Targets. LAV crewmembers had to transit off 

of the range, and the time from the end of the last task to the start of the surveys could vary from as short at 5 

minutes to as long as an hour or more (average time was 29 minutes). Delays between completion of a trial and 

taking the survey could have muted perceptions of fatigue, as Marines had time to recover from their exertions.
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final fatigue self-reports from 14 males in Control and Low-Density groups, and five 

males in High-Density groups33; statistical results are summarized in the table below 

summarized in the table below (Table 98). 

Table 98 – Summary of Males’ Final Fatigue Scores (by Integration Level) - 0313

N.4.12.1.2.1 Final Fatigue Scores (by Integration Level)

Post-trial fatigue results by Integration Level proved to be mixed. For the Non-Live Fire 

scenario trials, the males’ less-fatigued responses in the High-Density group were

significantly differed from the Control group (p<0.01), but not the Low-Density group 

(p=0.96); there was also a significant difference between the distribution of responses 

for between the Low-Density and High-Density groups (p=0.02). We found no significant 

difference in males’ responses found between any of the groups for the Live-Fire 

scenario trials.

This is consistent with the difference in degrees of compensation permitted by the two 

scenarios. For example, most tasks in the Non-Live Fire scenario were conducted by 

the entire crew (allowing many opportunities for assistance to occur), whereas the LiveFire scenario restricted the conduct of most tasks to one (or perhaps two) 

crewmembers, without allowing for much assistance between volunteers. 

As we saw with previous results for this MOS, males final fatigue scores remained 

heavily clustered in the lowest two levels: “1-Fully Alert” and “2-Very Alert”, regardless 

of Integration Level. This was especially so for the Live-Fire scenario (Table 99). When 

participating in integrated crews, we see more males reporting the mid-range scores of 

“3-Okay” and sometimes “4-A Little Tired”, which suggests some males may have been 

 

33 The Vehicle Commander billet in all groups was always filled by a male 0313; only the Driver and Gunner billets 

could be filled by either sex.

MOS Fatigue Location / Day IL N 

(scores)

Median 

/ Mode

χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

0313 Final

(Post-Trial)

29Palms/1 

“Non-Live Fire” 

C 87 2 / 1

7.98 0.02*

(LD-C) 

0.05 0.96

LD 56 2 / 1 (HD-C) 

2.73 <0.01*

HD 28 2 / 2 (HD-LD)

2.41 0.02*

29Palms/2 

“Live-Fire”

C 84 1 / 1

2.77 0.25

(LD-C)

0.96 0.34

LD 54 2 / 1 (HD-C) 

1.57 0.12

HD 27 2 / 1 (HD-LD)

0.82 0.41
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working a little bit harder in the integrated groups, especially when conducting 

maintenance tasks. 

Table 99 – Males’ Final Fatigue Score Distributions (by Integration Level) - 0313

N.4.12.2 Workload Results 

For the 0313 volunteers at Twentynine Palms, we have maximum workload self-reports 

from 14 males and seven females. Because workload survey responses were ordinal in 

nature, we restricted our statistical analysis to the non-parametric Kruskal-Wallis (rank 

sum) test to check for significance between factors, using the criteria of p ≤ 0.10 for 

statistical significance (*). Where we had more than two groups to compare—and if the 

Kruskal-Wallis test showed significance for similarity—then we conducted Wilcoxon 

pairwise comparisons (using p<0.033 to adjust for multiple comparisons).

N.4.12.2.1 Workload Results by Gender

We first looked at how maximum workload self-reports compared between males and 

females. Results are summarized in the table below (Table 100). 

Table 100 - Summary of Max Workload Scores (by Gender) – 0313

We did not a find a significant difference between female and male 0313 volunteers’ 

maximum workload scores for either day in their run-cycle (i.e., Non-Live Fire and LiveMOS Workload Location / Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

0313

Max 

Workload for 

Trial

29Palms/1 

“Non-Live Fire” 

M 171 3 / 3 0.01 0.92

F 84 3 / 3

29Palms/2

“Live-Fire” 

M 169 3 / 3 2.56 0.44

F 83 3 / 3
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Fire). For both groups, we saw max workload scores heavily clustered at “3-Active but 

Easy”, with a secondary peak at “4-Challenging”. 

Table 101 - Max Workload Score Distributions (by Gender) - 0313

We saw no reports—from either gender—at the highest workload levels (i.e., “6-

Overloaded” and “7-Unmanageable”). This suggests all Marines felt capable of 

accomplishing (if not always easily) the workload assigned them.

N.4.12.2.2 Workload Results by Integration Level

In addition to looking at how maximum workload self-reports compared between males 

and females, we also examined whether males’ responses remained consistent at 

different integration levels. For 0811s, we compared males’ responses in Control (i.e., 

all-male), Low-Density (i.e., 1 female), and High-Density (i.e., 2 females) LAV crews. 

We have max workload self-reports from 14 males (14 males in the Control and LowDensity groups, and five males in the High-Density group); statistical results are 

summarized in the table below (Table 102). 

Table 102 - Summary of Males’ Max Workload Scores (by Integration Level) – 0313

We found mixed results when we looked at males’ max workload responses by 

Integration Level. For Non-Live Fire trials, we saw a significant difference between 

MOS Workload Location / Day IL N 

(scores)

Median

/ Mode

χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test 

p-Value

0313

Max 

Workload 

for Trial

29Palms/1 

“Non-Live Fire” 

C 87 3 / 3

10.7 <0.01*

(LD-C)

2.3 0.02*

LD 56 3 / 3 (HD-C)

3.1 <0.01*

HD 28 3.5 / 3 (HD-LD)

-0.12 0.91

29Palms/2

“Live-Fire” 

C 87 3 / 3

LD 54 3 / 3 1.8 0.40

HD 28 3 / 3
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Control and Integrated groups, but none at all for Live-Fire trials. When we look at the 

scores males reported between (Table 103), we see that males’ in integrated groups 

(for Non-Live Fire trials) show a shift towards higher maximum workloads—in particular 

a shift upward from “3-Active by Easy” to “4-Challenging”. A similar pattern appears like 

it might be emerging for Live-Fire trials—though it’s less pronounced, as well as 

countering, and (very) slight, rise in scores at “2-Little to Do” such that the pattern is not 

significant. 

Table 103 - Males’ Max Workload Score Distributions (by Integration Level) – 0313

As for possible mechanisms, it may be that males’ in integrated groups are required to 

take on a larger workload during the Non-Live Fire scenario, at least one task (if not 

more). The lack of a difference for Live-Fire trials may be a function of the difference in 

degrees of compensation permitted by the two scenarios. For example, most tasks in 

the Non-Live Fire scenario were conducted by the entire crew (allowing many 

opportunities for assistance to occur), whereas the Live-Fire scenario restricted the 

conduct of most tasks to one (or perhaps two) crewmembers, without allowing for much 

assistance between volunteers. 

N.4.12.3 Cohesion Results

For the 0313 volunteers at Twentynine Palms, we have Unit Cohesion survey results 

(five statements per survey) from 14 males and seven females. Cohesion responses for 

each statement were set on a nine-point, Likert scale (one indicating “Strongly 

Disagree” and nine indicating “Strongly Agree”). 

Because the cohesion responses consistently violated the normality and independence 

assumptions for parametric data, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). Where we had more than two 

groups to compare—and if the Kruskal-Wallis test showed significance for similarity—
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then we conducted Wilcoxon pairwise comparisons (using p<0.033 to adjust for multiple 

comparisons).

N.4.12.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five responses, which scaled between 5 and 45)—compared between 

males and females, following the conclusion of their unit’s run-cycle. Statistical results

are summarized in the table below (Table 104).

Table 104 - Summary of Unit Cohesion Scores (by Gender) - 0313

We found a significant difference between 0313 males and females for all five cohesion 

statements (“Q1-Unity”, “Q2-Responsibility”, “Q3-Aspirations”, “Q4-Help” and “Q5-

Comm”), as well as for the overall composite cohesion score. When we look more 

closely at the distribution of responses for each statement, we see that females tended 

to a bit more optimistic (i.e., higher scores) than males. 

For all five questions, female responses peak most sharply at “9” (70.4% to 77.8%)—

compared to what we see among males (56.7% to 61.6%)—and then taper off sharply 

with virtually no responses below “5”. Males, on the other hand, also peak at “9” (but not 

as high) before tapering off less sharply unit popping up again in a small, secondary 

peak (10.4% to 12.2%) at level “5”. We see virtually no responses—for either gender—

below “5”.

We also graphed the means for each survey statement as a percentage of how strongly 

the volunteers agreed (positive) or disagreed (negative) with each survey statement 

(Figure 20). Consistent with what we saw in the distributions of responses, we see that 

females tend to be more optimistic about their units’ cohesion than males—across the 

board—although both are strongly positive. 

MOS Location Cohesion Gender N 

(scores) Mean SD χ2 

Statistic

χ2 pValue

0313 29Palms

Q1: Group was united in trying 

to reach goals

M 164 8.04 1.45

7.74 <0.01*

F 81 8.57 1.01

Q2: We all take responsibility for 

task success of the group

M 164 8.12 1.33

6.21 0.01*

F 81 8.47 1.25

Q3: Group members have similar 

aspirations for success

M 164 8.18 1.32

7.88 <0.01*

F 81 8.62 0.86

Q4: If members had problems 

with a task, all wanted to help

M 164 8.15 1.35

3.35 0.07*

F 81 8.49 1.06

Q5: Members communicated 

freely about responsibilities

M 164 8.10 1.38

4.47 0.03*

F 81 8.42 1.18

Composite Score (sum of Q1-Q5)

M 164 40.60 6.55

3.84 0.05*

F 81 42.57 5.12
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Figure 20 - Perception of Unit Cohesion (by Gender) – 0313

N.4.12.3.2 Cohesion Results by Integration Level

In addition to looking at how unit cohesion scores compared between males and 

females, we also examined whether males’ cohesion responses remained consistent at 

different integration levels. For 0313s, we compared males’ responses in Control (i.e., 

all-male), Low-Density (i.e., 1 female), and High-Density (i.e., 2 females) LAV crews.

We have unit cohesion survey results (five statements per survey) from 14 males (14 

males in the Control and Low-Density groups, and five males in the High-Density 

group); statistical results are summarized in the table below (Table 105).
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Table 105 - Summary of Males' Unit Cohesion Scores (by Integration) - 0313

We found a statistical difference between the Control group and the High-Density group, 

but not between the other two pairings, for all five cohesion statements, as well as for 

the overall composite cohesion score. 

When we looked at the distributions of each question, we see very similar patterns—the 

majority of responses are heavily skewed to the far right (i.e., “9”, at Significantly 

Agree), and taper off abruptly, with a broad, shallow span (of different thicknesses) in 

the middle range (i.e., “7” to “5”). The Control group has relatively low levels of 

responses in the middle range (1% to 7%), which get progressively more pronounced 

MOS Cohesion IL N 

(scores) Mean SD χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

0313

Q1: Group was united in 

trying to reach goals

C 83 8.35 1.31

13.97 <0.01*

(LD-C)

-1.66 0.10

LD 54 7.93 1.48 (HD-C)

-3.80 <0.01*

HD 27 7.33 1.54 (HD-LD)

-1.99 0.05

Q2: We all take 

responsibility for task 

success of the group

C 83 8.43 1.05

10.68 <0.01*

(LD-C)

-1.53 0.13

LD 54 7.98 1.47 (HD-C)

-3.30 <0.01*

HD 27 7.44 1.58 (HD-LD)

-1.71 0.09

Q3: Group members have 

similar aspirations for 

success

C 83 8.43 1.15

10.96 <0.01*

(LD-C)

-1.82 0.07

LD 54 8.09 1.35 (HD-C)

-3.24 <0.01*

HD 27 7.59 1.55 (HD-LD)

-1.63 0.10

Q4: If members had 

problems with a task, all 

wanted to help

C 83 8.41 1.09

6.84 0.03*

(LD-C)

-0.80 0.42

LD 54 8.07 1.48 (HD-C)

-2.68 <0.01*

HD 27 7.52 1.63 (HD-LD)

-1.65 0.10

Q5: Members 

communicated freely about 

responsibilities

C 83 8.40 1.11

8.39 0.02*

(LD-C)

-1.68 0.09

LD 54 7.96 1.47 (HD-C)

-2.79 <0.01*

HD 27 7.44 1.69 (HD-LD)

-1.34 0.18

Composite Score 

(sum of Q1-Q5)

Lowest: 5 | Highest 45

C 83 42.02 5.42

11.06 <0.01*

(LD-C)

-1.77 0.08

LD 54 40.04 6.98 (HD-C)

-3.30 <0.01*

HD 27 37.33 7.68 (HD-LD)

-1.65 0.10
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with the density level (i.e., 4%-17% for Low-Density groups, and 7% to 26% for HighDensity groups). 

We also graphed the means for each statement as a percentage of how strongly the 

volunteers agreed (positive) or disagreed (negative) with each question’s statement 

(Figure 21). The average values (by integration level) shown are consistent with what 

we saw with regards to males’ relatively high perceptions of unit cohesion within the 

Control group, along with the easy decline in their perception of cohesion when in the 

Low- and High-Density groups.

Unfortunately, the survey did not provide for reasons as to why males were more likely 

to choose lower cohesion scores when in an integrated group. The number of 

responses per Integration Level is not ideal (27 and 54, for High- and Low-Density 

groups, respectively). For that reason, we should be a bit cautious in extrapolating these 

results to the larger 0313 community. 

Figure 21 - Males' Perception of Unit Cohesion (by IL) – 0313

We also can’t rule it out to potential for differences in experience to play a role in the 

reduced cohesion perceptions by males in integrated groups. Incidentally, the average 

values for the integrated groups appear to be quite different from how females 

perceived unit cohesion. 

N.4.13 M1A1 Tank Crewman (MOS 1812)

N.4.13.1 Fatigue Results

For the 1812 volunteers at Twentynine Palms, we have baseline and final fatigue selfreports from 16 males and three females. Because fatigue survey responses were 

ordinal in nature, we restricted our statistical analysis to the non-parametric Kruskal-
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Wallis (rank sum) test to check for significance between factors, using the criteria of p ≤ 

0.10 for statistical significance (*). 

N.4.13.1.1 Fatigue Results by Gender

We first looked at how fatigue self-reports compared between males and females, 

including their baseline (pre-trial) and final (post-trial, for both days in the run-cycle) 

fatigue levels. Results are summarized in the table below (Table 106). 

Table 106 - Summary of Pre-Trial, Mid-Trial, and Final Fatigue Scores (by Gender) - 1812

N.4.13.1.1.1 Pre-Trial Fatigue Scores (by Gender)

We did not find a significant difference between female and male 1812 volunteers’ pretrial fatigue scores—a result consistent the strong peaks at “2-Very Lively” for both 

genders (Table 107), with nearly all responses at level “3-Okay” or below (94.4% for 

males, 91.7% for females). 

We found only a very small fraction of responses—only 1.1 percent for males (driven 

largely by one male) and 2.8 percent for females (a single response each by two 

Marines)—at the “5-Moderately Tired” level, with none at “6-Extremely Tired” or “7-

Exhausted”. Combined with the lack of any obvious pattern of increasing scores over 

time suggests that 1812 volunteers had sufficient recovery time between trials. 

N.4.13.1.1.2 Final Fatigue Scores

In looking at the volunteers’ post-trial responses, we found no significant differences for 

either the Non-Live Fire scenario trials or the Live-Fire scenario trials. Both males and 

females showed the same strong peak at “2-Very Lively”, with most other responses 

falling at “1-Fully Alert” or “3-Okay”, for both days. 

 

34 The 1812 trials at Twentynine Palms shared space at Range 500 with 0313 (LAV) and 1833 (AAV) trials. As a 

results, the three MOS operated on a three-day cycle, where each individual MOS had one non-live fire day, one 

live-fire day, and one day devoted to general maintenance on the vehicles (non-trial). For 1812s, their trial days 

were Day 2 (non-live fire) and Day 3 (live-fire) of this cycle.

MOS Fatigue Location / 

Day34 Gender N Median / 

Mode χ2 Statistic χ2 p-Value

1812

Baseline 

(Pre-Trial) 29Palms/2,3

M 356 2 / 2

0.24 0.62

F 72 2 / 2

Final

(Post-Trial)

29Palms/2

“Non-Live Fire” 

M 178 2 / 2

0.28 0.60

F 35 2 / 2

29Palms/3

“Live-Fire”

M 180 2 / 2

0.01 0.91

F 36 2 / 2
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Table 107 - Pre-Trial, Mid-Trial, and Final Fatigue Score Distributions (by Gender) - 0812

N.4.13.1.2 Fatigue Results by Integration Level

Next, we looked at whether males fatigue responses remained consistent at different 

integration levels. For 1812s, we compared males’ responses in Control (i.e., all-male) 

and Low-Density (i.e., 1 female) Tank crews, where females might be in one of two 

billets (Driver or Loader)35. We have final fatigue self-reports from 16 males; statistical 

results are summarized in the table below (Table 108). 

Table 108 – Summary of Males’ Mid-Trial and Final Fatigue Scores (by Integration Level) - 1812

N.4.13.1.2.1 Final Fatigue Scores (by Integration Level)

Post-trial fatigue results by Integration Level were not significantly different for either 

trial scenario. In keeping with the distribution of fatigue scores seen in the “by gender” 

results above, males largely reported fatigue levels at “2-Very Lively” with clustering just 

above and below (i.e., “1-Fully Alert” and “3-Okay”) at the end of each day’s trial.

The 1812 Scheme of Maneuver (SoM) incorporated a combination of both crew-level 

(e.g., Remove/Replace Track Section, Crew Evacuation, Evacuate Wounded Crewman, 

Conduct Vehicle Recovery, Conduct Ammo Resupply, and Transfer Ammunition) and 

 

35 The third billet in the three-man crews—Tank Gunner—could only be filled by a Marine experienced in the MOS; 

as such, this billet was filled by all-male volunteers only.

MOS Fatigue Location / Day IL N 

(scores)

Median 

/ Mode

χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

1812 Final

(Post-Trial)

29Palms/2

“Non-Live Fire” 

C 108 2 / 2

0.02 0.89 (LD-C)

-0.14 0.89

LD 70 2 / 2

29Palms/3

“Live-Fire”

C 108 2 / 2

0.27 0.60 (LD-C)

0.52 0.61

LD 72 2 / 2
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individual-level tasks (Arm Main Gun, Manipulate Turret, Prep/Reload Commander’s 

Weapon Station, and Engage Defensive/Offensive Targets36) (see Annex I). 

Crew-level tasks could (notionally) have provided opportunities for males to compensate 

for females in integrated crews (e.g., share, or swap duties)— making them more 

tired—whereas individual-level tasks prohibit such compensation, but might have

revealed differences by gender if females were taxed more heavily by specific tasks 

(perhaps allowing additional recovery for non-participants). We found no indication of 

either condition. 

While the mixed nature of the 1812 SoM—with interspersed crew- and individual-level 

tasks—might have masked some low-level compensation or task-specific fatigue effects 

for this MOS, the fact that both male and female Marines persistently reported lower 

fatigue levels (“3-Okay” or below), such effects—if they exist—are likely short-lived and 

minor. 

Table 109 – Males’ Final Fatigue Score Distributions (by Integration Level) - 1812

N.4.13.2 Workload Results

For the 1812 volunteers at Twentynine Palms, we have max workload self-reports from 

16 males and three females. Because workload survey responses were ordinal in 

nature, we restricted our statistical analysis to the non-parametric Kruskal-Wallis (rank 

sum) test to check for significance between factors, using the criteria of p ≤ 0.10 for 

statistical significance (*). 

N.4.13.2.1 Workload Results by Gender

We first looked at how maximum workload self-reports compared between males and 

females. Results are summarized in the table below (Table 110). 

 

36 While the entire crew is involved in engaging targets, the bulk of the physical activity falls on the Loader.
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Table 110 - Summary of Max Workload Scores (by Gender) – 1812

We found a significant difference between female and male 1812 volunteers’ maximum 

workload scores for both days in their run-cycle (i.e., Non-Live Fire and Live-Fire). Both 

groups strongly favored maximum workload responses at “3-Active but Easy” (73% for 

males, and 60.0% for females) for the Live-Fire scenario, but females were a bit more 

likely to have some responses at “4-Challenging” and less likely to have some at “2-

Little to Do” or lower (Table 111). 

Table 111 - Max Workload Score Distributions (by Gender) - 1812

Because there were a number tasks for the 1812 Scheme of Maneuver that were only 

done by particular billets—and because only males could be Tank Gunners—we also 

checked to see whether we still saw a significant difference between the two groups 

when we only compared Marines in the Tank Driver and Tank Loader positions—we 

did.

It’s also possible that the difference between the two groups may be due to females 

having less time in the MOS; if so, we would expect the difference between the two 

groups to gradually disappear over time as they became more skilled. Its unlikely 

fatigue played a role, as we did not see any difference between males and females. 

MOS Workload Location / Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

1812

Max 

Workload for 

Trial

29Palms/2

“Non-Live Fire” 

M 180 3 / 3

9.3 <0.01*

F 36 4 / 4

29Palms/3

“Live-Fire”

M 178 3 / 3

11.2 <0.01*

F 35 3 / 3
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N.4.13.2.2 Workload Results by Integration Level

In addition to looking at how maximum workload self-reports compared between males 

and females, we also examined whether males’ responses remained consistent at 

different integration levels. For 1812s, we compared males’ responses in Control (i.e., 

all-male) and Low-Density (i.e., 1 females) Tank crews. We have max workload selfreports from 16 males; statistical results are summarized in the table below (Table 112). 

Table 112 - Summary of Males’ Max Workload Scores (by Integration Level) – 1812

We found mixed results when we looked at males’ max workload responses by 

Integration Level. For Live-Fire trials, we saw a significant difference between LowDensity and Control groups, but not no difference for Non-Live Fire trials. These results 

are somewhat counter-intuitive, at first look. Of the two scenarios, the non-live fire 

scenario would seem the most conducive towards compensation in a crew’s division of 

work. 

However, when we look more closely at the scores reported (Table 113), we can see a 

small number of scores at “1-No Demands” among Control groups and a score at “7-

Unmanageable” in the Low-Density group. Because the non-parametric test we used 

(Kruskal-Wallis) looks at the ranking order of groups, these scores at the extrema (and 

in opposite directions for the two groups)—while relatively tiny—could be driving the 

significant difference conclusion.

Table 113 - Males’ Max Workload Score Distributions (by Integration Level) – 1812

MOS Workload Location / Day IL N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

1812

Max 

Workload for 

Trial

29Palms/2

“Non-Live Fire” 

C 108 3 / 3 2.0 0.15

LD 72 3 / 3

29Palms/3

“Live Fire”

C 107 3 / 3 4.0 0.05*

LD 71 3 / 3
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Indeed, if we were to exclude just the four responses found at “1-No Demands” for LiveFire trials (contributed by four different Marines in the Tank Gunner or Tank Driver 

billets during the first week of the study), we find that there is no longer a significant 

difference between Control and Low-Density groups for either day (χ2 = 2.3, p=0.13). 

This certainly makes any determination that a real difference exists in males’ workload 

perceptions, based upon Integration Level, highly suspect—especially when we did not 

see a difference during the Non-Live Fire scenario where compensation would be more 

plausible (based on the Scheme of Maneuver). 

N.4.13.3 Cohesion Results

For the 1812 volunteers at Twentynine Palms, we have Unit Cohesion survey results 

(five statements per survey) from 16 males and three females. Cohesion responses for 

each statement were set on a nine-point, Likert scale (one indicating “Strongly 

Disagree” and nine indicating “Strongly Agree”). 

Because the cohesion responses consistently violated the normality and independence 

assumptions for parametric data, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). 

N.4.13.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five responses, which scaled between 5 and 45)—compared between 

males and females, following the conclusion of their unit’s run-cycle. Statistical results

are summarized in the table below (Table 114).

Table 114 - Summary of Unit Cohesion Scores (by Gender) - 1812

MOS Location Cohesion Gender N 

(scores) Mean SD χ2 

Statistic

χ2 pValue

1812 29Palms

Q1: Group was united in trying 

to reach goals

M 162 8.33 0.90

3.72 0.05*

F 33 8.64 0.65

Q2: We all take responsibility for 

task success of the group

M 162 8.31 1.00

0.47 0.49

F 33 8.52 0.67

Q3: Group members have similar 

aspirations for success

M 162 8.29 1.06

1.83 0.18

F 33 8.61 0.61

Q4: If members had problems 

with a task, all wanted to help

M 162 8.31 0.89

3.34 0.07*

F 33 8.58 0.79

Q5: Members communicated 

freely about responsibilities

M 162 8.35 0.89

0.89 0.35

F 33 8.48 0.83

Composite Score (sum of Q1-Q5)

M 162 41.59 4.12

2.49 0.11

F 33 42.82 3.02
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We found a significant difference between 1812 males and females for only two of the 

five cohesion statements (“Q1-Unity” and “Q4-Help”), and no difference for the overall 

composite cohesion score (although the latter is borderline). When we look more closely 

at the distribution of responses for each statement, we see that females tended to a bit 

more optimistic (i.e., higher scores) than males. 

For the two questions where we see a significant difference, we see that females 

strongly and consistently report cohesion scores in the top two levels (90.0% and 

87.9%, for “Q1-Unity” and “Q4-Help”, respectively). Males’ responses for these same 

two questions, on the other hand, are more broadly spread between “5” and “9”, though 

they, too, favor the highest two levels (84.6% and 80.9%, for “Q1-Unity” and “Q4-Help”, 

respectively). 

We also graphed the means for each survey statement as a percentage of how strongly 

the volunteers agreed (positive) or disagreed (negative) with each survey statement 

(Figure 22). The average values (by gender) reflect a consistently high perception of 

unit cohesion across the board among the 1812 volunteers, despite a very small 

percentage of responses among males that drive their responses a hair more 

pessimistic for two questions: “Q1-Unity” and “Q4-Help”. 

Figure 22 - Perception of Unit Cohesion (by Gender) – 1812

N.4.13.3.2 Cohesion Results by Integration Level

In addition to looking at how unit cohesion scores compared between males and 

females, we also examined whether males’ cohesion responses remained consistent at 

different integration levels. For 1812s, we compared males’ responses in Control (i.e., 

all-male) and Low-Density (i.e., 1 female) Tank crews. We have unit cohesion survey 

results (five statements per survey) from 16 males; statistical results are summarized in 

the table below (Table 115).
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Table 115 - Summary of Males' Unit Cohesion Scores (by Integration Level) - 1812

We found significant differences between the Control and both integrated groups (i.e., 

Low-Density and High-Density groups) for all five cohesion statements, as well as for 

the overall composite cohesion score. 

When we looked at the distributions of each question, we see very similar patterns—the 

majority of responses are heavily skewed to the far right (i.e., “9”, at Significantly Agree) 

that tapers off over a span of several levels. For the Control group, we see a bit more 

representation at the peak (63% to 66%), with a taper that drops off very quickly at “7”. 

On the other hand, the Low-Density group has a smaller peak (41% to 44%), and it 

spans a wider stretch (tapers off at “5” or “6”. 

We also graphed the means for each statement as a percentage of how strongly the 

volunteers agreed (positive) or disagreed (negative) with each question’s statement 

(Figure 23). The average values (by integration level) shown are consistent with what 

we saw with regards to males’ very higher perceptions of unit cohesion within the 

Control group, with fairly shallow dip to the Low-Density group’s average. 

MOS Cohesion IL N (scores) Mean SD χ2 Statistic χ2 p-Value

1812

Q1: Group was united in trying to 

reach goals

C 96 8.53 0.71

10.78 <0.01*

LD 66 8.03 1.05

Q2: We all take responsibility for 

task success of the group

C 96 8.50 0.83

9.15 <0.01*

LD 66 8.05 1.16

Q3: Group members have similar 

aspirations for success

C 96 8.46 0.93

8.44 <0.01*

LD 66 8.05 1.20

Q4: If members had problems with 

a task, all wanted to help

C 96 8.49 0.77

9.30 <0.01*

LD 66 8.05 0.98

Q5: Members communicated 

freely about responsibilities

C 96 8.52 0.78

8.97 <0.01*

LD 66 8.11 0.98

Composite Score 

(sum of Q1-Q5)

Lowest: 5 | Highest 45

C 96 42.50 3.45

11.04 <0.01*

LD 66 40.27 4.65
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Figure 23 - Males' Perception of Unit Cohesion (by Integration Level) - 1812

Unfortunately, the survey did not provide for reasons as to why males were more likely 

to choose lower cohesion scores when in an integrated group, but the difference in 

experience between males and females may have been a factor. We should also keep 

in mind that these are the result of a relatively small volunteer pool (16 Marines) and 

their experiences with only three females, who may or may not be representative for the 

larger 1812 community. 

Incidentally, these results differ a fair bit from how females rated their perception of unit 

cohesiveness in integrated groups—their results were more positive that males’ 

responses in an integrated group. Plus, with the small unit size, some of the males’

perceptions may have been colored by a different (vice a truly non-cohesive) group 

dynamic. 

N.4.14 AAV Crewman (MOS 1833)

N.4.14.1 Fatigue Results

For the 1833 volunteers, we have baseline and final fatigue self-reports from 17 males 

and 10 females (for Twentynine Palms), and 16 males and 10 females (for Pendleton). 

Because fatigue survey responses were ordinal in nature, we restricted our statistical 

analysis to the non-parametric Kruskal-Wallis (rank sum) test to check for significance 

between factors, using the criteria of p ≤ 0.10 for statistical significance (*). Where we 

had more than two groups to compare—and if the Kruskal-Wallis test showed 

significance for similarity—then we conducted Wilcoxon pairwise comparisons (using 

p<0.033 to adjust for multiple comparisons). 
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N.4.14.1.1 Fatigue Results by Gender

We first looked at how fatigue self-reports compared between males and females, 

including their baseline (pre-trial) and final (post-trial, for both days in the run-cycle at 

Twentynine Palms) fatigue levels. Statistical results are summarized in the table below 

(Table 116). 

Table 116 - Summary of Pre-Trial and Final Fatigue Scores (by Gender) - 1833

N.4.14.1.1.1 Pre-Trial Fatigue Scores (by Gender)

We found a significant difference between female and male 1833 volunteers’ pre-trial 

fatigue scores for Twentynine Palms, but not at Pendleton where the amphibious

portion was conducted. For the Twentynine Palms portions, females were slightly more 

likely to report pre-trial fatigue levels of “1-Fully Alert” or “Very Lively” (81%) compared 

to males (72.2%), and slightly less likely than males to report mid-range fatigue levels of 

“3-Okay” or “4-A Little Tired” (17.9% versus 22.5%). 

We found very few of the higher fatigue scores for either gender (i.e., “5-Moderately 

Tired”, “6-Extremely Tired”, “7-Exhausted) at Twentynine Palms—only 5.4 percent for 

males (driven overwhelmingly by one Marine), and 1.1 percent for females (also driven 

largely by one Marine)—and no obvious pattern of increasing scores over time, 

suggesting volunteers largely had sufficient recovery time between trials. 

At Pendleton, both genders favored pre-trial responses of “1-Fully Alert” to “3-Okay” 

(88.5% and 90.9%, for males and females respectively), with slightly higher (though still 

low) representation in the higher fatigue scores (10.1% and 10.4%)—both largely driven 

by the same two Marines driving the representation in this range for Twentynine Palms. 

The Pendleton results likewise suggest that most volunteers had sufficient recovery 

time between trials.

MOS Fatigue Location/ Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

1833

Baseline

(Pre-Trial)

29Palms/

1&3

M 485 2 / 1 

9.5 <0.01*

F 268 2 / 1

Final

(Post-Trial)

29Palms/1

“Live Fire”

M 238 2 / 2

0.71 0.40

F 129 2 / 2

29Palms/3

“Non-Live Fire”

M 244 2 / 2 

0.00 0.96

F 134 2 / 2

Baseline

(Pre-Trial)

Pendleton/1

“Amphib”

M 139 2 / 2

1.6 0.20

F 77 2 / 2

Final

(Post-Trial)

Pendleton/1

“Amphib”

M 139 2 / 2

5.6 0.02*

F 77 2 / 2
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As to why we see a gender difference at Twentynine Palms but not at Pendleton, it may 

be that the longer duration—and more austere living conditions—presented by the 

Twentynine Palms’ trials was a bit less conducive to recovery (or morale) for a sufficient 

sub-set of males to produce significance. When we look at who contributed to pre-trial 

scores of “4-A Little Tired” or higher (representing only 12% of male responses), we see 

that only eight of out of 17 Marines contributed responses in this range37. At the same 

time, all 17 male Marines did contribute at least some pre-trial scores to the lower range 

(“3-Okay” and below), which represent the majority of responses (88.0%). 

Conversely, when we look at the same fatigue range-split for females, we see that eight 

of 10 females contributed to their “4-A Little Tired” and higher range (representing only 6 

percent of responses), and all contributed to the lower “3-Okay” and below range—

representing a slightly higher overall percentage than males (94.0%). 

So, while we technically see a significant difference between males and females at 

Twentynine Palms, it appears that this may be due to periodic shifts to slightly higher 

fatigue levels by a sub-set of males—which could be influenced by a number of 

factors—rather than a substantial physiological difference. 

N.4.14.1.1.2 Final Fatigue Scores (by Gender)

In looking at the volunteers’ post-trial responses, we found mixed results (Table 116): 

we saw no significant difference post-trial between genders for either day at Twentynine 

Palms, but we did see a significant difference for Pendleton trials. 

At Pendleton, males most often reported post-trial scores of “2-Very Lively” or “1-Fully 

Alert” (69.1%), with a respectable percentage at “3-Okay” (14.4%). By comparison, 

females show a slightly flatter, more dispersed distribution with “2-Very Lively” or “Okay”

reported most often (59.7%), with respectable percentages split between “1-Fully Alert”

(14.3%) and “4-A Little Tired (15.6%). Both groups had comparable (and relatively 

small) representation at “5-Moderately Tired” and “6-Extremely Tired” (10.1 percent for 

males, 10.4% for females)—typically single responses by a handful of Marines. 

For Twentynine Palms, the distributions look very similar—clustering predominantly 

between “1-Fully Alert” and “3-Okay” with comparably small representation at “5-

Moderately Tired” or “6-Extremely Tired”—but without the statistical difference. 

As with the pre-trial results, we must ask why—when the gross shape of male versus 

female distribution curves appear so similar and at levels suggesting most Marines 

(most of the time) had energy remaining by the end of a trial—we see a significant 

 

37 When we look at the same split for females, we see that eight of 10 females contributed to the “4-Okay” and 

higher range (representing only 6 percent of responses), and 
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difference at one site but not the other, and whether that difference is operationally 

relevant and repeatable. 

On the face of it, there were certainly a number of physically demanding elements in the 

Pendleton trials (e.g., lifting the dummy in the water CASEVAC, moving and securing 

the tie-down chains). However, it’s hard to see these being that much harder than the 

physical elements found during the Twentynine Palms trials (e.g., lifting the dummy in 

the turret CASEVAC, moving ammo, breaking track, mounting the M2 and Mk19 

weapon systems) to warrant Pendleton being significant where Twentynine Palms was 

not. Indeed, the gross shapes of the fatigue distributions for both locations are 

remarkably similar. 

When we looked at the range of responses an individual Marine reported at Pendleton

post-trial, we found that 80 percent of females, and 50 percent of males reported within 

a range covering three levels or more (e.g., 1 to 4, 2 to 4, 2 to 6)—despite conducting 

only the single scenario (i.e., amphibious ops). There was even greater variability at 

Twentynine Palms (90% of females and 65% of males had a response range of three or 

greater). 

With this degree of variability within the same individuals from day-to-day—which may 

have been influenced by a number of factors including billet, weather, group dynamic, 

and morale—it’s seems less likely that the statistically significant (but hardly 

operationally distinguishable) difference seen between genders at Pendleton was a real 

physiological difference, and more the result of relatively small number of subjects, a 

fewer number of trials, and their high inter-subject variability. 
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Table 117 - Pre-Trial and Final Fatigue Score Distributions (by Gender) - 1833

N.4.14.1.2 Fatigue Results by Integration Level

Next, we looked at whether males fatigue responses remained consistent at different 

integration levels. For 1833s, we compared males’ responses in Control (i.e., all-male), 

Low-Density (i.e., 1 female), and High-Density (i.e., 2 females) AAV crews. We have 

final fatigue self-reports from 17 males for Twentynine Palms, and 16 males for 

Pendleton; statistical results are summarized in the table below (Table 118).
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Table 118 – Summary of Males’ Final Fatigue Scores (by Integration Level) - 1833

N.4.14.1.2.1 Final Fatigue Scores (by Integration Level)

For 1833s, we did not see any significant difference in post-trial fatigue results based on

Integration Level for any of the three trial scenarios (Twentynine Palms’ Live-Fire and 

Non-Live Fire, and Pendleton’s Amphibious Ops). Across all integration levels and 

locations, we see males’ responses clustering among the three lowest levels (ranging 

between 63.0% and 93.2%) and peaking at “2-Very Lively”. 

However, we do see some borderline statistical results for Pendleton in High-Density 

units, compared to Control and Low-Density crews. This is likely due to the presence of 

a second, substantial peak at “5-Moderately Tired” (29.6%). When we look more closely 

at these responses, we see that most (69%) were from two Marines that had reported 

the same level of fatigue in their pre-trial survey (i.e., “5-Moderately Tired”)—i.e., they 

were just as tired after the trial as they had when they’d started. 

In addition, as we examined their history of responses over the course of the study, we 

found that both persistently reported moderate-to-high levels (“4-Okay” to “7-

Exhausted”) of pre-trial fatigue at both Twentynine Palms and Pendleton (71.0%). At the 

same time, they also consistently reported (79% of the time) the exact same (or one 

higher) post-trial fatigue level, regardless of the integration level of their unit. This

suggests that this second peak—and the resulting borderline statistical result—is not a 

function of Integration Level, but more a characteristic of two male Marines.

MOS Fatigue Location / Day IL N Median 

/ Mode

χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test 

p-Value

1833

Final

(Post-Trial)

29Palms/1

“Live-Fire” 

C 110 2 / 2

1.3 0.52

(LD-C)

0.05 0.96

LD 84 2 / 2 (HD-C)

-1.1 0.29

HD 44 2 / 1 (HD-LD)

-1.0 0.30

29Palms/3

“Non-Live Fire”

C 114 2 / 2

1.0 0.59

(LD-C)

-0.44 0.66

LD 84 2 / 2 (HD-C)

-1.0 0.30

HD 46 2 / 2 (HD-LD)

-0.59 0.55

Final

(Post-Trial)

Pendleton/1

“Amphib”

C 66 2 / 2

2.3 0.31

(LD-C)

-0.27 0.79

LD 46 2 / 2 (HD-C)

1.3 0.19

HD 27 2 / 2,5 (HD-LD)

1.4 0.15
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Table 119 – Males’ Final Fatigue Score Distributions (by Integration Level) - 1833

N.4.14.2 Workload Results

For the 1833 volunteers, we have baseline and final fatigue self-reports from 17 males 

and 10 females (for Twentynine Palms), and 16 males and 10 females (for Pendleton).

Because workload survey responses were ordinal in nature, we restricted our statistical 

analysis to the non-parametric Kruskal-Wallis (rank sum) test to check for significance 

between factors, using the criteria of p ≤ 0.10 for statistical significance (*). Where we 

had more than two groups to compare—and if the Kruskal-Wallis test showed 

significance for similarity—then we conducted Wilcoxon pairwise comparisons (using 

p<0.033 to adjust for multiple comparisons).

N.4.14.2.1 Workload Results by Gender

We first looked at how maximum workload self-reports compared between males and 

females. Results are summarized in the table below (Table 120). 

Table 120 - Summary of Max Workload Scores (by Gender) – 1833

MOS Workload Location / Day Gender N (scores) Median / 

Mode χ2 Statistic χ2 p-Value

1833

Max 

Workload for 

Trial

29Palms/1

“Live Fire”

M 236 3 / 3 17.4 <0.01*

F 130 3.5 / 4

29Palms/3

“Non-Live Fire”

M 244 3 / 3 2.2 0.13

F 134 3 / 3

Pendleton/1

“Amphib”

M 139 3 / 3 1.1 0.30

F 77 3 / 3
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We found mixed results between male and female 1833 volunteers in their maximum 

workload scores; the results were significant for the “Live-Fire” scenario, but not for the 

“Non-Live Fire” or “Amphibious” scenarios, though the “Non-Live Fire” results could be 

considered borderline.

For the non-significant scenarios, both genders were most likely to report a peak 

workload of “3-Active but Easy”; only for the “Live-Fire Scenario” were females slightly 

more likely to report their peak workload as “4-Challenging” (though “3-Active but Easy” 

still had substantial representation). 

We saw few of the highest max workload scores for either group (i.e., “6-Overloaded” or 

“7-Unmanageable”)—only one male response (for the Non-Live Fire scenario) and 2 to 

4 percent of female responses (by only three Marines, across all three scenarios). This 

suggests most Marines felt capable of accomplishing (if not always easily) the workload 

assigned them. 

As far as the statistical difference between males and females for the Live-Fire 

scenario, it’s unlikely that fatigue was a factor (since the only fatigue effect we saw, by 

gender, was found during the Amphibious scenario). However, it may be that there is a 

slight experience bias that is emphasized during the heightened tempo (or pressure) 

associated with live-fire effects. Without some additional fidelity as to what task or tasks 

elicited the slightly higher reporting rates, then it’s difficult to say. If experience is the 

driving factor in the difference, then we would expect this to decrease over time. 

N.4.14.2.2 Workload Results by Integration Level

In addition to looking at how max workload self-reports compared between males and 

females, we also examined whether males’ responses remained consistent at different 

integration levels. For 1812s, we compared males’ responses in Control (i.e., all-male), 
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Low-Density (i.e., 1 female), and High-Density (i.e., 2 females) AAV crews. We have 

maximum workload self-reports from 17 males (17 males in the Control and LowDensity groups, and 16 males in the High-Density group) for Twentynine Palms and 16 

males (16 males in the Control and Low-Density groups, and 13 males in the HighDensity group) for Pendleton; statistical results are summarized in the table below 

(Table 121). 

Table 121 - Summary of Males’ Max Workload Scores (by Integration Level) – 1833

We did not see a significant difference between males’ responses for any integration 

level, regardless of the scenario. For the Live-Fire trials, males heavily report maximum

workload scores between “2-Little to Do” and “4-Challenging” (95.3% for Control, 96.4% 

for Low-Density, and 97.7% for High-Density). 

On Non-Live Fire trials, we see clustering in this same general range—though with 

lower numbers at “2-Little to Do”, which is consistent with the more physical (and less 

strictly delineated by billet) nature of the non-live fire scenario. 

Finally, with the Pendleton Amphibious trials, we see even lower numbers of reports at 

“2-Little to Do” for all three groups, but the same heavy concentration at “3-Active but 

Easy” and “4-Challenging”. 

This suggests that there are no changes in either compensation or cooperation between 

Control and integrated groups—at least of a nature to shift males’ perception of their 

max workload. However, the borderline result found for the Pendleton scenario—while 

not significant—might warrant additional study to see if the results remain constant 

when more trials are run.

MOS Workload Location / Day IL N 

(scores)

Median

/ Mode

χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test 

p-Value

1833

Max 

Workload 

for Trial

29Palms/1

“Live Fire”

C 108 3 / 3

LD 84 3 / 3 2.8 0.25

HD 44 3 / 3

29Palms/3

“Non-Live Fire”

C 114 3 / 3

LD 84 3 / 3 0.21 0.90

HD 46 3 / 3

Pendleton/1

“Amphib”

C 66 3 / 3

LD 46 3 / 3 4.5 0.11

HD 27 4 / 4
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Table 122 - Males’ Max Workload Score Distributions (by Integration Level) – 1833

N.4.14.3 Cohesion Results

For the 1833 volunteers, we have Unit Cohesion survey results (five statements per 

survey) from 17 males and 10 females (for Twentynine Palms), and 16 males and 10 

females (for Pendleton). Cohesion responses for each statement were set on a ninepoint, Likert scale (one indicating “Strongly Disagree” and nine indicating “Strongly 

Agree”). 

Because the cohesion responses consistently violated the normality and independence 

assumptions for parametric data, we restricted our statistical analysis to the nonparametric Kruskal-Wallis (rank sum) test to check for significance between factors, 

using the criteria of p ≤ 0.10 for statistical significance (*). Where we had more than two 

groups to compare—and if the Kruskal-Wallis test showed significance for similarity—

then we conducted Wilcoxon pairwise comparisons (using p<0.033 to adjust for multiple 

comparisons).

N.4.14.3.1 Cohesion Results by Gender

We first looked at how cohesion results—for each statement, and for a composite result 

(the sum of all five responses, which scaled between 5 and 45)—compared between 

males and females, following the conclusion of their unit’s run-cycle. Statistical results

are summarized in the tables below for Twentynine Palms (Table 123) and Pendleton 

(Table 124).
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Table 123 - Summary of Unit Cohesion Scores (by Gender) - 1833 (29Palms)

For Twentynine Palms, we found no significant difference in between 1833 males and 

females for all five cohesion statements, as well as no difference for their respective 

overall composite cohesion scores. For both genders, and across all five statements, 

we see a very strong preference for cohesion scores in the top two levels (68.9% to 

74.6%), with a very small number of sporadic reports at all levels below “5”. 

Table 124 - Summary of Unit Cohesion Scores (by Gender) - 1833 (Pendleton)

However, when we look at the results for the Pendleton phase of the study (i.e., the 

amphibious scenario), we see a different result entirely—we find a significant difference 

between all five cohesion statements (“Q1-United”, “Q2-Responsibility”, “Q3-

Aspirations”, “Q4-Help”, and “Q5-Comm”), as well as for the overall composite cohesion 

MOS Cohesion Gender N 

(scores) Mean SD χ2 

Statistic

χ2 pValue

1833

Q1: Group was united in trying to 

reach goals

M 244 7.98 1.43

0.45 0.50

F 134 7.97 1.26

Q2: We all take responsibility for 

task success of the group

M 244 7.86 1.55

1.68 0.20

F 134 8.09 1.28

Q3: Group members have similar 

aspirations for success

M 244 7.90 1.37

0.36 0.55

F 134 7.98 1.31

Q4: If members had problems with a 

task, all wanted to help

M 244 7.84 1.59

0.94 0.33

F 134 8.04 1.31

Q5: Members communicated freely 

about responsibilities

M 244 7.94 1.47

0.58 0.45

F 134 7.85 1.46

Composite Score (sum of Q1-Q5)

M 244 39.53 6.83

1.03 0.31

F 134 39.93 6.20

MOS Cohesion Gender N Mean SD χ2 

Statistic

χ2 pValue

1833

Q1: Group was united in trying to 

reach goals

M 139 8.20 1.40

4.46 0.03*

F 77 7.88 1.48

Q2: We all take responsibility for 

task success of the group

M 139 8.19 1.45

6.39 0.01*

F 77 7.82 1.48

Q3: Group members have similar 

aspirations for success

M 139 8.16 1.49

4.49 0.03*

F 77 7.86 1.49

Q4: If members had problems with a 

task, all wanted to help

M 139 8.18 1.45

5.28 0.02*

F 77 7.82 1.49

Q5: Members communicated freely 

about responsibilities

M 139 8.13 1.52

7.78 <0.01*

F 77 7.71 1.57

Composite Score (sum of Q1-Q5)

M 139 40.86 7.11

4.16 0.04*

F 77 39.09 7.18
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score. This is rather unexpected, given that the two populations are almost entirely the 

same (one male from Twentynine Palms did not continue for the Pendleton phase). 

When we look more closely at the distributions of each gender at Pendleton, we still see 

very strong clustering at the two highest levels—as we saw during Twentynine Palms 

(71.4% and 85.6%). Where the two phases differ is that females tend to be a bit more 

evenly split between “8” and “9” than before, and we see a slight bump in male reports

of the lowest level (“1”)—all by the same male Marine—and in female reports at “2” and 

“3” (also by a single female Marine). Based on these revelations, it does not appear that 

the significant differences we see for the Pendleton phase are necessarily practical 

differences in the general perception of unit cohesion for 1833s. 

We also graphed the means for each survey statement as a percentage of how strongly 

the volunteers agreed (positive) or disagreed (negative) with each survey statement, for 

both Twentynine Palms (Figure 24) and Pendleton (Figure 25). 

The average values (by gender)—for both sites—reflect a generally high perception of 

unit cohesion across the majority of 1833 volunteers, despite a very small percentage of 

responses by two Marines. The only practical difference between the two sites—one 

showing no significance (Twentynine Palms) and one that does (Pendleton)—is a slight 

dip in females’ perception of unit cohesion. 

Figure 24 - Perception of Unit Cohesion (by Gender) – 1833 (Twentynine Palms)
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Figure 25 - Perception of Unit Cohesion (by Gender) – 1833 (Pendleton)

N.4.14.3.2 Cohesion Results by Integration Level

In addition to looking at how unit cohesion scores compared between males and 

females, we also examined whether males’ cohesion responses remained consistent at 

different integration levels. For 1833s, we compared males’ responses in Control (i.e., 

all-male), Low-Density (i.e., 1 female), and High-Density (i.e., 2 females) AAV crews.

We have unit cohesion survey results (five statements per survey) from 17 males (17 

males in the Control and Low-Density groups, and 16 males in the High-Density group) 

for Twentynine Palms (Table 125) and 16 males (16 males in the Control and LowDensity groups, and 13 males in the High-Density group) for Pendleton (Table 126). 
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Table 125 - Summary of Males' Unit Cohesion Scores (by Integration Level) - 1833 (29Palms)

For Twentynine Palms, we found a statistical difference between the Control group and 

both integration levels (i.e., High-Density, and Low-Density groups) for all five cohesion 

statements, as well as for the overall composite cohesion score. However, we did not 

see a difference between the two integration levels. 

When we looked at the distributions of each question, we see very similar patterns—the 

majority of responses are heavily skewed to the far right (i.e., “9”, at Significantly 

Agree), and taper off relatively quickly to the left. Where the differences occur is in the 

sharpness of the main peak at “9” and the span of the taper. For Control groups, we see 

MOS Cohesion IL N Mean SD χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

1833

Q1: Group was united in 

trying to reach goals

C 114 8.39 0.83

12.68 <0.01*

(LD-C)

-2.56 0.01*

LD 84 7.76 1.56 (HD-C)

-3.27 <0.01*

HD 46 7.37 1.97 (HD-LD)

-1.03 0.30

Q2: We all take 

responsibility for task 

success of the group

C 114 8.30 0.94

12.97 <0.01*

(LD-C)

-2.86 <0.01*

LD 84 7.58 1.78 (HD-C)

-3.10 <0.01*

HD 46 7.30 2.00 (HD-LD)

-0.75 0.45

Q3: Group members have 

similar aspirations for 

success

C 114 8.23 0.96

8.54 0.01*

(LD-C)

-2.64 <0.01*

LD 84 7.69 1.39 (HD-C)

-2.14 0.03

HD 46 7.48 1.93 (HD-LD)

-0.07 0.95

Q4: If members had 

problems with a task, all 

wanted to help

C 114 8.16 1.22

5.70 0.06*

(LD-C)

-2.05 0.04

LD 84 7.55 1.86 (HD-C)

-1.90 0.06

HD 46 7.61 1.78 (HD-LD)

-0.06 0.95

Q5: Members 

communicated freely about 

responsibilities

C 114 8.36 0.93

15.57 <0.01*

(LD-C)

-3.14 <0.01*

LD 84 7.67 1.65 (HD-C)

-2.43 <0.01*

HD 46 7.41 1.89 (HD-LD)

-0.71 0.48

Composite Score 

(sum of Q1-Q5)

Lowest: 5 | Highest 45

C 114 41.43 4.28

11.73 <0.01*

(LD-C)

-2.52 0.01*

LD 84 38.25 7.57 (HD-C)

-3.12 <0.01*

HD 46 37.17 9.09 (HD-LD)

-0.89 0.37
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the sharpest peak (52% to 60% across all five questions) that tapers off, predominantly, 

by “7” with virtually no responses beyond that. 

For the two integrated groups, the peaks are a bit more shallow (35% to 45%), and the 

taper spans a wider (and more negative) set of responses—mostly by “5”, but there are 

sporadic reports of scores at the lowest level “1” (significantly disagree). 

Table 126 - Summary of Males' Unit Cohesion Scores (by Integration Level) - 1833 (Pendleton)

MOS Cohesion IL N Mean SD χ2 

Statistic

χ2 pValueZ-Test 

Statistic

Z-Test pValue

1833

Q1: Group was united in 

trying to reach goals

C 66 8.62 0.58

12.65 <0.01*

(LD-C)

-2.04 0.04

LD 46 8.28 0.89 (HD-C)

11.81 <0.01*

HD 27 7.04 2.53 (HD-LD)

-1.91 0.06

Q2: We all take 

responsibility for task 

success of the group

C 66 8.59 0.68

11.81 <0.01*

(LD-C)

-2.00 0.05

LD 46 8.30 0.84 (HD-C)

-3.25 <0.01*

HD 27 7.00 2.62 (HD-LD)

-1.83 0.07

Q3: Group members have 

similar aspirations for 

success

C 66 8.65 0.57

19.52 <0.01*

(LD-C)

-2.11 0.03*

LD 46 8.33 0.84 (HD-C)

-4.23 <0.01*

HD 27 6.67 2.60 (HD-LD)

-2.76 <0.01*

Q4: If members had 

problems with a task, all 

wanted to help

C 66 8.68 0.50

21.16 <0.01*

(LD-C)

-2.62 <0.01*

LD 46 8.30 0.81 (HD-C)

-4.32 <0.01*

HD 27 6.74 2.55 (HD-LD)

-2.62 <0.01*

Q5: Members 

communicated freely about 

responsibilities

C 66 8.64 0.60

19.43 <0.01*

(LD-C)

-2.25 0.02*

LD 46 8.28 0.89 (HD-C)

-4.21 <0.01*

HD 27 6.63 2.63 (HD-LD)

-2.65 <0.01*

Composite Score 

(sum of Q1-Q5)

Lowest: 5 | Highest 45

C 66 43.18 2.75

16.18 <0.01*

(LD-C)

-2.35 0.02*

LD 46 41.50 4.08 (HD-C)

-3.78 <0.01*

HD 27 34.07 12.59 (HD-LD)

-2.19 0.03*
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When we looked the Pendleton results, we do find a statistical difference between the 

Control group and the High-Density; for the Low-Density group, we see mixed results 

against both the Control group and the High-Density group. 

For this location, the pattern is almost identical to what we saw for Twentynine Palms 

(i.e., peaks for all groups at “9”, with the absolute percentage dropping with integration 

level and in the span of the taper. For the High-Density group, we also see some 

indications of a secondary peak at the neutral level, “5”, with some sporadic reports at 

the lowest level, “1” (representing 11% of all High-Density responses). 

We also graphed the means for each statement as a percentage of how strongly the 

volunteers agreed (positive) or disagreed (negative) with each question’s statement, for 

both Twentynine Palms (Figure 26) and Pendleton (Figure 27). The average values (by 

integration level) shown are consistent with what we saw with regards to males’ 

relatively high perceptions of unit cohesion within the Control group, along with the easy 

decline in their perception of cohesion when in the Low- and High-Density groups.

Figure 26 - Males' Perceptions of Unit Cohesion (by Integration Level) - 1833 (29Palms)
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Figure 27 - Males' Perceptions of Unit Cohesion (by Integration Level) - 1833 (Pendleton)

Unfortunately, the survey did not provide for reasons as to why males were more likely 

to choose lower cohesion scores when in an integrated group, nor what might have 

changed between Twentynine Palms and Pendleton, given that the populations were 

almost identical. 

Relative experience levels may have played a role—which may also explain the greater 

volatility of responses for the Amphibious scenario at Pendleton, especially when 

combined with the relatively low N values for High-Density groups. Incidentally, the 

sharper drop in males’ perceptions in High-Density groups for Pendleton deviates quite 

a bit from how females perceived their unit cohesion.
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Annex O. 

Readiness

This annex details the readiness portion of the Ground Combat Element Integrated 

Task Force (GCEITF) experiment. The sections outline the Data Set Description, and 

Modeling Results. 

O.1 Data Set Description 

O.1.1 Data Set Overview

The readiness dataset contains observations for each volunteer’s medical readiness at 

an individual level. Although readiness for each Marine can be summarized as a ratio 

of the number of full duty days to the number of total duty days, we had much more 

detail on individual volunteer outcomes and we discuss the analyses of these outcomes 

below. The total summary measure of readiness may obscure some of the more 

detailed outcomes, thus, we do not analyze it as a stand-alone result. 

The observed time began when the Marine joined the GCEITF and ended at the 

completion of the experiment. The completion of the experiment for an individual could 

either be the actual end of the experiment, when a Marine DOR, or when a Marine was 

dropped (due to medical reasons) from the experiment by GCEITF leadership. For each 

volunteer, we recorded the following variables, in addition to the USMC personnel 

variables discussed in Methodology Annex. 

• Start and end dates of participation, 

• Reason for end of observation (DOR or end of experiment), 

• Dates of every visit to the aid station, 

• Diagnosis resulting from every visit to the aid station, 

• Number of documented visits to the aid station, 

• Number of calendar days in which the volunteer wasn’t available for 

participation in the experiment due to injury or illness (termed ‘unavailable’ from 

here on). 

• Number of calendar days the volunteer was unavailable due to experimental 

injury (we will use ‘occupational injury’ from here on to describe these), 

• Number of calendar days the volunteer was unavailable due to an injury or 

illness that was not related to his or her participation in the experiment (we term 

these ‘non-occupational injuries’), 
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• Lost training days1 (days lost between joining the units and the start of the 

experiment), 

• Lost Experimental days2 (days lost between the start and end of the 

experiment), 

• Number of calendar days until the first medical visit (occupational, nonoccupational, or overall), 

• Number of calendar days until the first occupational injury, 

O.1.2 Volunteer Participants

At the beginning of the experiment, we had 104 female volunteers and 283 male 

volunteers; we only performed statistical modeling on 102 female volunteers and 254 

male volunteers. Data errors or omissions caused volunteers to be excluded from 

modeling analysis. 

O.2 Descriptive Statistics 

The 283 males were available 98.4% of the time while the 104 females were available 

96.8% of the time based on the total quantity of days available divided by the total days. 

Table O-1 provides a break out of the unavailable days by gender and causality 

(occupational vs. non-occupational3). 

Table O-1. Percentage Breakout of Unavailable Days by Gender and Causality

Occupational Non-Occupational

Male 40% 60%

Female 80% 20%

Almost half of the male volunteers (49%) and the majority of female volunteers (80%) 

experienced an injury or illness during their time assigned to the GCEITF. Some 

volunteers experienced more than one. Figure O-1 illustrates the percentage of males 

and females with injuries and/or illnesses ranging from 0 to 4. 

 

1 Training days include time from when the volunteer joined the unit and until the earlier of DOR date or 

02/28/2015. 

2 Experimental days include time from 03/01/2015 and until the earlier of DOR date or the end of experiment for 

the volunteer’s MOS. 

3 Non-occupational categorization includes illnesses (e.g., colds, flu, skin rashes, etc.) whereas occupational does 

not.
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Figure O-1. Percentage of Volunteers, by Gender, with One or More Injuries or Illnesses

O.3 Statistical Modeling Results 

O.3.1 Statistical Modeling Results Overview

The modeling section explains the relationships observed in the data in this modeling 

section. The goal of statistical modeling, as applied here, is to estimate, 

simultaneously, the effect of gender and other relevant variables on readiness. Refer to 

the Methodology Annex for a broad overview of the analysis plan and the variables 

used in the models. 

For each outcome, we describe the significant variables in the model and whether these 

variables are either positively or negatively correlated with the result. A negative 

correlation indicates an increase in that variable will result in a decrease in the response 

variable, which is a desired outcome for injury rates and days missed from the 

experiment but not a desirable outcome for time to injury. 

O.3.2 Readiness Method of Analysis

Because of small sample size issues, we group 0311, 0331, 0341, 0351, and 0352

Engineers, as well as Provisional Infantry and Provisional Machine Guns, into a ‘hiking 

MOS’ category; Tanks, AAV, and LAV into a ‘vehicle MOS’ category; and Artillery as its 

own category, since it is neither a hiking nor a vehicle MOS.

The starting full model for each variable includes a person’s gender, MOS type, height, 

weight, AFQT, GT, PFT run, PFT crunch, CFT MUF, and CFT MTC times. Model 

selection using AIC was only possible for the DOR analysis. For other outcomes of 

interest, we only comment on significance of the individual variables in the full model. 
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Variables reported as significant are concluded to be significant based on at least a 

one-sided test. 

We used the following types of models for the outcomes of interest. For a detailed 

description of the models and the rationale for their choice, refer to the Methodology 

Annex.

A zero-inflated negative binomial model, with gender as a predictor of the probability of 

event, and gender, as well as other variables, predicting the expected count of events, 

was used to model

• Lost training days,

• Lost experimental days,

• Number of visits to the aid station, 

• Days unavailable to participate, 

• Days unavailable to participate due to an occupational injury, 

• Days unavailable to participate due to a non-occupational injury. 

A Cox Proportional Hazards model was used to model

• Days to first medical visit,

• Days to first experimental injury.

Finally, a frailty model was used to model

• Instantaneous injury rates.

O.3.3 Readiness Modeling Results

The only personnel variables that consistently stood out as predictors of readiness were 

gender and MOS type. In particular, with the exception of non-occupational injuries, 

outcomes were always worse for female volunteers. Marines in vehicle MOSs tended 

to have lower injury rates than those in hiking or Artillery MOSs. The CFT MUF time 

appears several times as a predictor of readiness, so we recommend further 

investigation of the relationship of this measure with injury rates. Other variables, listed 

below, appeared statistically significant, but had effects of negligible size.

O.3.3.1 Lost training days

We modeled lost training days using zero-inflated negative binomial regression. The 

‘event’ part of this model is run as a function of gender, and the count part of the model 

is run as a function of gender, MOS group, and personnel variables. We report 

significant correlations below.
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Females were 18 percentage points more likely to lose training days, and the difference 

is statistically significant with a two-sided p-value <0.01. Of those who lost training days,

however, males lost significantly more as indicated by a two-sided p-value of 0.06. 

Specifically, of those who lost training days, males lost over 4 times more than females, 

keeping all else constant.

Additionally, the following variables were found to be significantly negatively correlated 

to the number of lost training days, for those Marines who lost them:

• Vehicle MOS (relative to hiking MOS), 

• CFT MTC time, 

• PFT crunch score. 

The following variables were found to be significantly positively correlated to the number 

of lost training days, for those Marines who lost them:

• CFT MANUF time.

O.3.3.2 Lost experimental days

We model lost experimental days using zero-inflated negative binomial regression. The 

‘event’ part of this model is run as a function of gender, and the count part of the model 

is run as a function of gender, MOS group, and personnel variables. We report 

significant correlations below.

Females were 12.65 percentage points more likely to lose experimental days and the 

difference is statistically significant with a 2-sided p-value of 0.02. However, of those 

Marines who lost experimental days, there was no statistically significant difference 

between how many were lost by male and female Marines. 

Additionally, the following variables were found to be significantly negatively correlated 

to the number of lost experimental days, for those Marines who lost them:

• Vehicle MOS (relative to hiking MOS), 

• Weight.

The following variables were found to be significantly positively correlated to the number 

of lost experimental days, for those Marines who lost them:

• AFQT.

O.3.3.3 Number of visits to the aid station

We model the number of visits to the aid station using zero-inflated negative binomial 

regression. The ‘event’ part of this model is run as a function of gender, and the count 
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part of the model is run as a function of gender, MOS group, and personnel variables. 

We report significant correlations below.

Female Marines were 37 percentage points more likely to have a medical visit, which is 

a statistically significant difference based on a p-value < 0.01. However, of those 

Marines who had at least one medical visit, male and female Marines had 

approximately the same number of visits, holding all else constant. 

Additionally, the following variables were found to be significantly negatively correlated 

to the number of visits to the aid station, for those Marines who made them:

• Vehicle MOS (relative to hiking MOS),

• Weight

• GT score

The following variables were found to be significantly positively correlated to the number 

of visits to the aid station, for those Marines who made them:

• AFQT. 

O.3.3.4 Days unavailable to participate

We model days unavailable to participate using zero-inflated negative binomial 

regression. The ‘event’ part of this model is run as a function of gender, and the count 

part of the model is run as a function of gender, MOS group, and personnel variables. 

We report significant correlations below.

Female Marines were 25 percentage points more likely to not be able to participate in 

the experiment. However, among the Marines who were unavailable for at least one 

day, females were unavailable for fewer days than males, keeping other variables 

constant, and the result is statistically significant in a one-sided test with a p-value of 

0.09. 

Additionally, the following variables were found to be significantly negatively correlated 

to the number days unavailable to participate, for those Marines who lost them:

• Vehicle MOS (relative to hiking MOS),

• Weight.

The following variables were found to be significantly positively correlated to the number 

of days unavailable to participate, for those Marines who lost them:

• CFT MANUF time. 
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O.3.3.5 Days unavailable to participate due to occupational injury

We model days unavailable to participate due to occupational injury using zero-inflated 

negative binomial regression. The ‘event’ part of this model is run as a function of 

gender, and the count part of the model is run as a function of gender, MOS group, and 

personnel variables. We report significant correlations below.

Female Marines were about 19 percentage points more likely to miss experimental days 

due to an injury resulting directly from performing experimental tasks, and the difference 

is statistically significant with a p-value <0.01. Of the Marines who missed days due to 

such injuries, there are no differences in the number of days missed by males and 

females, holding all other variables constant. 

Additionally, the following variables were found to be significantly negatively correlated 

to the number of days unavailable to participate due to occupational injury, for those 

Marines who lost them:

• Vehicle MOS (relative to hiking MOS).

The following variables were found to be significantly positively correlated to the number 

of days unavailable to participate due to occupational injury, for those Marines who lost 

them:

• None.

O.3.3.6 Days unavailable to participate due to a non-occupational injury

We model the number of days unavailable to participate due to a non-occupational 

injury using zero-inflated negative binomial regression. The ‘event’ part of this model is 

run as a function of gender, and the count part of the model is run as a function of 

gender, MOS group, and personnel variables. We report significant correlations below.

Because of over-dispersion, the zero inflated part of the model did not estimate 

standard errors for this result so we cannot comment on statistical significance of the 

difference in probability, by gender, of missing at least one day due to a nonoccupational injury.

However, the negative binomial part of the model identifies that male Marines are likely 

to miss 12 times the number of days due to a non-occupational injury than female 

Marines, holding all other variables constant. 

Additionally, the following variables were found to be significantly negatively correlated 

to the number of days unavailable to participate due to a non-occupational injury, for 

those Marines who lost them:

• Weight.
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The following variables were found to be significantly positively correlated to the number 

of days unavailable to participate due to a non-occupational injury, for those Marines 

who lost them:

• Artillery (relative to hiking MOS),

• AFQT, 

• CFT MANUF time.

O.3.3.7 Days to first medical visit

We model days to first medical visit using a Cox Proportional Hazards model. Time to 

first medical visits is modeled as a function of gender, MOS group, and personnel 

variables. We report significant correlations below.

Survival analysis of days to first medical visit showed no difference by gender. 

Additionally, the following variables were found to be significantly negatively correlated 

to the number of days to first medical visit: 

• Vehicle MOS (relative to hiking MOS), 

The following variables were found to be significantly positively correlated to the number 

of days to first medical visit: 

• GT Score. 

O.3.3.8 Days to first experimental injury

We model days to first experimental injury using a Cox Proportional Hazards model. 

Time to first medical visit is modeled as a function of gender, MOS group, and 

personnel variables. We report significant correlations below.

Survival analysis of days to first experimental injury showed no significant impact of 

gender. 

Additionally, the following variables were found to be significantly negatively correlated 

to the number of days to first experimental injury: 

• Vehicle MOS (relative to hiking MOS). 

The following variables were found to be significantly positively correlated to the number 

of days to first experimental injury: 

• GT score. 
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O.3.3.9 Frailty analysis of injury rates

We model injury rates using frailty models. Injury rates for individuals are modeled as a 

function of gender, MOS group, and personnel variables, while taking into account the 

fact that we have repeated observations for some Marines. Based on AIC and BIC, we 

chose Weibull distribution for the baseline hazard and Gamma for the frailty function. 

We report significant correlations below.

We ran three models based on three outcomes: any event that results in a medical visit

(AE), only non-occupational injuries (NOI), and any occupational injuries (OI). In all 

three models, male Marines were statistically significantly less likely to have the 

negative outcomes we modeled. The hazard rate for men was 0.48 (AE), 0.53 (NOI), 

and 0.45 (OI) that of females, ceteris paribus. 

Additionally, the following variables were found to be significantly negatively correlated 

to the instantaneous hazard rate in the analysis of all events leading to a medical visit:

• Weight,

• AFQT score.

The following variables were found to be significantly positively to the instantaneous 

hazard rate in the analysis of all events leading to a medical visit: 

• Artillery MOS (relative to hiking MOS).

The following variables were found to be significantly negatively correlated to the 

instantaneous hazard rate of a non-occupational injury:

• None.

The following variables were found to be significantly positively to the instantaneous 

hazard rate of a non-occupational injury: 

• Artillery MOS (relative to hiking MOS), 

• Height,

• CFT MANUF time. 

The following variables were found to be significantly negatively correlated to the 

instantaneous hazard rate of an occupational injury:

• Vehicle MOS (relative to hiking MOS),

• Weight,

• AFQT.
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The following variables were found to be significantly positively to the instantaneous 

hazard rate of an occupational injury: 

• None.
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Annex P.

Proficiency and Conduct Marks 

This annex details the Proficiency and Conduct Mark portion of the Ground Combat 

Element Integrated Task Force (GCEITF). The sections below explains the purpose of 

the Proficiency and Conduct Marks in the Marine Corps, logical expectations of impacts 

on marks given experimental realities, mitigation of negative career impacts, and 

descriptive statistics.

P.1 Proficiency Marks 

Proficiency marks are assigned to Marines who hold the grade of E-1 to E-4. The 

proficiency mark indicates how well a Marine performed his or her primary duty during 

the performance period. The marks are provided by a Marine’s commander in 

consultation with the officer or staff noncommissioned officer who supervised the Marine

in the performance of his/her duties. Proficiency marks consider the Marine’s technical 

skills, specialized knowledge, and the “whole Marine concept,” which is commonly 

understood as mission accomplishment, leadership, intellect and wisdom, individual 

character, physical fitness, personal appearance, and completion of professional 

military education (HQMC, 2000). 

P.2 Conduct Marks 

Conduct marks are assigned to Marines who hold the grade of E-1 through E-4. The 

conduct mark indicates a Marine’s observance of the law, regulations, conformance to 

accepted usage and customs, and positive contribution to unit and Corps. General 

bearing, attitude, interest, reliability, courtesy, cooperation, obedience, adaptability, 

influence on others, moral fitness, physical fitness as effected by clean and temperate 

habits, and participation in unit activities not related directly to unit mission are all 

factors in the evaluation (HQMC, 2000). 

P.3 Limitations for Analysis

P.3.1 Proficiency Marks - Logical Expectations

P.3.1.1 MOS Experience 

In a non-experimental unit, proficiency marks are assigned based on the performance of 

duties in the Marine’s assigned billet. In the case of the GCEITF experiment, only a few 

MOSs were operating within their assigned primary MOS (i.e., Males with Closed MOSs 

and male and female Combat Engineers (MOS 1371)). Female Marine volunteers 

recruited from the Fleet Marine Force in support of this event possessed an open 

Primary MOS and had no ground combat-unit experience, and, therefore, did not have 

any fleet unit-level training experience prior to their assignment to the GCEITF. 
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Combat arms male Marine volunteers obtained in support of this event had fleet unitlevel training experience and, in some cases, real-world deployment experience in their 

MOS prior to the conduct of this event. The only exception is Male Provisional 

Infantryman and Provisional Machine Gunners who may or may not have been 

assigned to closed units prior to the GCEITF experiment. This disparity in occupational 

experience is noted as a limitation.

P.3.1.2 Billet Assignment 

In many cases in the Fleet Marine Force, a junior Marine begins his or her career in a 

basic billet with minimal complexity, advancing through billets of increasing 

responsibility as proficiency increases. Per the design of the experiment, personnel 

assignments to billets were randomized, resulting in an unconventional training period 

before the start of the experimental phase as well as a change in billet assignment with 

every new trial during the conduct of the experiment. 

P.3.1.3 Physiological Disparities

The GCEITF was designed to measure performance differences in the execution of 

tasks that were identified as the most physically demanding within each experimental 

MOS. Furthermore the selected tasks were ones that could be done repetitively and 

were not necessarily the ones that required the most cognitive/technical skills and 

therefore did not lend themselves to evaluation of anything other than physicality. The 

expectation that each Marine perform his or her duties within that MOS lends itself to a 

stratification of performance levels based, on some level, on the physical capacity to 

execute the task. It stands to reason that two Marines who are physiologically different 

from each other might perform a physical task with different levels of effectiveness, and 

that, theoretically, this would affect the way their evaluating superiors perceived their 

proficiency. 

P.3.2 Conduct Marks: Logical Expectations

Contrary to proficiency, conduct marks are assigned in ways that are generally blind to 

primary versus billet MOS. Anecdotally, conduct marks tend to be similar to proficiency 

marks. 

P.3.2.1 Conduct Marks: Experimental Nuances

Unlike within Fleet Marine Force Units, the GCEITF volunteers reserved the unusual 

right to Drop on Request. It has been theorized that this had an inordinate effect on the 

behavior of some volunteers, and that it imparts a sense of power that undermines

traditional military order. In most cases, volunteers acted with the level of 

professionalism expected of United States Marines. As such, one would anticipate that 

conduct marks reflected the behavior that volunteers exhibited, but that but some 

distortion from the norms likely remained. 
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P.3.2.2 Sample sizes 

Proficiency and Conduct marks are assigned to Marines in the grade of E-1 to E-4. This 

decreased the sample size of the groups being compared and analyzed. Though we 

provide summary statistics to describe the data, in most cases, sample sizes are 

sufficiently small to where any extrapolation of these descriptions outside of the GCEITF 

sample is not appropriate.

P.4 Experimental Mitigation 

Per the EAP:

“Male and Female Open MOS volunteers participating in the provisional rifle 

company experiment as well as female volunteer participants for closed MOSs will 

not be performing in their normal MOS functions for the duration of their assignment 

to the GCEITF. Duty proficiency marks will be assigned in accordance with the 

Individual Records Administration Manual (HQMC, 2000) and the commanding 

officer of the GCEITF will provide due allowance for Marines who will be filling 

billets inconsistent with their grade and normal MOS skills.” 

In practical terms, participation in the experiment cannot harm the participants, including 

their chances for promotion or retention. Of particular note, when a Marine was 

operating outside his or her MOS within the ITF, the proficiency and conduct marks 

assigned were administratively used to compare the Marine to others in that Marine’s 

primary MOS. For instance, a Female Marine serving in the 0311 portion of the 

experiment, with a primary MOS of 0411, would not administratively (in the context of 

the greater Marine Corps population) be compared to other 0311s. Instead, her marks 

count toward her composite score and her promotion potential is gauged against 0411s,

regardless of her assigned duties. 

The special allowances necessary to protect the volunteers, which are provided by the 

commanding officer of the GCEITF in the issuance of the proficiency and conduct 

ratings, preclude their use in any meaningful analysis.

P.5 Descriptive Statistics 

Tables P-1 and P-2 provided the descriptive statistics for the GCEITF volunteers.

Table P-1. Descriptive Statistics for Proficiency Marks

Including DOR individuals Excluding DOR individuals

Metric Gender Sample 

Size Mean SD Sample 

Size Mean SD 

Proficiency Mark – all 

MOS’s (includes DOR 

individuals)

M 198 4.40 0.17 144 4.42 0.15

F 71 4.45 0.20 55 4.47 0.20

0311

M 50 4.36 0.19 26 4.42 0.17

F 8 4.28 0.27 5 4.36 0.30
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Including DOR individuals Excluding DOR individuals

Metric Gender Sample 

Size Mean SD Sample Size Mean SD 

0313

M 10 4.53 0.13 9 4.53 0.13

F 7 4.41 0.04 7 4.41 0.04

0331

M 8 4.41 0.19 4 4.38 0.13

F 7 4.44 0.19 5 4.48 0.22

0341

M 6 4.45 0.20 4 4.50 0.20

F 5 4.58 0.19 4 4.55 0.21

0351

M 2 1

F 3 0

0352

M 4 2

F 0 0

0811

M 28 4.41 0.13 27 4.42 0.13

F 13 4.58 0.15 11 4.58 0.15

1371

M 19 4.28 0.19 14 4.32 0.18

F 9 4.28 0.19 7 4.30 0.21

1812

M 18 4.41 0.19 16 4.43 0.14

F 2 4.55 0.07 2 4.55 0.07

1833

M 14 4.47 0.12 13 4.47 0.13

F 5 4.48 0.13 5 4.48 0.13

PI

M 33 4.39 0.14 26 4.42 0.13

F 10 4.40 0.13 6 4.38 0.15

PMG

M 6 4.42 0.12 2 4.40 0.14

F 4 4.6 0.22 3 4.70 0.10

Table P-2. Descriptive Statistics for Conduct Marks

Including DOR individuals Excluding DOR individuals

Metric Gender Sample 

Size Mean SD Sample 

Size Mean SD 

Conduct Mark (includes DOR 

individuals)

M 198 4.39 0.17 144 4.41 0.15

F 73 4.45 0.18 55 4.47 0.18

0311

M 50 4.36 0.19 26 4.42 0.17

F 8 4.31 0.26 5 4.38 0.33

0313

M 10 4.48 0.17 9 4.48 0.18

F 7 4.40 0.06 7 4.40 0.06

0331

M 8 4.41 0.20 4 4.43 0.13

F 7 4.47 0.16 5 4.52 0.16

0341

M 6 4.47 0.23 4 4.50 0.27

F 5 4.58 0.18 4 4.50 0.19

0351

M 2 1

F 3 0

0352

M 4 2

F 0 0
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Including DOR individuals Excluding DOR individuals

Metric Gender Sample 

Size Mean SD Sample 

Size Mean SD 

0811

M 28 4.40 0.11 27 4.41 0.11

F 13 4.48 0.11 11 4.48 0.12

1371

M 19 4.29 0.18 14 4.32 0.18

F 9 4.28 0.22 7 4.31 0.23

1812

M 18 4.36 0.15 16 4.38 0.10

F 2 4.60 0.14 2 4.60 0.14

1833

M 14 4.48 0.16 13 4.48 0.17

F 5 4.56 0.11 5 4.56 0.11

PI

M 33 4.38 0.14 26 4.40 0.15

F 10 4.41 0.12 6 4.43 0.15

PMG

M 6 4.43 0.14 2 4.40 0.00

F 4 4.58 0.21 3 4.67 0.12
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Annex Q. 

GCEITF Population

This annex describes the population of the GCEITF volunteers when compared to 

today’s Marine Corps Active Component who possess the same parameters as the 

GCEITF population, i.e., E-1 to E-5s, full-duty medical status. The sections outline the 

Population Overview, Assumptions, Limitations, Descriptive Statistics, Results, and 

Insights. 

Q.1 GCEITF Population Overview

Q.1.1 Background

The ability to generalize the results of the GCEITF experiment to the wider Marine 

Corps is, in part, dependent upon how representative the GCEITF participants were of 

the total population of Marines. 

Q.1.2 Purpose 

This annex presents comparative analysis results for selected personnel variables 

judged to be indicative of relevant military capabilities. These results inform judgment 

about the repeatability of the experimental results and the expectation that observed 

integration effects would be observed throughout a similarly integrated Marine Corps.

Q.1.3 Analytic Objective

The fundamental question addressed by this analysis is: 

How representative are the GCEITF Marine volunteers when compared to the 

Marine Corps’ total Active Component population of Marines with the same 

parameters? 

Q.1.3.1 Participant Parameters

First, to answer this question, the comparisons between the GCEITF volunteer sample 

and the Marine Corps’ total active component population (query database pulled June 

2014) had to be of similar parameters to include:

• The total Marine Corp’s population was defined using the Active Component, 

whereas the GCEITF sample contains both Active and Reserve Component 

Marines. 

• Pay grade of E-5 and below. 

• Full-duty status (i.e., not currently on limited/light duty or pending physical 

evaluation board). 
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• For MOS-to-MOS comparisons, Marines must hold the same Primary MOS 

(PMOS). MOS-to-MOS comparisons were done by gender (i.e., Female 1371 

Combat Engineers within the GCEITF were compared to female Marines who 

also possess the 1371 PMOS within the total Marine Corps, given the same 

parameters; Male PI and PIMG Marines were compared to male open MOS 

Marines within the total Marine Corps, given the same parameters)

From this point on, this annex will refer to the Marine Corps’ total Active Component 

population used for comparison as the total Marine Corps Population.

The GCEITF population encompassed all volunteers who actively participated in the 

experiment. While the number of volunteers was in constant flux, the maximum active 

participation by volunteers at any one time was 382 (278 males/104 females). 

Q.1.3.2 Personnel Variables used for comparison

Second, to answer this question, the comparisons between the GCEITF volunteer 

sample and the Marine Corps’ total active component population were based on 

variables that are common among all Marines, regardless of gender. The tables and 

graphs present the mean of each variable. While the PFT/CFT score used in the 

comparisons are gender-normed, the component scores of PFT and CFT events that 

are continuous and/or gender-neutral (i.e., run times (continuous time captured), crunch 

score (where 100 is the maximum score regardless of gender) were used to give 

greater insight into the individual personnel variables of the Marines within the two 

groups. The 12 personnel variables used include:

• Age

• Height

• Weight

• AFQT

• GT

• PFT, Total Score

• PFT, Crunches

• PFT, Run Time

• CFT, Total Score

• CFT, Maneuver under Fire

• CFT, Movement to Contact

• Rifle Range Score
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Q.1.3.3 Analytical comparisons

Lastly, to answer this question, several comparisons were conducted. All comparisons 

given for the below personnel variables are done so between the GCEITF population 

and the total Marine Corps population with the same parameters, aggregated and by 

PMOS. For each of the 12 personnel variables, 15 comparisons were made yielding a 

total of 180 comparisons. The comparisons are as follows:

Q.1.3.3.1 Objective 1 (Closed MOSs) Comparisons

Q.1.3.3.1.1 Male-Male Marines (Closed MOSs)

GCEITF male Marines participating within their closed MOSs were compared in two 

ways. They were compared to the total male Marine Corps population and they were 

compared to the male Marines currently serving with the same MOS.

Q.1.3.3.1.2 Female-Female Marines (Closed MOSs)

GCEITF female Marines participating within their closed MOSs were compared to the

total female Marine Corps population. Comparing females to other females serving in 

closed MOSs wasn’t possible, as that population currently does not exist. An open 

proxy MOS was also not used.

Q.1.3.3.2 Objective 2 (Open MOSs in Closed MOS Units) Comparisons

Q.1.3.3.2.1 Male-Male Marines (Open MOSs)

GCEITF male Marines participating within their open MOSs, as part of Provisional 

Infantry (PI) or as Provisional Infantry Machinegunners (PIMG), were compared in two 

ways. They were compared to the total male Marine Corps population and they were 

compared to the male Marines currently serving in open MOSs.

GCEITF male Marines participating within the 1371 Combat Engineer MOSs were also 

compared in two ways. They were compared to the total male Marine Corps population

and they were compared to the male Marines currently serving in the 1371 MOS.

Q.1.3.3.2.2 Female-Female Marines (Open MOSs)

GCEITF female Marines participating within their open MOSs, as part of Provisional 

Infantry, were compared to the total female Marine Corps population. 

GCEITF female Marines participating within the 1371 Combat Engineer MOSs were 

compared in two ways. They were compared to the total female Marine Corps 

population and they were compared to the female Marines currently serving in the 1371 

MOS.
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AUGUST 2015 Q-4 

Q.1.3.4 Analytical Methodology

The personnel variables were compared using a non-parametric Kolmogorov-Smirnov 

Test (KST) for differences. Observed differences were judged to be statistically 

significant if the KST produced a p-value less than or equal to 0.10. 

Q.2 Assumptions 

Conclusions depend on the validity of assumptions. These assumptions include:

• The Marine Corps Reserve Component Marines are similar both physically and 

mentally in the performance of Marine Corps fitness and cognitive tests as the Active 

Marine Component.

• When comparison of continuous/gender-neutral personnel variables (i.e., PFT run 

time, AFQT score) were used for analysis, it is assumed that the Marines times

and/or scores reflect the best effort of the individual.

Q.3 Limitations 

The following limitations are noted:

• Because a population of female Marines serving in currently closed MOSs does not 

exist, this Annex is limited to only comparing those GCEITF female Marines who 

participated in Closed MOS experiments to the total female Marine Corps 

population, which consists of Open MOSs only. There is no MOS that can serve as 

a proxy MOS for comparison purposes.

Q.4 Descriptive and Basic Inferential Statistics 

Q.4.1 Descriptive Statistics Overview

This section includes a comparative analysis of personnel variables among GCEITF

volunteers and the larger Marine Corps based on the results of descriptive statistics, 

non-parametric Kolmogorov-Smirnov Test (KST) for differences, and density plots. This 

section presents results that are statistically significant for each gender and for MOS. 

The Population Appendix contains the descriptive statistics for the remainder of the 

personnel variables. 

Q.4.2 Results overview 

One hundred eighty comparisons were conducted and only 30 provided evidence of 

statistically significant differences between the MOSs analyzed between GCEITF and 

the total Marine Corps population. Of those 30 differences, the following results are 

presented for MOS-to-MOS comparisons:

• 14 were observed between male Closed MOS-MOS comparisons. 

• 4 were observed between male Open MOS-to-MOS comparisons. 

• 4 were observed between male 1371 MOS-to-MOS comparisons. 
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• 4 between the female GCEITF volunteers and the total female Marine Corps 

population. 

• 4 were observed between female 1371 MOS-to-MOS comparisons. 

The differences noted were all within the normal limits of any particular variable. With 

the exception of very few differences, the GCEITF volunteers were representative of the 

total population of the Marine Corps. As such, the experimental results can be 

generalized to the wider Marine Corps with confidence in the repeatability of the 

experiment and our expectation that performance differences observed in the 

experiment would also appear in a Marine Corps similarly integrated. 

Q.4.2.1 Age

The table Q-1 and Q-2 below display the results for comparing the age of the male 

GCEITF volunteers to that of the total Marine Corps population given the same 

parameters. The tables display non-parametric KST results and p-values suggesting 

statistical significance. Figures Q-1 through Q-4 are density plots that display the 

density of calculated values in a shape. If p-values are less than the a-priori determined 

significance level of 0.10, we conclude that there is statistical evidence that the 

response for the GCEITF group is different from that in the total Marine Corps 

population. 

Table Q-1 – GCEITF Male Age Compared to Population Male Age

Table Q-2. Significant Male Age Comparisons by MOS

Male Age

All MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

278 22.45 2.45 18.80 21.85 31.60 79212 23.03 3.03 17.40 22.30 47.10 0.02*

Male Age

MOS 

(w/ 

DOR)

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

0352 16 21.71 1.61 20.00 21.25 25.60 790 23.35 3.24 18.50 22.60 36.30 0.07*

1812 19 23.12 2.08 19.80 22.90 27.20 379 22.87 2.78 18.70 22.00 34.20 0.05*

PI&PMG 55 21.69 2.01 19.40 20.90 28.00 58368 23.18 3.04 17.70 22.50 44.40 < 

0.01*
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Figure Q-1 – Age by Population for Males

Figure Q-2. Age by Population for Males MOS 0352
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Q-7 AUGUST 2015

Figure Q-3. Age by Population for Males MOS 1812

Figure Q-4. Age by Population for Males MOS PI & PIMG

The average age of the GCEITF male was 22.45 years, and the average age of a male 

in the Marine Corps Population was 23.03 years. Based on the p-value of the K-S test 

being less than 0.10, this age difference is statistically significant. The GCEITF males 

were statistically significantly younger than the Marine Corps Population, by 

approximately 6 months. The following MOSs had statistically significant differences:
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AUGUST 2015 Q-8 

• 0352 GCEITF males’ average age was 21.71 years and the average age of a 

male in the Marine Corps 0352 population was 23.35 years. The GCEITF males 

were statistically significantly younger, by approximately 20 months.

• 1812 GCEITF males’ average age was 23.12 years and the average age of a 

male in the Marine Corps 1812 population was 22.87 years. The GCEITF males 

were statistically significantly older, by approximately 3 months.

• PI & PIMG GCEITF males’ average age was 21.69 years and the average age of 

a male in the Marine Corps open MOS population was 23.18 years. The 

GCEITF males were statistically significantly younger, by approximately 18 

months.

There is no statistically significant difference in age between female Marines in the 

GCEITF when compared to females in the total Marine Corps Population or in any of 

the female MOS-to-MOS comparisons. 

Q.4.2.2 Height

There is no statistically significant difference in height between Marines in the GCEITF

when compared to the Marine Corps Population or in any of the MOS-to-MOS 

comparisons. 

Q.4.2.3 Weight

Table Q-3 displays the results from the comparison of the weight of the male GCEITF

volunteers to that of males in the Marine Corps Population given the same parameters. 

The table displays non-parametric KST results and p-values suggesting statistical 

significance. Figure Q-5 is a density plots that display the density of calculated values 

in a shape. If p-values are less than the a-priori determined significance level of 0.10, 

we conclude that there is statistical evidence that the response for the GCEITF group is 

different from that in the total Marine Corps Population. 

Table Q-3. GCEITF Male Weight Compared to Population Male Weight

Male 

All 

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

DOR 

incl 278 169.79 22.92 117.00 170.00 246.00 79198 172.36 23.46 92.00 172.00 295.00 0.08*
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Figure Q-5. Weight by Population for Males

The average weight of the GCEITF male was 169.79 lb and the average weight of a 

male in the total Marine Corps Population was 172.36 lb. Based on the p-value of the 

K-S test being less than .10, this difference is statistically significant. The GCEITF

males were statistically significantly lighter than the total Marine Corps Population, by 

approximately 2.5 lb. There are no statistically significant differences in any of the 

MOS-to-MOS comparisons. 

There is no statistically significant difference in weight between females in the GCEITF

when compared to the total Marine Corps Population or in any of the female MOS-toMOS comparisons. 

Q.4.2.4 AFQT

Table Q-4 through Q-6 below display the results for comparing the AFQT of the male

and female GCEITF Volunteers to that of the total Marine Corps Population given the 

same parameters. The tables display non-parametric KST results and p-values 

suggesting statistical significance. Figure Q-6 through Q-10 are density plots that

display the density of calculated values to a shape. If p-values are less than the a-priori 

determined significance level of 0.10, we conclude that there is statistical evidence that 

the response for the GCEITF group is different from that in the total Marine Corps 

population. 
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Table Q-4. GCEITF Male AFQT Compared to Male Population AFQT

Male 

All MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

DOR incl 277 60.56 19.19 22.00 59.00 99.00 79199 62.63 17.79 4.00 62.00 99.00 0.03*

Table Q-5. Significant Male AFQT Comparisons by MOS

Male AFQT

MOS

GCEITF USMC KS 

Test

N Mean SD Median Max N Mean SD Min Median Max Pvalue

0313 14 70.64 20.59 38.0 77.0 95.0 447 59.72 17.74 23.0 56.0 99.0 0.05*

1833 20 61.90 18.27 31.0 69.0 89.0 906 54.93 16.82 20.0 52.0 98.0 0.04*

PI&PMG 55 57.96 17.86 28.0 54.0 95.0 58356 63.24 17.73 9.0 63.0 99.0 0.04*

Table Q-6. Significant Female AFQT Comparisons by MOS

Female AFQT

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

1371 9 74.00 17.73 39 75 92 124 60.56 16.86 33 59.5 95 0.04*

Figure Q-6. AFQT by Population for Males
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Figure Q-7. AFQT by Population for Males MOS 0313

Figure Q-8. AFQT by Population for Males MOS 1833
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Figure Q-9. AFQT by Population for Males MOS PI & PIMG

Figure Q-10. AFQT by Population for Females MOS 1371

The average AFQT score of the GCEITF male was 60.56 and the average AFQT score 

of a male in the Marine Corps Population was 62.63. Based on the p-value of the K-S 

test being less than 0.10, this difference is statistically significant. The GCEITF male 

had statistically significant lower scores when compared to the Marine Corps 

Population, by approximately 2 points. The following MOSs had statistically significant 

differences:

• 0313 GCEITF males’ average AFQT score was 70.64 and the average AFQT 

score for a male in the Marine Corps 0313 population was 59.72. The GCEITF

males’ AFQT scores were statistically significantly greater, by approximately 11 

points.
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• 1833 GCEITF males’ average AFQT score was 61.90 and the average AFQT 

score for a male in the Marine Corps 1833 population score was 54.93. The 

GCEITF males’ AFQT scores were statistically significantly greater, by 

approximately 7 points.

• PI & PIMG GCEITF males’ average AFQT score was 57.96 and the average

AFQT score of a male in the Marine Corps open MOS population was 63.24. 

The GCEITF males’ AFQT scores were statistically significantly less, by 

approximately 5 points.

There is no statistically significant difference in AFQT score between female Marines in 

the GCEITF when compared to the total Marine Corps Population. The following MOS 

had a statistically significant difference:

• 1371 GCEITF females’ average AFQT score was 74.00 and the average AFQT 

score for a female in the Marine Corps 1371 population was 60.56. The GCEITF

females’ AFQT scores were statistically significantly greater, by approximately 13 

points.

Q.4.2.5 GT

Tables Q-7 and Q-8 below display the results for comparing the GT score of the male 

GCEITF Volunteers to that of the males in the Marine Corps Population given the same 

parameters. The tables display non-parametric KST results and p-values suggesting 

statistical significance. Figure Q-11 and Q-12 are density plots that display the density 

of calculated values to a shape. If p-values are less than the a-priori determined 

significance level of 0.10, we conclude that there is statistical evidence that the 

response for the GCEITF group is different from that in the total Marine Corps 

population. 

Table Q-7. GCEITF Male GT Score Compared to Male Population GT Score 

Male 

All MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

DOR incl 272 106.79 12.17 80.00 106.00 136.00 79207 108.99 11.73 12 108 159 < 

0.01*

Table Q-8. Significant Male GT Comparisons by MOS

Male GT

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue
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PI&PMG 54 104.44 12.47 81 102.0 136 58363 109.33 11.73 12 108 159 0.01*

Figure Q-11. GT by Population for Males

Figure Q-12. GT by Population for Males for MOS PI & PIMG

The average GT score of the GCEITF male was 106.79 and the average GT score of a 

male in the Marine Corps Population was 108.99. Based on the p-value of the K-S test 

being less than 0.10, this difference is statistically significant. The GCEITF males 

scored lower and the difference is statistically significant compared to the males in the

Marine Corps Population, by approximately 2.2 points. The following MOS had a 

statistically significant difference:

• PI & PIMG GCEITF males’ average GT score was 104.44 and the average GT 

score of a male in the Marine Corps open MOS population was 109.33. The 

GCEITF males’ GT scores were statistically significantly lower, by approximately 

5 points.
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There is no statistically significant difference in GT scores between females in the 

GCEITF when compared to females in the Marine Corps Population. There are no 

statistically significant differences in any of the female MOS-to-MOS comparisons. 

Q.4.2.6 Physical Fitness Test (PFT) Score

Table Q-9 through Q-11 below display the results for comparing the Physical Fitness 

Test (PFT) Scores of the male and female GCEITF Volunteers to that of the total Marine 

Corps Population given the same parameters. The tables display non-parametric KST

results and p-values suggesting statistical significance. Figure Q-13 through Q-17 are 

density plots that display the density of calculated values in a shape. If p-values are 

less than the a-priori determined significance level of 0.10, we conclude that there is 

statistical evidence that the response for the GCEITF group is different from that in the 

total Marine Corps Population. 

Table Q-9. Significant Male PFT Score Comparisons by MOS

Male PFT

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

0331 13 237.00 27.61 181.0 243.0 281.0 1532 263.84 25.69 159.0 271.0 300.0 < 

0.01*

0811 35 239.06 34.67 165.0 246.0 294.0 1179 254.45 27.38 136.0 259.0 300.0 < 

0.01*

1371 19 244.58 34.09 194.0 247.0 300.0 1876 255.41 28.03 138.0 261.0 300.0 0.09*

Table Q-10. GCEITF Female PFT Score Compared to Female Population PFT Score

Female

All MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

DOR incl 104 275.72 20.03 211.00 280.00 300.00 6419 255.51 31.36 125 263 300 < 

0.01*

Table Q-11. Significant Female PFT Score Comparisons by MOS

Female PFT

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

1371 9 281.89 14.59 253 285 300 123 259.95 31.18 160 266 300 0.08*
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Figure Q-13. PFT by Population for Males MOS 0331

Figure Q-14. PFT by Population for Males MOS 0811
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Figure Q-15. PFT by Population for Males MOS 1371

Figure Q-16. PFT by Population for Females
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Figure Q-17. PFT by Population for Females MOS 1371

There is no statistically significant difference in PFT score between males in the 

GCEITF when compared to males in the total Marine Corps Population. The following 

MOSs had statistically significant differences:

• 0331 GCEITF males’ average PFT score was 237 and the average PFT score for 

males in the Marine Corps 0331 population was 263.83. The GCEITF males’ 

average PFT score was statistically significantly lower, by approximately 27 

points.

• 0811 GCEITF males’ average PFT score was 239.06 and the average PFT score 

for males in the Marine Corps 0811 population was 254.45. The GCEITF males’ 

average PFT score was statistically significantly lower, by approximately 15 

points.

• 1371 ITF males’ average PFT score was 244.58 and the average PFT score for 

males in the Marine Corps 1371 population was 255.41. The GCEITF males’ 

average PFT score was statistically significantly lower, by approximately 11 

points.

The average PFT score of the GCEITF female was 275.72 and the average PFT score 

of a female in the Marine Corps Population was 255.51. Based on the p-value of the 

K-S test being greater than 0.10, this difference is statistically significant. The GCEITF

females’ PFT scores were statistically significantly higher than the females in the Marine 

Corps Population, by approximately 20 points. The following MOS had a statistically 

significant difference:

• 1371 GCEITF females’ average PFT score was 281.89 and the average PFT 

score for females in the Marine Corps 1371 population was 259.95. The GCEITF
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females’ average PFT score was statistically significantly higher, by 

approximately 22 points.

Q.4.2.7 PFT Crunches

There is no statistically significant difference in PFT crunches between Marines in the 

GCEITF when compared to the total Marine Corps Population. There are no statistically 

significant differences in any of the MOS-to-MOS comparisons. 

Q.4.2.8 PFT Run time

Table Q-12 through Q-14 below display the results from the comparisons of the PFT run 

times of the male and female GCEITF Volunteers to that of the total Marine Corps 

Population given the same parameters. The tables display non-parametric KST results 

and p-values suggesting statistical significance. Figure Q-18 through Q-20 are density 

plots that display the density of calculated values in a shape. If p-values are less than 

the a-priori determined significance level of 0.10, we conclude that there is statistical 

evidence that the response for the GCEITF group is different from that in the total 

Marine Corps population. 

Table Q-12. Significant Male Run Time Comparison by MOS

Male Run Time (minutes)

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

1812 19 23.91 1.93 20.20 24.00 29.00 367 22.48 2.03 17.22 22.35 30.25 <0.01*

Table Q-13. GCEITF Female Run Time Compared to Female Population Run Time

Female

All MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

103 23.79 2.20 19.3 23.67 30.7 6397 25.76 2.55 17.55 25.70 40.98 <.01*

Table Q-14. Significant Female Run Time Comparison by MOS

Female

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

1371 9 22.99 1.34 20.53 23.43 24.67 121 25.27 2.55 19.85 25.25 32.67 <0.01*
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Figure Q-18. PFT Run Time by Population for Males MOS 1812

Figure Q-19. PFT Rum time by Population for Females
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Figure Q-20. PFT Run Time by Population for Females MOS 1371

There is no statistically significant difference in PFT run times between males in the 

GCEITF when compared to males in the Marine Corps Population. The following MOSs 

had statistically significant differences:

• 1812 GCEITF males’ average PFT run time was 23.91 minutes and the average

PFT run time for males in the Marine Corps 1812 population was 22.48 minutes. 

The GCEITF males’ average PFT run time was statistically significantly slower, 

by approximately 1:25.

The average PFT run time of the GCEITF female was 23.79 minutes and the average 

PFT run time of a female in the Marine Corps Population was 25.76 minutes. Based on 

the p-value of the K-S test being greater than 0.10, the difference is statistically

significant and faster, on average, by approximately 2 minutes. The following MOSs 

had statistically significant differences:

• 1371GCEITF females’ average PFT run time was 22.99 minutes and the average

PFT run time for females in the Marine Corps 1371 population was 25.72. The 

GCEITF Marines’ average PFT run time was statistically significantly faster.

Q.4.2.9 Combat Fitness Test (CFT) score

Table Q-15 through Q-17 below display the results for comparing the CFT scores of the 

male and female GCEITF Volunteers to that of the total Marine Corps Population given 

the same parameters. The tables display non-parametric KST results and p-values 

suggesting statistical significance. Figure Q-21 through Q-26 are density plots that 

display the density of calculated values in a shape. If p-values are less than the a-priori 

determined significance level of 0.10, we conclude that there is statistical evidence that 
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AUGUST 2015 Q-22

the response for the GCEITF group is different from that in the total Marine Corps 

population. 

Table Q-15. GCEITF Male CFT Score Compared to Male Population CFT Score

Male 

All MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

DOR incl 275 287.44 11.19 236.00 290.00 300.00 78567 288.29 11.83 148.00 291.00 300.00 0.04*

Table Q-16. Signficant Male CFT Score Comparisons by MOS 

Male 

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

0311 63 287.41 11.47 258.0 291.0 300.0 9732 290.93 9.99 214.0 294.0 300.0 0.04*

0341 18 284.56 10.33 261.0 287.5 297.0 1580 291.42 10.27 157.0 294.0 300.0 0.01*

0811 35 285.49 9.69 262.0 286.0 300.0 1185 288.59 10.76 226.0 291.0 300.0 0.06*

1371 19 283.68 11.35 265.0 283.0 300.0 1872 289.20 10.71 222.0 292.0 300.0 0.02*

Table Q-17. GCEITF Female CFT Score Compared to Female Population CFT Score

Female

All 

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

DOR 

incl 103 292.98 8.37 266 297 300 6476 286.83 13.17 143 290 300 < 0.01*
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Figure Q-21. CFT by Population for Males

Figure Q-22. CFT by Population for Males MOS 0311
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AUGUST 2015 Q-24

Figure Q-23. CFT by Population for Males MOS 0341

Figure Q-24. CFT by Population for Males MOS 0811
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Q-25 AUGUST 2015

Figure Q-25. CFT by Population for Males MOS 1371

Figure Q-26. CFT by Population for Females

The average CFT score of the GCEITF male was 287.44 and the average CFT score of 

a male in the Marine Corps Population was 288.29. Based on the p-value of the K-S 

test being greater than 0.10, the difference is statistically significant and better, on 

average, by approximately 1 point. The following MOSs had statistically significant 

differences:
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• 0311 GCEITF males’ average CFT score was 284.56 and the average CFT 

score for males in the Marine Corps 0311 population was 290.42. The GCEITF

males’ average CFT score was statistically significantly lower, by approximately 4 

points.

• 0341 GCEITF males’ average CFT score was 287.41 and the average CFT 

score for males in the Marine Corps 0341 population was 290.93. The GCEITF

males’ average CFT score was statistically significantly lower, by approximately 4 

points.

• 0811 GCEITF males’ average CFT score was 285.49 and the average CFT 

score for males in the Marine Corps 0811 population was 288.59. The GCEITF

males’ average CFT score was statistically significantly lower, by approximately 3 

points.

• 1371 GCEITF males’ average CFT score was 283.68 and the average CFT 

score for males in the Marine Corps 1371 population was 289.20. The GCEITF

males’ average CFT score was statistically significantly lower, by approximately 6 

points.

The average CFT score of the GCEITF female was 292.98 and the average CFT 

score of a female in the Marine Corps Population was 286.83. Based on the p-value 

of the K-S test being greater than 0.10, there is a statistically significant difference 

between the two groups. The GCEITF females’ CFT scores are higher, on average, 

by approximately 6 points. There are no statistically significant differences in any of 

the MOS-to-MOS comparisons. 

Q.4.2.10 CFT Maneuver Under Fire (MUF) time

Table Q-18 through Q-20 below display the results for the comparisons of the CFT MUF 

time of the male and female GCEITF Volunteers to that of the total Marine Corps 

Population given the same parameters. The tables display non-parametric KST results 

and p-values suggesting statistical significance. Figure Q-27 through Q-31 are density 

plots that display the density of calculated values in a shape. If p-values are less than 

the a-priori determined significance level of 0.10, we conclude that there is statistical 

evidence that the response for the GCEITF group is different from that in the total 

Marine Corps population. 

Table Q-18. GCEITF Male MUF Time Compared to Male Population MUF Time

Male 

All MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

DOR incl 275 2.44 0.31 1.80 2.40 3.75 78688 2.40 0.32 1.08 2.37 8.00 0.06*
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Table Q-19. Significant Male MUF Time Comparisons by MOS

Male 

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

0311 63 2.44 0.34 1.8 2.4 3.8 9738 2.32 0.29 1.5 2.3 5.3 <0.01*

0341 18 2.48 0.23 2.0 2.5 2.9 1582 2.32 0.31 1.6 2.3 8.0 <0.01*

1371 19 2.58 0.30 1.9 2.6 3.0 1876 2.37 0.28 1.7 2.3 3.8 <0.01*

Table Q-20. GCEITF Female MUF Time Compared to Female Population MUF Time

Female

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

DOR incl 103 3.09 0.42 2.2 3.08 4.1 6489 3.27 0.47 2 3 7 <0.01*

Figure Q-27. CFT MUF by Population for Males
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Figure Q-28. CFT MUF by Population for Males MOS 0311

Figure Q-29. CFT MUF by Population for Males MOS 0341
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Figure Q-30. CFT MUF by Population for Males MOS 1371

Figure Q-31. CFT MUF by Population for Females

The average CFT MUF time of the GCEITF male was 2.44 minutes and the average 

CFT MUF time of a male in the Marine Corps Population was 2.4 minutes. Based on 

the p-value of the K-S test being less than 0.10, this difference is statistically significant. 

The GCEITF males’ CFT MUF times were statistically significantly slower than the

males in the Marine Corps Population times, by approximately 2 seconds. The 

following MOSs had statistically significant differences:

• 0311 GCEITF males’ average CFT MUF time was 2.44 minutes and the average

CFT MUF time for males in the Marine Corps 0311 population was 2.32 minutes. 
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AUGUST 2015 Q-30

The GCEITF males’ average CFT MUF time was statistically significantly slower, 

by approximately 7 seconds.

• 0341 GCEITF males’ average CFT MUF time was 2.48 minutes and the average

CFT MUF time for males in the Marine Corps 0341population was 2.32 minutes. 

The GCEITF males’ average CFT MUF time was statistically significantly slower, 

by approximately 9 seconds.

• 1371 GCEITF males’ average CFT MUF time was 2.58 minutes and the average

CFT MUF time for males in the Marine Corps 1371population was 2.37 minutes. 

The GCEITF males’ average CFT MUF time was statistically significantly slower, 

by approximately 12 seconds.

The average CFT MUF time of the GCEITF female was 3.09 minutes and the 

average CFT MUF time of a female in the Marine Corps Population was 3.27 

minutes. Based on the p-value of the K-S test being less than 0.10, this difference is 

statistically significant. The GCEITF females’ CFT MUF times were statistically 

significantly faster than for females in the Marine Corps Population, by 

approximately 11 seconds. There are no statistically significant differences in any of 

the MOS-to-MOS comparisons. 

Q.4.2.11 CFT Movement to Contact (MTC) time

Table Q-21 and Q-22 below display the results for comparing the CFT MTC time of the 

male and female GCEITF volunteers to that of the Marine Corps population given the 

same parameters. The tables display non-parametric KST results and p-values 

suggesting statistical significance. Figure Q-32 through Q-35 are density plots that 

display the density of calculated values in a shape. If p-values are less than the a-priori 

determined significance level of 0.10, we conclude that there is statistical evidence that 

the response for the GCEITF group is different from that in the total Marine Corps 

population. 

Table Q-21. Significant Male CFT MTC Time Comparison by MOS

Male 

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

0341 18 3.08 0.27 2.7 3.0 3.8 1582 2.85 0.29 1.8 2.8 4.4 <0.01*

0811 35 3.02 0.30 2.0 3.1 3.6 1187 2.91 0.30 2.0 2.9 4.0 <0.01*

PI&PMG 54 2.85 0.23 2.3 2.9 3.5 57863 2.94 0.30 1.8 2.9 6.6 0.03*
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-31 AUGUST 2015

Table Q-22. GCEITF Female CFT MTC Time Compared to Female Population CFT MTC Time

Female

All 

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

DOR 

incl 103 3.43 0.30 2.8 3.42 4.3 6497 3.63 0.39 2.0 3.62 9.4 <0.01*

Figure Q-32. CFT MTC by Population for Males MOS 0341

Figure Q-33. CFT MTC by Population for Males MOS 0811
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-32

Figure Q-34. CFT MTC by Population for Males PI & PMG

Figure Q-35. CFT MTC by Population for Females

There is no statistically significant difference in CFT MTC times between male Marines 

in the GCEITF when compared to the males in the Marine Corps population. The 

following MOSs had statistically significant differences:

• 0341 GCEITF males’ average CFT MTC time was 3.08 minutes and the average 

CFT MTC time for males in the Marine Corps 0341 population was 2.85 minutes. 

The GCEITF males’ average CFT MTC time was statistically significantly slower 

by approximately 25 seconds.
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-33 AUGUST 2015

• 0811 GCEITF males’ average CFT MTC time was 3.02 minutes and the average 

CFT MTC time for males in the Marine Corps 0811 population was 2.91 minutes. 

The GCEITF males’ average CFT MTC time was statistically significantly slower 

by approximately 7 seconds.

• PI & PMG GCEITF males’ average CFT MTC time was 2.85 minutes and the 

average CFT MTC time for males in the Marine Corps PI & PMG population was

2.94 minutes. The GCEITF males’ average CFT MTC time was statistically 

significantly faster by approximately 5 seconds.

The average CFT MTC time of the GCEITF female was 3.43 minutes and the 

average CFT MTC time of a female in the Marine Corps Population was 3.63 

minutes. Based on the p-value of the K-S test being less than 0.10, this difference is 

statistically significant. The GCEITF females’ CFT MTC times were statistically 

significantly faster than for females in the Marine Corps Population, by 

approximately 12 seconds. There are no statistically significant differences in any of 

the MOS-to-MOS comparisons. 

Q.4.2.12 Rifle Range Score

Table Q-23 and Q-24 below display the results from the comparison of the Rifle Range 

score of the male GCEITF Volunteers to that of the total Marine Corps Population given 

the same parameters. The tables display non-parametric KST results and p-values 

suggesting statistical significance. Figure Q-36 through Q-40 are density plots that 

display the density of calculated values in a shape. If p-values are less than the a-priori 

determined significance level of 0.10, we conclude that there is statistical evidence that 

the response for the GCEITF group is different from that in the total Marine Corps 

population. 

Table Q-23. Significant Male Rifle Range Comparisons by MOS

Male 

MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

0311 65 303.55 23.27 193.0 311.0 334.0 9759 307.19 24.01 85.0 311.0 348.0 0.04*

0341 18 291.89 35.34 183.0 303.0 323.0 1591 304.92 26.41 116.0 309.0 345.0 0.07*

0811 35 300.17 14.43 250.0 299.0 324.0 1195 304.33 26.38 135.0 309.0 345.0 0.02*

PI&PMG 55 293.38 23.61 179.0 296.0 333.0 58352 306.71 21.66 47.0 310.0 347.0 < 

0.01*
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-34

Table Q-24. GCEITF Male Rifle Range Compared to Male Population Rifle Range

Male 

All MOS

GCEITF USMC KS 

Test

N Mean SD Min Median Max N Mean SD Min Median Max Pvalue

DOR incl 278 299.95 25.10 162.00 303.00 342.00 79189 306.83 22.31 47.00 310.00 349.00 < 

0.01*

Figure Q-36. Rifle Range by Population for Males

Figure Q-37. Rifle Range by Population for Males MOS 0311
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-35 AUGUST 2015

Figure Q-38. Rifle Range by Population for Males MOS 0341

Figure Q-39. Rifle Range by Population for Males MOS 0811
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-36

Figure Q-40. Rifle Range by Population for Males MOS PI & PMG

The average Rifle Range score for the GCEITF male was 299.95 and the average Rifle 

Range score for a male in the Marine Corps Population was 306.83. Based on the 

p-value of the K-S test being less than 0.10, this difference is statistically significant. 

The GCEITF males’ Rifle Range scores were statistically significantly less than the total

Marine Corps population, by approximately 7 points. The following MOSs had 

statistically significant differences:

• 0311 GCEITF males’ average Rifle Range score was 303.55 and the average

Rifle Range score for males in the Marine Corps 0311 population was 307.19. 

The GCEITF males’ average Rifle Range score was statistically significantly 

lower, by approximately 4 points.

• 0341 GCEITF males’ average Rifle Range score was 291.89 and the average

Rifle Range score for males in the Marine Corps 0341population was 304.92. 

The GCEITF males’ average Rifle Range score was statistically significantly 

lower, by approximately 13 points.

• 0811 GCEITF males’ average Rifle Range score was 300.17 and the average

Rifle Range score for males in the Marine Corps 0811 population was 304.33. 

The GCEITF males’ average Rifle Range score was statistically significantly 

lower, by approximately 4 points.

• PI and PIMG GCEITF males’ average Rifle Range score was 293.38 and the 

average Rifle Range score for males in the Marine Corps open MOS population 

was 306.71. The GCEITF males’ average Rifle Range score was statistically 

significantly lower, by approximately 13 points.

There is no statistically significant difference in Rifle Range scores between females 

in the GCEITF when compared to females in the Marine Corps Population. There 
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-37 AUGUST 2015

are no statistically significant differences in any of the female MOS-to-MOS 

comparisons. 

Q.5 Insights 

• Female Marines inclined to volunteer for closed MOSs perform better, on 

average, when compared to the female Marine Corps population on the following 

physical tests: overall PFT score, PFT crunches, Overall CFT score, and MUF

time.

• Females Combat Engineers (MOS 1371) inclined to volunteer for assignment to 

closed units perform better, on average, when compared to the female Marine 

Corps population on the following cognitive and physical tests: AFQT score, 

overall PFT score, and PFT crunches. 
FOR OFFICIAL USE ONLY 

This document constitutes pre-decisional, deliberative opinion and recommendations. 

Not releasable under FOIA pursuant to 5 U.S.C. 552 (b) (5).

Appendix to Annex Q

GCEITF Population

This appendix describes the population of the GCEITF volunteers when compared to 

today’s Marine Corps Active Component who possess the same parameters as the 

GCEITF population, i.e. E-1 to E-5s, full duty medical status. The appendix presents 

the full Descriptive Statistics and interpretive results. 

Q.1 GCEITF Population Parameters and Personnel Variables 

The ability to generalize the results of the GCEITF experiment to the wider Marine 

Corps is, in part, dependent upon how representative the GCEITF participants were of 

the total population of Marines. 

The comparisons made between the GCEITF volunteer sample and the Marine Corps 

total active component population were done using the same parameters to include:

• The total Marine Corp’s population was defined using the Active Component 

whereas the GCEITF sample contains both Active and Reserve Component 

Marines. The decision to use the Marine Corp’s Active Component as the basis 

for comparison was a conservative one that embodies the idea that Reserve 

Marines are equal to Active Marines. This assumption is reasonable because 

Reserve Marines are required to maintain Marine Corps standards and could be 

activated at any time to serve on a continuous basis with their Active Duty 

counterparts. This approach is conservative due to the most likely direction of 

error in the assumption. If reserve Marines were believed to be inferior to active 

Marines, then the basis of comparison (the active Marine Corps) would be 

superior to the GCEITF (source from the active and reserve components). Thus, 

if this analysis concludes that the sample (GCEITF) was representative of the 

population (the active component), then the sample will have attained the higher 

standard to which the experiment’s results could be generalized.

• Pay grade of E-5 and below

• Full-duty status (i.e., not currently on limited/light duty, or pending physical 

evaluation board)

• For MOS to MOS comparisons, Marines must hold the same Primary MOS 

(PMOS). MOS-MOS comparisons were done by gender (ie. Female 1371 

Combat Engineers within the GCEITF were compared to female Marines who 

also possess the 1371 PMOS within the total Marine Corps given the same 

parameters; Male PI and PIMG Marines were compared to male open MOS 

Marines within the total Marine Corps given the same parameters)
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-2 

From this point on, this annex will refer to the Marine Corps’ total Active Component 

population used for comparison as the total Marine Corps Population.

The GCEITF population encompassed all the volunteers who actively participated in the 

experiment. While the number of volunteers was in constant flux, the maximum active 

participation by volunteers at any one time was 382 (278 Males/ 104 females). 

Furthermore, the comparisons between the GCEITF volunteer sample and the Marine 

Corps total active component population were based on variables that are common 

among all Marines regardless of gender. The tables and graphs present the mean of 

each variable. While the PFT/CFT score used in the comparisons are gender-normed, 

the component scores of PFT and CFT events that are continuous and/or gender 

neutral (i.e. run times (continues time captured), crunch score (where 100 is the 

maximum score regardless of gender) were used to give greater insight into the 

individual personnel variables of the Marine within the two groups. The 12 personnel 

variables used include:

• Age

• Height

• Weight

• AFQT

• GT

• PFT, Total Score

• PFT, Crunches

• PFT, Run Time

• CFT, Total Score

• CFT, Movement to Contact

• CFT, Maneuver under Fire

• Rifle Range Score

All comparisons given for the below personnel variables are done so between the 

GCEITF population and the Marine Corps population in the aggregate and by PMOS. 

All GCEITF Marines who maintain open MOSs and performed the Provisional Infantry 

(PI) and Provisional Machine Gun (PMG) were compared to the total Marine Corps 

Population of currently Open MOSs. For each of the 12 personnel variables, a total of 

15 comparisons were made. Males were compared to males in the aggregate (GCEITF

to Total Marine Corps Population) and by the 9 closed MOSs, by MOS 1371, and by PI 

& PMG to open MOSs. Females were compared to females in the aggregate (GCEITF
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-3 AUGUST 2015

to Total Marine Corps Population), by MOS 1371, and then by PI & PMG to open 

MOSs. A total of 180 comparisons were made.

Q.1.1 Age

This personnel variable defines the age, specified in years, of the population. 

Q.1.1.1 Age (Male Marines)

Table Q-1 compares male Marines within the GCEITF to all male Marines within the 

total Marine Corps Population and by MOS. 

Table Q-1. Male Age Comparisons

Male Age

All MOS GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

278 22.45 2.45 18.80 21.85 31.60 79212 23.03 3.03 17.40 22.30 47.10 0.02*

Male Age

MOS (w/ DOR) GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0300 0 131 22.84 3.27 17.40 22.70 32.50

0311 65 22.78 2.80 18.80 22.10 31.60 9766 22.30 2.77 18.10 21.70 47.10 0.15

0313 14 23.29 2.05 20.60 22.55 27.60 447 22.96 2.74 18.80 22.40 31.60 0.54

0321 0 318 23.86 2.95 18.70 23.60 36.00

0331 13 22.03 2.59 19.50 21.00 28.40 1550 22.83 3.09 18.50 22.10 36.70 0.62

0341 18 22.77 2.27 20.40 22.10 27.80 1591 22.60 3.09 18.40 21.80 38.70 0.13

0351 4 23.80 2.74 19.80 24.70 26.00 713 22.67 3.11 18.60 21.80 37.90 0.26

0352 16 21.71 1.61 20.00 21.25 25.60 790 23.35 3.24 18.50 22.60 36.30 0.07*

0372 0 138 27.32 2.51 22.80 27.00 36.80

0800 0 60 21.93 2.84 18.50 21.80 30.80

0811 35 22.63 2.62 18.90 21.90 28.80 1195 22.69 2.93 18.50 22.00 35.50 0.96

0842 0 168 21.99 2.38 18.80 21.25 29.80

0844 0 324 22.66 2.92 18.40 22.00 38.50

0847 0 121 22.53 2.38 19.20 22.20 31.70

0861 0 250 22.88 2.55 18.60 22.45 30.70

1371 19 22.78 3.29 19.10 21.90 30.00 1890 22.61 3.13 18.50 21.75 40.30 0.99

1800 0 24 20.27 1.98 18.50 19.50 25.70

1812 19 23.12 2.08 19.80 22.90 27.20 379 22.87 2.78 18.70 22.00 34.20 0.05*

1833 20 21.99 2.00 19.10 21.60 26.30 906 23.10 3.18 18.40 22.20 39.80 0.30

8011 0 18 20.43 2.35 18.60 19.60 28.20

8972 0 65 22.11 2.35 18.60 21.50 31.80

PI&PMG 55 21.69 2.01 19.40 20.90 28.00 58368 23.18 3.04 17.70 22.50 44.40 < 0.01*
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-4 

Q.1.1.1.1 Age (Male Marines) Results

The average age of the GCEITF male Marines was 22.45 years old compared to the 

average age of male Marines within the total Marine Corps Population which is 23.03 

years old. Based on the p-value of the K-S test being less than .10, this age difference 

is statistically significant. The GCEITF male Marines were statistically significantly 

younger than the USMC total population by approximately six months. Additionally, the 

following MOSs had statistically significant differences:

• 0352 GCEITF male Marines average age was 21.71 years old compared to the 

average Marine Corps 0352 population which is 23.35 years old. The GCEITF

Marines were statistically significantly younger, by approximately twenty months.

• 1812 GCEITF male Marines average age was 23.12 years old compared to the 

average Marine Corps 1812 population which is 22.87 years old. The GCEITF

Marines were statistically significantly older, by approximately 3 months.

• PI & PIMG GCEITF male Marines average age was 21.69 years old compared to 

the average Marine Corps open MOS population which is 23.18 years old. The 

GCEITF Marines were statistically significantly younger, by approximately 

eighteen months.

Q.1.1.2 Age (Female Marines)

Table Q-2 compares female Marines within the GCEITF to all female Marines within the 

total Marine Corps Population. Table Q-2 compares the 1371 Combat Engineer female 

Marines within the GCEITF to female 1371 Combat Engineers within the total Marine 

Corps Population and the PI and PMG GCEITF Marines to the total Marine Corps’ open 

MOS female Population

Table Q-2. Female Age Comparisons

Female Age 

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

 104 22.69 2.93 18.4 21.95 33.9 6631 22.77 2.87 18.1 22.10 38.9 0.77

 

Female Age 

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0311 12 21.28 2.38 18.9 20.40 25.8 0 

0313 7 19.57 0.93 18.4 19.50 20.8 0 

0331 9 23.19 2.82 20.1 22.70 28.4 0 

0341 8 23.38 4.36 21.2 21.60 33.9 0 

0351 3 21.47 1.56 19.8 21.70 22.9 0 

0352 4 24.60 2.72 21.8 24.25 28.1 0 
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-5 AUGUST 2015

Female Age 

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0811 15 23.99 2.86 20.0 24.10 28.7 0 

1371 9 22.32 2.53 19.1 22.20 26.6 124 22.06 2.57 18.5 21.40 29.2 0.53

1812 4 23.70 1.53 21.9 23.85 25.2 0 

1833 12 22.93 2.72 19.6 22.80 27.9 0 

8000 0 1 22.40 22.4 22.40 22.4 

8011 0 5 20.52 3.41 18.7 19.20 26.6 

8972 0 8 21.83 3.18 18.5 20.50 27.2 

PI&PMG 21 22.79 3.11 19.0 21.60 30.1 6491 22.79 2.88 18.1 22.10 38.9 0.98

Q.1.1.2.1 Age (Female Marines) Results

The average age of the GCEITF female Marines was 22.69 years old compared to the 

average age of female Marines within the total Marine Corps Population which is 22.77 

years old. Based on the p-value of the K-S test being greater than .10, there is no 

statistically significant difference between the two groups. Additionally, there are no 

statistically significant differences in any of the MOS-MOS comparisons. 

Q.1.2 Height

This personnel variable defines the height, specified in inches, of the population. 

Q.1.2.1 Height (Male Marines)

Table Q-3 compares male Marines within the GCEITF to all male Marines within the 

total Marine Corps Population and by MOS. 

Table Q-3. Male Height Comparisons

Male Height

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

 278 69.58 2.56 64.00 69.00 77.00 79197 69.49 2.72 58.00 69.00 84.00 0.98

Male Height

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0300 0 131 69.59 2.70 62 70.0 77 

0311 65 69.15 2.62 64 69.0 75 9765 69.47 2.69 60 69.0 80 0.99

0313 14 70.07 2.87 65 69.5 76 447 69.50 2.70 63 69.0 77 1.00

0321 0 318 70.53 2.35 62 70.0 78 

0331 13 71.69 2.56 68 71.0 76 1550 70.42 2.67 59 71.0 80 0.74

0341 18 68.83 2.20 65 69.5 73 1589 69.49 2.57 59 69.0 79 0.24 
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-6 

Male Height

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0351 4 69.50 3.32 67 68.5 74 713 69.90 2.69 62 70.0 80 0.84

0352 16 69.31 2.02 66 69.5 73 789 69.98 2.58 63 70.0 79 0.87

0372 0 136 71.10 2.40 65 71.0 77 

0800 0 60 69.07 2.97 62 69.0 76 

0811 35 69.89 2.69 65 70.0 77 1194 69.21 2.72 60 69.0 78 0.86

0842 0 168 69.84 2.69 65 70.0 78 

0844 0 324 69.65 2.87 59 69.0 77 

0847 0 121 69.75 2.84 63 70.0 76 

0861 0 250 69.76 2.44 63 70.0 78 

1371 19 69.68 2.26 65 69.0 74 1890 69.53 2.74 61 70.0 79 0.51

1800 0 24 69.17 2.78 63 70.0 74 

1812 19 69.42 2.80 64 70.0 76 379 69.37 2.81 62 69.0 77 1.00

1833 20 69.75 2.38 65 70.0 73 906 69.52 2.81 61 69.0 79 0.96

8011 0 18 68.33 2.00 64 68.5 71 

8972 0 65 70.06 2.57 65 70.0 75 

PI&PMG 55 69.55 2.51 64 69.0 75 58360 69.45 2.73 58 69.0 84 0.94

Q.1.2.1.1 Height (Male Marines) Results

The average height of the GCEITF male Marines was 69.58 inches tall compared to the 

average height of male Marines within the total Marine Corps Population which is 69.49 

inches tall. Based on the p-value of the K-S test being greater than .10, there is no 

statistically significant difference between the two groups. Additionally, there are no 

statistically significant differences in any of the MOS-MOS comparisons. 

Q.1.2.2 Height (Female Marines)

Table Q-4 compares female Marines within the GCEITF to all female Marines within the 

total Marine Corps Population. Table 4 compares the 1371 Combat Engineer female 

Marines within the GCEITF to female 1371 Combat Engineers within the total Marine 

Corps Population and the PI and PMG GCEITF Marines to the total Marine Corps’ open 

MOS female Population. 

Table Q-4. Female Height Comparisons

Female Height

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

 104 64.40 2.31 59.00 64.00 71.00 6628 64.19 2.56 56.00 64.00 75.00 0.60
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-7 AUGUST 2015

Female Height

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0311 12 65.67 2.46 62 65.5 71 0 

0313 7 64.14 1.46 63 64.0 67 0 

0331 9 65.44 2.24 63 66.0 69 0 

0341 8 64.13 3.76 59 64.0 71 0 

0351 3 63.00 1.00 62 63.0 64 0 

0352 4 63.25 1.50 62 63.0 65 0 

0811 15 64.27 2.15 59 64.0 67 0 

1371 9 64.11 1.76 60 65.0 66 124 64.17 2.21 59 64.0 70 0.98

1812 4 64.75 2.22 62 65.0 67 0 

1833 12 64.92 2.54 62 64.5 70 0 

8000 0 1 62.00 62 62.0 62 

8011 0 5 64.00 3.00 61 63.0 69 

8972 0 8 64.63 1.60 63 64.5 67 

PI&PMG 21 63.71 2.12 59 64.0 67 6488 64.19 2.57 56 64.0 75 0.67

Q.1.2.2.1 Height (Female Marines) Results

The average height of the GCEITF female Marines was 64.40 inches compared to the 

average height of female Marines within the total Marine Corps Population, which is 

64.19 inches. Based on the p-value of the K-S test being greater than 0.10, there is no 

statistically significant difference between the two groups. Additionally, there are no 

statistically significant differences in any of the MOS-MOS comparisons. 

Q.1.3 Weight

This personnel variable defines the weight, specified in pounds, of the population. 

Q.1.3.1 Weight (Male Marines)

Table Q-5 compares male Marines within the GCEITF to all male Marines within the 

total Marine Corps Population and by MOS. 

Table Q-5. Male Weight Comparisons

Male Weight

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

278 169.79 22.92 117.00 170.00 246.00 79198 172.36 23.46 92.00 172.00 295.00 0.08*
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-8 

Male Weight

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0300 0 131 170.99 23.02 113.0 170.0 228.0 

0311 65 168.06 23.69 129.0 166.0 220.0 9765 170.09 22.97 92.0 169.0 280.0 0.99

0313 14 170.86 22.19 132.0 173.0 222.0 447 171.51 22.51 110.0 170.0 244.0 1.00

0321 0 318 179.09 19.23 124.0 180.0 235.0 

0331 13 184.62 31.64 142.0 185.0 246.0 1550 182.17 22.92 112.0 182.0 281.0 0.74

0341 18 165.94 22.35 124.0 168.0 211.0 1590 170.66 22.55 104.0 170.0 265.0 0.27

0351 4 156.00 20.22 129.0 161.5 172.0 713 172.27 23.00 110.0 171.0 250.0 0.84

0352 16 169.50 29.92 127.0 165.0 239.0 789 174.19 22.46 120.0 175.0 265.0 0.87

0372 0 136 188.74 18.59 148.0 189.0 246.0 

0800 0 60 170.12 24.13 112.0 177.5 208.0 

0811 35 173.49 21.50 117.0 171.0 222.0 1194 170.77 23.59 108.0 171.0 271.0 0.86

0842 0 168 169.76 24.31 107.0 166.5 229.0 

0844 0 324 171.12 23.96 113.0 170.0 286.0 

0847 0 121 175.02 27.08 109.0 175.0 270.0 

0861 0 250 173.58 23.59 104.0 174.0 271.0 

1371 19 170.05 25.65 123.0 172.0 222.0 1890 171.75 24.54 102.0 171.0 288.0 0.51

1800 0 24 157.96 24.72 123.0 155.5 219.0 

1812 19 168.53 19.34 141.0 163.0 204.0 379 170.43 23.22 100.0 170.0 259.0 1.00

1833 20 166.25 14.96 128.0 167.5 196.0 906 171.58 23.82 106.0 171.0 277.0 0.96

8011 0 18 161.89 19.75 138.0 158.0 209.0 

8972 0 65 172.98 24.12 129.0 174.0 223.0 

PI&PMG 55 169.67 21.36 131.0 171.0 211.0 58360 172.53 23.48 97.0 172.0 295.0 0.94

Q.1.3.1.1 Weight (Male Marines) Results

The average weight of the GCEITF male Marines was 169.79 lb compared to the 

average weight of male Marines within the total Marine Corps Population which is 

172.36 lb. Based on the p-value of the K-S test being less than 0.10, this difference is 

statistically significant. The GCEITF male Marines were statistically significantly lighter 

than the USMC total population, by approximately 2.5lbs. Additionally, there are no 

statistically significant differences in any of the MOS-MOS comparisons. 

Q.1.3.2 Weight (Female Marines)

Table Q-6 compares female Marines within the GCEITF to all female Marines within the 

total Marine Corps Population. Table 6 compares the 1371 Combat Engineer female 

Marines within the GCEITF to female 1371 Combat Engineers within the total Marine 

Corps Population and the PI and PMG GCEITF Marines to the total Marine Corps’ open 

MOS female Population.
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-9 AUGUST 2015

Table Q-6. Female Weight Comparisons

Female Weight

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

104 135.33 14.39 105.0 135.00 174.0 6628 136.02 16.33 90.0 135.00 249.0 0.74

Female Weight

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0311 12 142.17 17.21 112 147.0 173 0 

0313 7 137 7.59 121 140.0 143 0 

0331 9 145.22 13.42 126 139.0 165 0 

0341 8 130.88 20.77 110 124.0 174 0 

0351 3 132.67 13.65 118 135.0 145 0 

0352 4 133.25 1.89 132 132.5 136 0 

0811 15 137.8 16.17 106 142.0 166 0 

1371 9 130.11 17.81 110 132.0 157 124 135.60 16.44 90 134.5 186 0.98

1812 4 134.75 8.02 127 133.5 145 0 

1833 12 132.08 11.66 110 134.0 155 0 

8000 0 1 109.00 109 109.0 109 

8011 0 5 128.20 8.32 119 129.0 139 

8972 0 8 133.25 13.17 104 134.5 146 

PI&PMG 21 131.52 11.29 105 131.0 149 6488 136.05 16.33 90 135.0 249 0.67

Q.1.3.2.1 Weight (Female Marines) Results

The average weight of the GCEITF female Marines was 135.33 lb compared to the 

average weight of female Marines within the total Marine Corps Population, which is 

136.02 lb. Based on the p-value of the K-S test being greater than 0.10, there is no 

statistically significant difference between the two groups. Additionally, there are no 

statistically significant differences in any of the MOS-MOS comparisons. 

Q.1.4 Armed Forces Qualification Test (AFQT)

This personnel variable defines AFQT as a score specified as a numerical value.

The Armed Forces Qualification Test, or AFQT, consists of the following four sections 

from the Armed Services Vocational Aptitude Battery (ASVAB): Word Knowledge, 

Paragraph Comprehension, Arithmetic Reasoning, and Mathematics Knowledge. The 

scores from these four sections make up the AFQT. 
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-10

Q.1.4.1 AFQT (Male Marines)

Table Q-7 compares male Marines within the GCEITF to all male Marines within the 

total Marine Corps Population and by MOS. 

Table Q-7. Male AFQT Comparisons

Male AFQT

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

277 60.56 19.19 22.00 59.00 99.00 79199 62.63 17.79 4.00 62.00 99.00 0.03*

Male AFQT

MOS

GCEITF USMC KS Test

N Mean SD Median Max N Mean SD Min Median Max P-value

0300 0 131 65.58 19.01 31.0 63.0 99.0 

0311 65 58.78 18.89 31.0 55.0 96.0 9766 59.69 17.73 4.0 59.0 99.0 0.69

0313 14 70.64 20.59 38.0 77.0 95.0 447 59.72 17.74 23.0 56.0 99.0 0.05*

0321 0 318 75.32 14.09 36.0 77.0 99.0 

0331 12 69.08 20.43 32.0 75.5 90.0 1549 61.25 17.33 22.0 61.0 99.0 0.13

0341 18 58.11 21.03 27.0 52.0 92.0 1591 59.62 17.54 16.0 57.0 99.0 0.66

0351 4 74.50 19.05 46.0 83.0 86.0 713 73.16 16.46 31.0 74.0 99.0 0.52

0352 16 74.06 14.27 51.0 77.5 95.0 790 73.06 16.07 23.0 74.0 99.0 1.00

0372 0 138 74.46 13.69 39.0 75.0 99.0 

0800 0 60 57.07 15.10 35.0 54.5 93.0 

0811 35 57.77 18.91 31.0 59.0 99.0 1195 54.05 16.82 16.0 51.0 99.0 0.33

0842 0 168 69.82 13.92 36.0 70.0 97.0 

0844 0 324 69.35 14.31 31.0 69.0 99.0 

0847 0 121 70.76 14.56 36.0 72.0 99.0 

0861 0 250 66.53 13.95 33.0 67.0 99.0 

1371 19 62.26 18.73 35.0 62.0 89.0 1890 59.86 16.67 21.0 59.0 99.0 0.66

1800 0 24 50.33 15.31 32.0 48.5 90.0 

1812 19 51.42 18.88 22.0 50.0 94.0 379 53.83 17.80 10.0 51.0 97.0 0.89

1833 20 61.90 18.27 31.0 69.0 89.0 906 54.93 16.82 20.0 52.0 98.0 0.04*

8011 0 18 64.39 16.37 36.0 66.5 87.0 

8972 0 65 77.32 12.13 46.0 81.0 97.0 

PI&PMG 55 57.96 17.86 28.0 54.0 95.0 58356 63.24 17.73 9.0 63.0 99.0 0.04*

Q.1.4.1.1 AFQT (Male Marines) Results

The average AFQT score of the GCEITF male Marines was 60.56 compared to the 

average AFQT score of male Marines within the total Marine Corps population which is 

62.63. Based on the p-value of the K-S test being less than .10, this difference is 

statistically significant. The GCEITF male Marines had lower scores that were 
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-11 AUGUST 2015

statistically significant when compared to the USMC total population, by approximately 2 

points. Additionally, the following MOSs had statistically significant differences:

• 0313 GCEITF male Marines average AFQT score was 70.64 compared to the 

average Marine Corps 0313 population which had average scores of 59.72. The 

GCEITF Marine’ AFQT scores were statistically significantly greater by 

approximately 11 points.

• 1833 GCEITF male Marines average AFQT score was 61.90 compared to the 

average Marine Corps 1833 population which had average scores of 54.93 The 

GCEITF Marines’ AFQT were statistically significantly greater, by approximately 

7 points.

• PI & PIMG GCEITF male Marines average AFQT score was 57.96 compared to 

the average Marine Corps open MOS population which had average scores of 

63.24. The GCEITF Marines’ AFQT scores were is statistically significantly less, 

by approximately five points.

Q.1.4.2 AFQT (Female Marines)

Table Q-8 compares female Marines within the GCEITF to all female Marines within the 

total Marine Corps Population. Table 8 compares the 1371 Combat Engineer female 

Marines within the GCEITF to female 1371 Combat Engineers within the total Marine 

Corps Population and the PI and PMG GCEITF Marines to the total Marine Corps’ open 

MOS female Population. 

Table Q-8. Female AFQT Comparisons

Female AFQT

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

104 61.66 19.22 10 63 99.0 6630 59.00 17.12 7 57 99 0.13

Female AFQT

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0311 12 59.67 24.82 10 65.5 92 0 

0313 7 54.00 20.61 35 51 96 0 

0331 9 58.89 20.05 22 64 81 0 

0341 8 61.88 16.59 35 61 93 0 

0351 3 69.67 6.66 64 68 77 0 

0352 4 78.00 10.42 70 74.5 93 0 

0811 15 58.67 22.25 31 54 99 0 

1371 9 74.00 17.73 39 75 92 124 60.56 16.86 33 59.5 95 0.04*

1812 4 71.75 10.24 57 75 80 0 
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-12

1833 12 63.75 16.24 38 62 93 0 

8000 0 1 33.00 33 33 33 

8011 0 5 60.40 18.43 43 55 85 

8972 0 8 79.38 4.34 71 81.5 82 

PI&PMG 21 55.95 17.39 32 53 91 6490 58.95 17.12 7 57 99 0.98

Q.1.4.2.1 AFQT (Female Marines) Results

The average AFQT score of the GCEITF female Marines was 61.66 compared to the 

average AFQT score of female Marines within the total Marine Corps Population which

is 59.00. Based on the p-value of the K-S test being greater than .10, there is no 

statistically significant difference between the two groups. However, the following MOS

had statistically significant difference: 

• 1371 GCEITF female Marines average AFQT score was 74.00 compared to the 

average female Marine Corps 1371 population which is 60.56. The GCEITF

Marines’ AFQT scores were statistically significantly greater by approximately 13 

points.

Q.1.5 General Classification Test (GT) 

This personnel variable defines GT as a score specified as a numerical value.

Q.1.5.1 GT (Male Marines)

Table Q-9 compares male Marines within the GCEITF to all male Marines within the 

total Marine Corps Population and by MOS. 

Table Q-9. Male GT Comparisons

Male GT

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

272 106.79 12.17 80.00 106.00 136.00 79207 108.99 11.73 12 108 159 < 0.01*

Male GT

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0300 0 131 111.80 12.86 86 111 151 

0311 62 105.74 12.18 80 103.0 133 9766 106.91 11.67 58 106 148 0.44

0313 14 113.71 12.37 95 113.0 133 447 107.56 11.27 81 106 148 0.30

0321 0 318 118.53 9.48 90 118 148 

0331 13 110.62 13.99 83 114.0 129 1550 108.32 11.36 80 108 150 0.31

0341 18 104.78 13.09 80 107.5 127 1591 106.90 11.46 80 106 154 0.62

0351 4 113.00 9.31 100 115.0 122 713 116.18 11.50 83 116 148 0.88
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0352 16 115.63 7.03 104 115.0 129 790 116.31 10.57 89 116 148 0.74

0372 0 138 118.37 9.56 102 117 151 

0800 0 60 104.68 9.19 89 103 131 

0811 34 103.82 11.33 88 103.5 132 1195 103.47 10.56 77 101 148 0.64

0842 0 168 113.60 8.15 100 112 138 

0844 0 324 113.69 8.13 90 111 142 

0847 0 121 115.84 9.28 102 114 150 

0861 0 250 111.68 8.21 97 110 137 

1371 18 110.17 9.76 93 109.0 126 1890 108.13 10.03 83 107 145 0.96

1800 0 24 100.67 9.12 89 98 126 

1812 19 102.11 10.34 91 100.0 126 379 103.16 11.72 64 101 147 1.00

1833 20 109.05 12.72 89 107.0 130 906 104.26 10.64 82 102 139 0.18

8011 0 18 108.17 10.13 93 110 125 

8972 0 65 119.82 7.67 104 120 139 

PI&PMG 54 104.44 12.47 81 102.0 136 58363 109.33 11.73 12 108 159 0.01*

Q.1.5.1.1 GT (Male Marines) Results

The average GT of the GCEITF male Marines was 106.79 compared to the average GT

of male Marines within the total Marine Corps population which is 108.99. Based on the 

p-value of the K-S test being less than .10, this difference is statistically significant. The 

GCEITF male Marines scored lower and the difference is statistically significant

compared to the USMC total population, by approximately 2.2 points. Additionally, the 

following MOS had a statistically significant difference:

• PI & PIMG GCEITF male Marines average GT score was 104.44 compared to 

the average Marine Corps open MOS population which is 109.33. The GCEITF

Marines’ GT scores were is statistically significantly lower by approximately five 

points.

Q.1.5.2 GT (Female Marines)

Table Q-10 compares female Marines within the GCEITF to all female Marines within 

the total Marine Corps Population. Table 10 compares the 1371 Combat Engineer 

female Marines within the GCEITF to female 1371 Combat Engineers within the total 

Marine Corps Population and the PI and PMG GCEITF Marines to the total Marine 

Corps’ open MOS female Population.

Table Q-10. Female GT Comparisons

Female GT

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

97 104.16 12.58 74.0 104.00 134.0 6631 102.58 10.84 68 102 146 0.20
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-14

Female GT

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0311 9 94.00 13.48 74 92 120 0 

0313 7 99.57 13.34 90 95 126 0 

0331 7 105.57 11.33 83 106 119 0 

0341 8 104.00 10.84 89 104.5 127 0 

0351 3 103.33 4.04 101 101 108 0 

0352 4 113.25 5.38 108 112.5 120 0 

0811 15 103.60 13.52 90 98 134 0 

1371 8 113.50 10.73 95 113 127 124 105.85 9.45 90 105 133 0.19

1812 4 114.75 5.12 108 115.5 120 0 

1833 12 108.83 11.98 92 105.5 131 0 

8000 0 1 92.00 92 92 92 

8011 0 5 100.20 7.95 92 98 110 

8972 0 8 117.38 5.58 111 116 127 

PI&PMG 20 100.00 12.05 83 102 120 6491 102.50 10.85 68 102 146 0.41

Q.1.5.2.1 GT (Female Marines) Results

The average GT of the GCEITF female Marines was 104.16 compared to the average 

GT score of female Marines within the total Marine Corps Population which is 102.58. 

Based on the p-value of the K-S test being greater than .10, there is no statistically 

significant difference between the two groups. Additionally, there are no statistically 

significant differences in any of the MOS-MOS comparisons. 

Q.1.6 Physical Fitness Test (PFT) Score

This personnel variable defines PFT as a score specified as a numerical value.

The PFT score is a composite score of three events: pull-ups (pull-ups or flexed-arm 

hang for females), abdominal crunches, and a 3-mile run. The score is gender-normed 

with a maximum of 300 points awarded to both male and female Marines.

Q.1.6.1 PFT (Male Marines) Score

Table Q-11 compares male Marines within the GCEITF to all male Marines within the 

total Marine Corps Population and by MOS. 

Table Q-11. Male PFT Comparisons

Male PFT

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

273 251.79 29.27 136.00 255.00 300.00 77991 253.55 29.67 116.00 259.00 300.00 0.29
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-15 AUGUST 2015

Male PFT

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0300 0 131 265.91 28.26 175.0 276.0 300.0 

0311 63 258.94 27.59 173.0 266.0 297.0 9670 258.91 26.77 136.0 264.0 300.0 1.00

0313 14 246.57 44.89 136.0 263.5 292.0 441 256.87 27.34 170.0 263.0 300.0 0.65

0321 0 316 279.42 17.34 203.0 285.0 300.0 

0331 13 237.00 27.61 181.0 243.0 281.0 1532 263.84 25.69 159.0 271.0 300.0 < 0.01*

0341 17 256.41 24.73 209.0 258.0 290.0 1569 259.59 26.62 151.0 264.0 300.0 0.91

0351 3 263.33 17.56 245.0 265.0 280.0 708 258.50 28.01 139.0 265.0 300.0 0.99

0352 16 267.50 18.10 240.0 264.5 300.0 784 259.08 26.07 155.0 264.0 300.0 0.48

0372 0 136 282.21 12.54 228.0 284.0 300.0 

0800 0 60 254.55 24.10 186.0 256.0 292.0 

0811 35 239.06 34.67 165.0 246.0 294.0 1179 254.45 27.38 136.0 259.0 300.0 < 0.01*

0842 0 166 247.72 30.66 145.0 250.0 298.0 

0844 0 322 250.18 32.13 139.0 256.0 300.0 

0847 0 120 245.72 29.53 172.0 251.0 294.0 

0861 0 244 254.86 29.39 157.0 261.0 300.0 

1371 19 244.58 34.09 194.0 247.0 300.0 1876 255.41 28.03 138.0 261.0 300.0 0.09*

1800 0 24 258.29 29.14 195.0 262.5 297.0 

1812 18 242.17 29.05 181.0 243.5 286.0 375 252.00 27.33 169.0 256.0 297.0 0.32

1833 20 258.15 21.32 223.0 257.0 293.0 898 254.74 29.72 137.0 260.0 300.0 0.84

8011 0 18 270.67 19.40 232.0 278.0 293.0 

8972 0 65 249.97 27.25 170.0 248.0 292.0 

PI&PMG 55 253.24 23.58 189.0 254.0 299.0 57357 251.76 30.26 116.0 257.0 300.0 0.46

Q.1.6.1.1 PFT Score (Male Marines) Results

The average PFT score of the GCEITF male Marines was 251.79 compared to the 

average PFT score of male Marines within the total Marine Corps Population which is 

253.55. Based on the p-value of the K-S test being greater than .10, this difference is 

not statistically significant. However, the following MOSs had statistically significant 

differences:

• 0331 GCEITF male Marines average PFT score was 237 compared to the 

average Marine Corps 0331 population which is 263.84. The GCEITF Marines’ 

average PFT scores were statistically significantly lower by approximately 27 

points.

• 0811 GCEITF male Marines average PFT score was 239.06 compared to the 

average Marine Corps 0811 population which is 254.45. The GCEITF Marines’ 
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-16

average PFT scores were statistically significantly lower by approximately 15

points.

• 1371 ITF male Marines average PFT score was 244.58 compared to the average 

male Marine Corps 1371 population which is 255.41. The GCEITF Marines’ 

average PFT scores were statistically significantly lower by approximately 11 

points.

Q.1.6.2 PFT (Female Marines) Score

Table Q-12 compares female Marines within the GCEITF to all female Marines within 

the total Marine Corps Population. Table 12 compares the 1371 Combat Engineer 

female Marines within the GCEITF to female 1371 Combat Engineers within the total 

Marine Corps Population and the PI and PMG GCEITF Marines to the total Marine 

Corps’ open MOS female Population.

Table Q-12. Female PFT Comparisons

Female PFT

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

104 275.72 20.03 211.00 280.00 300.00 6419 255.51 31.36 125 263 300 < 0.01*

Female PFT

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0311 12 285.67 13.79 254 288 300 0 

0313 7 273.86 23.37 225 281 293 0 

0331 9 284.78 8.50 272 285 300 0 

0341 8 285.13 8.68 271 287.5 295 0 

0351 3 288.33 12.58 275 290 300 0 

0352 4 286.50 12.92 274 286 300 0 

0811 15 270.47 20.00 238 274 300 0 

1371 9 281.89 14.59 253 285 300 123 259.95 31.18 160 266 300 0.08*

1812 4 281.50 18.27 259 283.5 300 0 

1833 12 273.67 18.66 238 276.5 300 0 

8000 0 1 205.00 205 205 205 

8011 0 5 252.00 27.40 204 264 269 

8972 0 8 266.13 11.37 254 266 287 

PI&PMG 21 260.52 25.01 211 264 300 6280 255.42 31.38 125 262 300 0.83

Q.1.6.2.1 PFT Score (Female Marines) Results

The average PFT score of the GCEITF female Marines was 275.72 compared to the 

average PFT score of female Marines within the total Marine Corps Population which is 
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-17 AUGUST 2015

255.51. Based on the p-value of the K-S test being greater than .10, this difference is 

statistically significant. The GCEITF female Marines’ PFT scores were statistically 

significantly higher than the USMC total population by approximately 20 points. 

Additionally, the following MOS had a statistically significant difference: 

• 1371 GCEITF female Marines’ average PFT score was 281.89 compared to the 

average female Marine Corps 1371 population which is 259.95. The GCEITF

Marines’ average PFT scores were statistically significantly higher by 

approximately 22 points.

Q.1.7 Physical Fitness Test (PFT) Crunches

This personnel variable defines PFT crunches as a total count (quantity of crunches) to 

execute as many crunches as able within a 2 minute time limit during an annual 

physical fitness test. The PFT crunch event during the PFT is scored the same for male 

and female Marines. Each crunch is awarded one point with a total score of 100. 

Q.1.7.1 PFT (Male Marines) Crunches

Table Q-13 compares male Marines within the GCEITF to all male Marines within the 

total Marine Corps Population and by MOS.

Table Q-13. Male PFT Crunches Comparisons

Male PFT Crunches

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

257 98.63 4.76 65 100 100 77075 98.59 5.39 17.00 100.00 100.00 1.00

Male PFT Crunches

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0300 0 130 98.15 7.00 52 100 100 

0311 53 99.89 0.82 94 100 100 9241 99.10 4.30 38 100 100 1.00

0313 14 97.50 9.35 65 100 100 440 99.18 3.74 60 100 100 1.00

0321 0 312 99.48 2.98 63 100 100 

0331 9 98.11 5.67 83 100 100 1458 99.18 3.89 50 100 100 1.00

0341 16 99.25 1.88 94 100 100 1517 99.10 4.61 50 100 100 0.97

0351 3 93.00 12.12 79 100 100 679 99.23 3.73 66 100 100 0.91

0352 16 98.19 5.34 80 100 100 753 99.24 3.96 51 100 100 1.00

0372 0 136 100.00 0.00 100 100 100 

0800 0 58 98.21 4.61 83 100 100 

0811 34 99.09 3.78 80 100 100 1174 99.12 4.14 54 100 100 1.00

0842 0 167 98.41 4.68 74 100 100 

0844 0 317 98.80 4.75 64 100 100 
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-18

0847 0 121 97.96 6.33 64 100 100 

0861 0 233 98.46 5.88 54 100 100 

1371 18 98.11 4.83 85 100 100 1796 99.00 4.32 56 100 100 0.86

1800 0 24 97.04 7.15 76 100 100 

1812 19 97.47 6.59 75 100 100 370 98.41 5.92 50 100 100 0.93

1833 20 99.25 3.35 85 100 100 873 98.60 5.69 50 100 100 1.00

8011 0 18 100.00 0.00 100 100 100 

8972 0 65 99.57 1.50 93 100 100 

PI&PMG 55 98.09 5.19 74 100 100 57193 98.43 5.69 17 100 100 0.96

Q.1.7.1.1 PFT Crunches (Male Marines) Results

The average PFT crunches of the GCEITF male Marines was 98.63 compared to the 

average PFT crunches of male Marines within the total Marine Corps Population which 

is 98.59. Based on the p-value of the K-S test being greater than .10, there is no 

statistically significant difference between the two groups. Additionally, there are no 

statistically significant differences in any of the MOS-MOS comparisons. 

Q.1.7.2 PFT (Female Marines) Crunches

Table Q-14 compares female Marines within the GCEITF to all female Marines within 

the total Marine Corps Population. Table 14 compares the 1371 Combat Engineer 

female Marines within the GCEITF to female 1371 Combat Engineers within the total 

Marine Corps Population and the PI and PMG GCEITF Marines to the total Marine 

Corps’ open MOS female Population.

Table Q-14. Female PFT Crunches Comparisons

Female PFT Crunches

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

103 96.83 7.49 60.0 100.00 100.0 6434 94.62 10.93 35.0 100.00 100.0 0.44

Female PFT Crunches

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0311 12 98.08 6.04 79 100 100 0 

0313 7 94.43 9.73 77 100 100 0 

0331 9 99.89 0.33 99 100 100 0 

0341 8 98.50 3.51 90 100 100 0 

0351 3 100.00 0.00 100 100 100 0 

0352 4 97.75 4.50 91 100 100 0 

0811 14 97.14 6.01 82 100 100 0 

1371 9 97.67 7.00 79 100 100 123 96.49593496 9.804125916 51 100 100 1.00
GCEITF EAR ANNEX Q

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Q-19 AUGUST 2015

1812 4 100.00 0.00 100 100 100 0 

1833 12 95.42 11.96 60 100 100 0 

8000 0 1 65 65 65 65 

8011 0 5 93.8 13.31164903 70 100 100 

8972 0 8 98.375 4.596194078 87 100 100 

PI&PMG 21 94.00 9.30 72 100 100 6295 94.59126291 10.94367908 35 100 100 0.95

Q.1.7.2.1 PFT Crunches (Female Marines) Results

The average PFT crunches of the GCEITF female Marines was 96.83 compared to the 

average PFT crunches of female Marines within the total Marine Corps Population 

which is 94.62. Based on the p-value of the K-S test being greater than .10, there is no 

statistically significant difference between the two groups. Additionally, there are no 

statistically significant differences in any of the MOS-MOS comparisons. 

Q.1.8 Physical Fitness Test (PFT) Run Time

This personnel variable defines PFT run time as total time required to run a 3 mile 

distance during an annual physical fitness test specified as in minutes.

Q.1.8.1 PFT (Male Marines) Run Time

Table Q-15 compares male Marines within the GCEITF to all male Marines within the 

total Marine Corps Population and by MOS.

Table Q-15. Male PFT Run Time Comparisons

Male PFT Run Time (minutes)

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

257 22.30 2.14 17.48 22.17 30.48 76832 22.56 2.39 13.97 22.37 40.98 0.14

Male PFT Run Time (minutes)

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0300 130 21.12 1.82 17.63 20.75 27.10 

0311 53 21.79 1.83 18.37 21.80 26.40 9231 21.99 2.19 15.83 21.80 39.20 0.63

0313 14 22.40 2.73 19.27 21.79 27.83 440 22.39 2.35 16.83 22.13 36.87 0.88

0321 312 20.33 1.72 16.95 20.08 26.23 

0331 9 21.93 1.70 19.92 21.67 24.80 1457 21.63 2.20 13.97 21.38 36.38 0.86

0341 16 22.62 2.69 19.18 21.81 28.30 1516 21.83 2.07 16.38 21.67 29.83 0.59

0351 3 24.03 5.61 20.35 21.25 30.48 678 21.91 2.18 16.53 21.73 36.38 0.90

0352 16 21.51 2.26 18.00 21.27 27.17 752 22.28 2.23 16.37 22.25 27.97 0.10

0372 134 20.64 1.75 16.33 20.50 26.50 

0800 58 22.05 1.75 18.18 21.76 26.92 
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-20

0811 34 22.48 1.93 18.97 22.71 25.97 1168 22.35 2.14 16.83 22.20 35.58 0.35

0842 167 22.35 2.24 18.32 22.05 29.72 

0844 314 22.30 2.26 17.33 22.21 27.60 

0847 121 22.92 2.22 18.68 22.68 28.73 

0861 230 22.28 2.25 16.28 22.18 28.47 

1371 18 22.46 2.19 17.48 22.94 26.83 1794 22.35 2.16 16.20 22.25 31.48 0.73

1800 24 21.22 1.65 18.40 21.07 24.52 

1812 19 23.91 1.93 20.20 24.00 29.00 367 22.48 2.03 17.22 22.35 30.25 <0.01*

1833 20 22.13 1.81 19.13 22.08 25.00 871 22.13 2.11 16.58 22.00 29.90 0.94

8011 18 20.70 1.46 18.80 20.96 23.13 

8972 65 22.85 2.24 18.47 22.70 27.52 

PI&PIMG 55 22.23 1.97 18.00 22.20 27.57 56878 22.75 2.42 14.27 22.57 40.98 0.28

Q.1.8.1.1 PFT Run time (Male Marines) Results

The average PFT run time of the GCEITF male Marines was 22.30 minutes compared 

to the average PFT run time of male Marines within the total Marine Corps Population 

which is 22.56 minutes. Based on the p-value of the K-S test being greater than .10, 

there is no statistically significant difference between the two groups. However, the 

following MOSs had statistically significant differences:

• 1812 GCEITF male Marines average PFT run time was 23.91 minutes compared 

to the average Marine Corps 1812 population which is 22.48 minutes. The 

GCEITF Marines’ average PFT run times were statistically significantly slower, by 

approximately 1:25.

Q.1.8.2 PFT (Female Marines) Run Time

Table Q-16 compares female Marines within the GCEITF to all female Marines within 

the total Marine Corps Population. Table Q-16 compares the 1371 Combat Engineer 

female Marines within the GCEITF to female 1371 Combat Engineers within the total 

Marine Corps Population and the PI and PMG GCEITF Marines to the total Marine 

Corps’ open MOS female Population.

Table Q-16. Female PFT Run Time Comparisons

Female PFT Run Time (minutes)

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

 103 23.79 2.20 19.3 23.67 30.7 6396 25.76 2.55 17.55 25.70 40.98 <.01*

Female PFT Run Time (minutes)

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-21 AUGUST 2015

0311 12 22.88 1.92 19.68 22.97 25.57 

0313 7 23.18 1.12 21.52 23.2 24.62 

0331 9 23.27 1.80 19.33 23.37 25.58 

0341 8 23.07 1.04 21.72 22.87 24.92 

0351 3 22.79 2.25 20.62 22.62 25.12 

0352 4 22.84 1.78 20.97 22.79 24.83 

0811 14 24.54 2.53 20.87 24.49 29.62 

1371 9 22.99 1.34 20.53 23.43 24.67 121 25.27 2.55 19.85 25.25 32.67 <0.01*

1812 4 23.43 3.35 19.38 23.68 27 

1833 12 24.20 1.95 20.07 24.28 27.92 

8000 1 26.33 26.33 26.33 26.33 

8011 5 27.36 1.44 26.02 26.93 29.25 

8972 8 25.27 1.72 23.15 25.14 28.55 

PI&PIMG 21 25.00 2.70 20.1 25.5 30.7 6260 25.77 2.55 17.55 25.72 40.98 0.64

Q.1.8.2.1 PFT Run time (Female Marines) Results

The average PFT run time of the GCEITF female Marines was 23.79 minutes compared 

to the average PFT run time of female Marines within the total Marine Corps Population 

which is 25.76 minutes. Based on the p-value of the K-S test being greater than .10, the

difference is statistically significant difference and faster, on average, by approximately 

two minutes. Additionally, the following MOSs had statistically significant differences:

• 1371GCEITF female Marines average PFT run time was 22.99 minutes 

compared to the average Marine Corps 1371 population which is 25.72. The 

GCEITF Marines’ average PFT run times were statistically significantly faster.

Q.1.9 Combat Fitness Test (CFT) Score

This personnel variable defines CFT as a score specified as a numerical value.

The CFT score is a composite score of three events: Movement to Contact Run (880 

yards), Ammunition Can lifts, Maneuver under Fire. The score is gender-normed with a 

maximum of 300 points awarded to both male and female Marines.

Q.1.9.1 CFT (Male Marines) Score

Table Q-17 compares male Marines within the GCEITF to all male Marines within the 

total Marine Corps Population and by MOS. 

Table Q-17. Male CFT Score Comparisons

Male CFT Score

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

275 287.44 11.19 236.00 290.00 300.00 78567 288.29 11.83 148.00 291.00 300.00 0.04*
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-22

Male CFT Score

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0300 0 127 290.17 12.39 221.0 294.0 300.0 

0311 63 287.41 11.47 258.0 291.0 300.0 9732 290.93 9.99 214.0 294.0 300.0 0.04*

0313 14 285.71 17.18 236.0 289.0 300.0 446 291.07 10.12 233.0 294.0 300.0 0.44

0321 0 316 297.59 5.33 254.0 300.0 300.0 

0331 13 287.46 12.56 256.0 288.0 300.0 1539 293.32 8.29 242.0 296.0 300.0 0.16

0341 18 284.56 10.33 261.0 287.5 297.0 1580 291.42 10.27 157.0 294.0 300.0 0.01*

0351 4 290.25 6.65 282.0 291.0 297.0 706 291.89 9.37 234.0 295.0 300.0 0.65

0352 16 290.06 8.14 273.0 290.5 300.0 784 291.39 9.14 239.0 294.0 300.0 0.84

0372 0 136 298.40 3.25 284.0 300.0 300.0 

0800 0 60 286.25 13.61 249.0 289.5 300.0 

0811 35 285.49 9.69 262.0 286.0 300.0 1185 288.59 10.76 226.0 291.0 300.0 0.06*

0842 0 167 290.54 8.84 257.0 292.0 300.0 

0844 0 322 288.39 10.57 250.0 291.0 300.0 

0847 0 121 286.93 11.99 251.0 289.0 300.0 

0861 0 247 289.29 9.90 253.0 291.0 300.0 

1371 19 283.68 11.35 265.0 283.0 300.0 1872 289.20 10.71 222.0 292.0 300.0 0.02*

1800 0 24 289.33 7.58 273.0 290.0 300.0 

1812 19 287.11 10.68 264.0 291.0 300.0 378 285.71 12.06 234.0 288.0 300.0 0.95

1833 20 292.20 9.18 272.0 295.0 300.0 904 290.71 10.40 234.0 293.0 300.0 0.59

8011 0 18 290.67 9.90 271.0 294.0 300.0 

8972 0 65 290.00 9.83 245.0 292.0 300.0 

PI&PMG 54 288.81 11.48 243.0 293.0 300.0 57838 287.38 12.26 148.0 290.0 300.0 0.19

Q.1.9.1.1 CFT (Male Marines) Score Results

The average CFT score of the GCEITF male Marines was 287.44 compared to the 

average CFT score of male Marines within the total Marine Corps Population which is 

288.29. Based on the p-value of the K-S test being less than .10, the difference is 

statistically significant. The GCEITF male Marines’ CFT scores were statistically lower 

than the USMC total population by approximately 1 point. Additionally, the following 

MOSs had statistically significant differences:

• 0311 GCEITF male Marines average CFT score was 287.41compared to the 

average Marine Corps 0311 population, which is 290.93. The GCEITF Marines’ 

average CFT scores were statistically significantly lower by approximately 3.5

points.
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-23 AUGUST 2015

• 0341 GCEITF male Marines average CFT score was 284.56 compared to the 

average Marine Corps 0341 population which is 291.42. The GCEITF Marines’ 

average CFT scores were statistically significantly lower, by approximately 6.7 

points.

• 0811 GCEITF male Marines average CFT score was 285.49 compared to the 

average Marine Corps 0811 population which is 288.59. The GCEITF Marines’ 

average CFT scores were statistically significantly lower, by approximately 3 

points.

• 1371 GCEITF male Marines average CFT score was 283.68 compared to the 

average Marine Corps 1371 population which is 289.20. The GCEITF Marines’ 

average CFT scores were statistically significantly lower, by approximately 6 

points.

Q.1.9.2 CFT (Female Marines) Score

Table Q-18 compares female Marines within the GCEITF to all female Marines within 

the total Marine Corps Population. Table 18 compares the 1371 Combat Engineer 

female Marines within the GCEITF to female 1371 Combat Engineers within the total 

Marine Corps Population and the PI and PMG GCEITF Marines to the total Marine 

Corps Population. 

Table Q-18. Female CFT Score Comparisons

Female CFT Score

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

103 292.98 8.37 266 297 300 6476 286.83 13.17 143 290 300 < 0.01*

Female CFT Score

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0311 12 292.92 8.74 276 296.5 300 0 

0313 7 291.14 5.96 282 291 299 0 

0331 9 296.33 7.12 279 300 300 0 

0341 8 296.75 4.23 290 299 300 0 

0351 3 299.33 1.15 298 300 300 0 

0352 4 298.50 1.73 297 298.5 300 0 

0811 15 289.73 9.97 272 294 300 0 

1371 9 292.56 10.62 274 300 300 123 288.17 12.82 236 293 300 0.30

1812 4 296.25 4.50 290 297.5 300 0 

1833 12 292.67 7.95 276 295 300 0 

8000 0 1 269.00 269 269 269 

8011 0 5 262.60 13.05 249 260 279 
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-24

8972 0 8 286.00 11.45 271 287.5 300 

PI&PMG 20 290.75 9.51 266 293.5 300 6337 286.83 13.17 143 290 300 0.30

Q.1.9.2.1 CFT (Female Marines) Score Results

The average CFT of the GCEITF female Marines was 292.98 compared to the average 

CFT score of female Marines within the total Marine Corps Population which is 286.83 

Based on the p-value of the K-S test being greater than .10, there is a statistically 

significant difference between the two groups. The GCEITF female Marines’ CFT 

scores are higher, on average, by approximately 6 points. Additionally, there are no 

statistically significant differences in any of the MOS-MOS comparisons. 

Q.1.10 Combat Fitness Test (CFT) MTC

This personnel variable defines CFT Movement to Contact (MTC) run time as total time 

required to run an 880 yard distance during an annual combat fitness test specified as 

in minutes.

Q.1.10.1 CFT (Male Marines) MTC

Table Q-19 compares male Marines within the GCEITF to all male Marines within the 

total Marine Corps Population and by MOS.

Table Q-19. Male CFT MTC Time Comparisons

Male CFT MTC Time (minutes)

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

275 2.93 0.26 1.97 2.92 3.83 78719 2.93 0.30 1.75 2.90 8.00 0.18

Male CFT MTC Time (minutes)

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0300 128 2.85 0.23 2.3 2.8 3.6 

0311 63 2.92 0.26 2.5 2.9 3.7 9740 2.88 0.28 1.8 2.9 8.0 0.78

0313 14 2.88 0.27 2.6 2.9 3.6 447 2.86 0.27 2.0 2.8 4.2 1.00

0321 0 316 2.66 0.20 2.1 2.7 3.4 

0331 13 2.93 0.27 2.3 2.9 3.3 1540 2.84 0.25 1.7 2.8 4.0 0.29

0341 18 3.08 0.27 2.7 3.0 3.8 1582 2.85 0.29 1.8 2.8 4.4 <0.01*

0351 4 2.91 0.14 2.7 2.9 3.1 708 2.88 0.26 2.0 2.9 4.3 0.73

0352 16 2.93 0.20 2.4 3.0 3.3 785 2.86 0.28 2.0 2.8 4.2 0.34

0372 136 2.70 0.18 2.2 2.7 3.2 

0800 60 2.94 0.22 2.5 2.9 3.5 

0811 35 3.02 0.30 2.0 3.1 3.6 1187 2.91 0.30 2.0 2.9 4.0 <0.01*

0842 168 2.86 0.27 2.3 2.8 3.9 
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-25 AUGUST 2015

0844 322 2.92 0.32 2.2 2.9 3.8 

0847 121 2.95 0.28 2.3 2.9 3.9 

0861 247 2.92 0.28 2.0 2.9 3.8 

1371 19 2.99 0.29 2.4 3.0 3.5 1875 2.93 0.27 1.8 2.9 4.3 0.40

1800 24 2.89 0.16 2.6 2.9 3.2 

1812 19 2.98 0.20 2.7 3.0 3.3 378 3.02 0.30 2.0 3.0 4.2 0.79

1833 20 2.84 0.21 2.3 2.8 3.2 904 2.85 0.30 2.0 2.8 4.1 0.67

8011 18 2.85 0.23 2.4 2.8 3.4 

8972 65 2.75 0.24 2.3 2.8 3.3 

PI&PMG 54 2.85 0.23 2.3 2.9 3.5 57863 2.94 0.30 1.8 2.9 6.6 0.03*

Q.1.10.1.1 CFT (Male Marines) MTC Score Results

The average CFT MTC time for GCEITF male Marines was 2.93 minutes compared to 

the average CFT MTC time of male Marines within the total Marine Corps Population 

which is 2.93. Based on the p-value of the K-S test being greater than .10, the 

difference is not statistically significant. The following MOSs had statistically significant 

differences:

0341 GCEITF male Marines average CFT MTC time was 3.08 compared to the average 

Marine Corps 0341 population which is 2.85. The GCEITF Marines’ average CFT MTC 

time scores were statistically significantly slower by approximately 25 seconds.

0811 GCEITF male Marines average CFT MTC time was 3.02 compared to the average 

Marine Corps 0811 population which is 2.91. The GCEITF Marines’ average CFT MTC 

time scores were statistically significantly slower by approximately 7 seconds.

PI & PMG GCEITF male Marines average CFT MTC time was 2.85 compared to the 

average Marine Corps PI & PMG population which is 2.94. The GCEITF Marines’ 

average CFT MTC time scores were statistically significantly faster by approximately 5 

seconds.

Q.1.10.2 CFT (Female Marines) MTC

Table Q-20 compares female Marines within the GCEITF to all female Marines within 

the total Marine Corps Population. Table 20 compares the 1371 Combat Engineer 

female Marines within the GCEITF to female 1371 Combat Engineers within the total 

Marine Corps Population and the PI and PMG GCEITF Marines to the total Marine 

Corps’ open MOS female Population.
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-26

Table Q-20. Female CFT MTC Time Comparisons

Female CFT MTC Time (minutes)

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

103 3.43 0.30 2.8 3.42 4.3 6497 3.63 0.39 2.0 3.62 9.4 <0.01*

Female CFT MTC Time (minutes)

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0311 12 3.27 0.24 2.93 3.2583 3.78 

0313 7 3.35 0.18 3.08 3.35 3.63 

0331 9 3.32 0.35 2.88 3.3 4 

0341 8 3.31 0.32 2.83 3.3917 3.73 

0351 3 3.14 0.29 2.88 3.0833 3.45 

0352 4 3.31 0.17 3.15 3.3 3.5 

0811 15 3.60 0.30 3.15 3.55 4.25 

1371 9 3.31 0.27 2.77 3.3667 3.73 123 3.58 0.42 1.97 3.5833 4.98 0.06

1812 4 3.41 0.29 3.07 3.4167 3.75 

1833 12 3.48 0.27 3.08 3.475 3.92 

8000 1 3.72 3.72 3.7167 3.72 

8011 5 3.88 0.40 3.53 3.7 4.53 

8972 8 3.63 0.35 3.33 3.4667 4.23 

PI&PMG 20 3.60 0.26 3.1 3.5667 4.17 6358 3.63 0.39 2.27 3.6167 9.35 0.90

Q.1.10.2.1 CFT (Female Marines) MTC Results

The average MTC time of the GCEITF female Marines was 3.43 minutes compared to 

the average MTC time of female Marines within the total Marine Corps Population which

is 3.63 minutes. Based on the p-value of the K-S test being less than .10, this difference 

is statistically significant. The GCEITF female Marines CFT MTC times were statistically 

significantly faster than the USMC total population, by approximately 12 seconds. 

Additionally, there are no statistically significant differences in any of the MOS-MOS 

comparisons. 

Q.1.11 Combat Fitness Test (CFT) MUF

This personnel variable defines CFT Maneuver under Fire (MUF) time as total time 

required to conduct the MUF event during an annual combat fitness test specified as in 

minutes.

Q.1.11.1 CFT (Male Marines) MUF

Table Q-21 compares male Marines within the GCEITF to all male Marines within the 

total Marine Corps Population and by MOS.
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-27 AUGUST 2015

Table Q-21. Male CFT MUF Time Comparisons

Male CFT MUF Time (minutes)

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

275 2.44 0.31 1.80 2.40 3.75 78688 2.40 0.32 1.08 2.37 8.00 0.06*

Male CFT MUF Time (minutes)

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0300 128 2.35 0.30 1.6 2.3 3.2 

0311 63 2.44 0.34 1.8 2.4 3.8 9738 2.32 0.29 1.5 2.3 5.3 <0.01*

0313 14 2.50 0.47 1.8 2.5 3.4 447 2.32 0.28 1.6 2.3 3.4 0.21

0321 316 2.15 0.23 1.6 2.1 3.4 

0331 13 2.48 0.36 2.1 2.5 3.5 1540 2.26 0.26 1.5 2.2 3.5 0.06

0341 18 2.48 0.23 2.0 2.5 2.9 1582 2.32 0.31 1.6 2.3 8.0 <0.01*

0351 4 2.42 0.15 2.3 2.4 2.6 708 2.30 0.26 1.6 2.3 3.6 0.37

0352 16 2.27 0.18 2.0 2.3 2.6 785 2.34 0.26 1.6 2.3 3.8 0.37

0372 136 2.04 0.26 1.5 2.1 2.8 

0800 60 2.44 0.28 1.9 2.4 3.0 

0811 35 2.48 0.30 2.0 2.5 3.3 1187 2.41 0.29 1.5 2.4 3.6 0.28

0842 167 2.36 0.24 1.8 2.3 3.2 

0844 322 2.42 0.28 1.8 2.4 3.5 

0847 121 2.45 0.31 1.9 2.5 3.4 

0861 247 2.39 0.27 1.8 2.4 3.4 

1371 19 2.58 0.30 1.9 2.6 3.0 1876 2.37 0.28 1.7 2.3 3.8 <0.01*

1800 24 2.41 0.17 2.1 2.5 2.7 

1812 19 2.44 0.32 2.1 2.3 3.2 378 2.44 0.29 1.7 2.4 3.4 0.55

1833 20 2.27 0.27 2.0 2.2 2.9 904 2.34 0.31 1.5 2.3 3.9 0.41

8011 18 2.39 0.29 2.0 2.3 2.9 

8972 65 2.45 0.32 1.7 2.5 3.3 

PI&PIMG 54 2.44 0.28 1.9 2.4 3.1 57829 2.43 0.32 1.1 2.4 4.9 0.80

Q.1.11.1.1 CFT (Male Marines) MUF Results

The average CFT MUF times of the GCEITF male Marines was 2.44 minutes compared 

to the average CFT MUF times of male Marines within the total Marine Corps 

Population which is 2.40 minutes. Based on the p-value of the K-S test being less than 

0.10, this difference is statistically significant. The GCEITF male Marines’ CFT MUF

times were statistically significantly slower than the USMC total population, by 

approximately 2 seconds. Additionally, the following MOSs had statistically significant 

differences:
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-28

• 0311 GCEITF male Marines average CFT MUF times was 2.44 minutes 

compared to the average Marine Corps 0311 population which had an average of 

2.32 minutes. The GCEITF Marines’ average CFT MUF times were statistically 

significantly slower, by approximately seven seconds.

• 0341 GCEITF male Marines average CFT MUF times was 2.48 minutes 

compared to the average Marine Corps 0341population which had an average of 

2.32 minutes. The GCEITF Marines’ average CFT MUF statistically significantly 

slower, by approximately nine seconds.

• 1371 GCEITF male Marines average CFT MUF times was 2.58 minutes 

compared to the average male Marine Corps 1371population which had an 

average of 2.37 minutes. The GCEITF Marines’ average CFT MUF statistically 

significantly slower, by approximately 12 seconds.

Q.1.11.2 CFT (Female Marines) MUF

Table Q-22 compares female Marines within the GCEITF to all female Marines within 

the total Marine Corps Population. Table 22 compares the 1371 Combat Engineer 

female Marines within the GCEITF to female 1371 Combat Engineers within the total 

Marine Corps Population and the PI and PMG GCEITF Marines to the total Marine 

Corps’ open MOS female Population.

Table Q-22. Female CFT MUF Time Comparisons

Female CFT MUF Time (minutes)

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

103 3.09 0.42 2.2 3.08 4.1 6489 3.27 0.47 2 3 7 <0.01*

Female CFT MUF Time (minutes)

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0311 12 3.12 0.40 2.5 3 3.8 

0313 7 3.33 0.35 3 3.2 4 

0331 9 2.90 0.43 2.3 2.9 3.7 

0341 8 2.93 0.39 2.4 2.9 3.5 

0351 3 2.49 0.42 2.2 2.4 3 

0352 4 2.89 0.26 2.6 2.9 3.2 

0811 15 3.24 0.41 2.5 3.2 3.9 

1371 9 3.18 0.47 2.7 3 4 123 3.20 0.47 2.417 3.167 5.833 0.67

1812 4 2.91 0.30 2.5 3 3.2 

1833 12 3.14 0.45 2.5 3.1 4.1 

8000 1 3.88 3.883 3.883 3.883 

8011 5 4.14 0.53 3.583 4.2 4.917 
GCEITF EAR ANNEX Q

FOR OFFICIAL USE ONLY 

Q-29 AUGUST 2015

8972 8 3.48 0.34 2.867 3.5 3.867 

PI&PIMG 20 3.15 0.42 2.6 3.2 4 6350 3.27 0.47 2 3.23 7.17 0.44

Q.1.11.2.1 CFT (Male Marines) MUF Results

The average CFT MUF times of the GCEITF female Marines was 3.09 minutes 

compared to the average CFT MUF times of female Marines within the total Marine 

Corps Population which is 3.27 minutes. Based on the p-value of the K-S test being less 

than 0.10, this difference is statistically significant. The GCEITF female Marines’ CFT 

MUF times were statistically significantly faster than the USMC total population, by 

approximately 11 seconds. Additionally, there are no statistically significant differences 

in any of the MOS-MOS comparisons. 

Q.1.12 Rifle Range Score

This personnel variable defines Rifle Range as a score specified as a numerical value.

Q.1.12.1 Rifle Range Score (Male Marines) 

Table Q-23 compares male Marines within the GCEITF to all male Marines within the 

total Marine Corps Population and by MOS.

Table Q-23. Male Rifle Range Score Comparisons

Male Rifle Range Score

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

278 299.95 25.10 162.00 303.00 342.00 79189 306.83 22.31 47.00 310.00 349.00 < 0.01*

Male Rifle Range Score

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0300 0 131 313.66 15.06 250.0 315.0 343.0 

0311 65 303.55 23.27 193.0 311.0 334.0 9759 307.19 24.01 85.0 311.0 348.0 0.04*

0313 14 295.57 38.80 187.0 300.0 340.0 447 306.95 22.77 147.0 311.0 342.0 0.32

0321 0 318 318.84 15.01 250.0 320.0 347.0 

0331 13 301.31 18.63 271.0 298.0 339.0 1550 308.51 22.37 137.0 312.0 347.0 0.00

0341 18 291.89 35.34 183.0 303.0 323.0 1591 304.92 26.41 116.0 309.0 345.0 0.07*

0351 4 304.00 13.74 289.0 303.5 320.0 713 307.68 22.57 133.0 312.0 342.0 0.91

0352 16 312.94 11.65 293.0 313.0 342.0 790 309.74 23.23 163.0 313.0 341.0 0.93

0372 0 138 322.48 11.42 285.0 322.5 349.0 

0800 0 60 303.12 19.36 250.0 306.5 336.0 

0811 35 300.17 14.43 250.0 299.0 324.0 1195 304.33 26.38 135.0 309.0 345.0 0.02*

0842 0 168 309.90 20.79 131.0 313.0 341.0 

0844 0 324 306.93 23.96 139.0 312.0 341.0 
GCEITF EAR APPENDIX TO ANNEX Q

FOR OFFICIAL USE ONLY 

AUGUST 2015 Q-30

0847 0 121 310.15 14.55 260.0 312.0 339.0 

0861 0 250 307.90 21.83 146.0 311.0 341.0 

1371 19 310.00 18.01 271.0 311.0 342.0 1890 306.34 23.42 139.0 310.0 346.0 0.90

1800 0 24 308.33 14.67 281.0 311.0 332.0 

1812 19 288.37 39.31 162.0 299.0 329.0 379 293.99 36.09 124.0 303.0 336.0 0.37

1833 20 305.60 21.57 250.0 309.5 330.0 906 308.20 21.49 171.0 312.0 347.0 0.55

8011 0 18 302.44 20.65 250.0 308.0 327.0 

8972 0 65 310.71 13.29 273.0 311.0 335.0 

PI&PMG 55 293.38 23.61 179.0 296.0 333.0 58352 306.71 21.66 47.0 310.0 347.0 < 0.01*

Q.1.12.1.1 Rifle Range Score (Male Marines) Results

The average Rifle Range score of the GCEITF male Marines was 299.95 compared to 

the average Rifle Range score of male Marines within the total Marine Corps Population 

which is 306.83. Based on the p-value of the K-S test being less than .10, this difference 

is statistically significant. The GCEITF male Marines’ Rifle Range scores were 

statistically significantly less than the USMC total population, by approximately 7 points. 

Additionally, the following MOSs had statistically significant differences:

• 0311 GCEITF male Marines average Rifle Range score was 303.55 compared to 

the average Marine Corps 0311 population which had an average score of 

307.19. The GCEITF Marines’ average Rifle Range scores were statistically 

significantly lower, by approximately four points.

• 0341 GCEITF male Marines average Rifle Range score was 291.89 compared to 

the average Marine Corps 0341population which had an average score of 

304.92. The GCEITF Marines’ average Rifle Range scores were statistically 

significantly lower, by approximately thirteen points.

• 0811 GCEITF male Marines average Rifle Range score was 300.17 compared to 

the average Marine Corps 0811 population which had an average score of 

304.33. The GCEITF Marines’ average Rifle Range scores were statistically 

significantly lower, by approximately four points.

• PI and PIMG GCEITF male Marines average Rifle Range score was 293.38 

compared to the average Marine Corps open MOS population which had an 

average score of 306.71. The GCEITF Marines’ average Rifle Range scores 

were statistically significantly lower, by approximately thirteen points.

Q.1.12.2 Rifle Range Score (Female Marines) 

Table Q-24 compares female Marines within the GCEITF to all female Marines within 

the total Marine Corps Population. Table 24 compares the 1371 Combat Engineer 

female Marines within the GCEITF to female 1371 Combat Engineers within the total 
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Marine Corps Population and the PI and PMG GCEITF Marines to the total Marine 

Corps’ open MOS female Population.

Table Q-24. Female Rifle Range Score Comparisons

Female Rifle Range Score

All MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

103 296.99 23.61 168.0 302.00 337.0 6629 295.98 26.62 109 300 344 0.94

Female Rifle Range Score

MOS

GCEITF USMC KS Test

N Mean SD Min Median Max N Mean SD Min Median Max P-value

0311 12 297.67 17.64 270 293.5 330 0 

0313 7 286.71 21.76 250 287 313 0 

0331 9 307.78 14.02 291 309 330 0 

0341 8 304.13 19.03 265 308.5 328 0 

0351 3 305.67 6.51 299 306 312 0 

0352 4 295.00 30.30 250 307 316 0 

0811 14 283.86 36.48 168 291 316 0 

1371 9 298.78 15.00 279 296 319 124 296.4677419 26.34277966 141 299 333 1.00

1812 4 320.50 14.80 304 320.5 337 0 

1833 12 289.42 21.61 250 296.5 310 0 

8000 0 1 293 293 293 293 

8011 0 5 287.6 17.03819239 262 290 309 

8972 0 8 306.75 17.20257456 282 310 325 

PI&PMG 21 299.67 23.28 250 306 327 6489 295.9631684 26.64596459 109 300 344 0.37

Q.1.12.2.1 Rifle Range Score (Female Marines) Results

The average Rifle Range score of the GCEITF female Marines was 296.99 compared to 

the average Rifle Range score of female Marines within the total Marine Corps 

Population, which is 295.98. Based on the p-value of the K-S test being greater than 

0.10, there is no statistically significant difference between the two groups. 

Additionally, there are no statistically significant differences in any of the MOS-MOS 

comparisons. 
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Annex R. 

Methodology

This annex details the methodology portion of the Ground Combat Element Integrated 

Task Force (GCEITF) experiment. The sections outline the Volunteer Timeline, Design 

of Experiment, Descriptive and Basic Inferential Statistics, Statistical Models, and 

Limitations. 

R.1 Volunteer Timeline 

R.1.1 Recruitment and Selection

On 10 June 2014, MCOTEA made the initial selections for volunteer participation from 

the pool of applicants who had provided informed consent. The initial selection 

consisted of 455 volunteers (287 Male/168 Female). MCOTEA registered all female 

volunteers who needed to attend Formal Learning Centers (FLCs) for Military 

Occupational Specialty (MOS) training with Training and Education Command 

(TECOM). 

R.1.2 School Assignments and Orders

All female volunteers attending FLCs were issued Temporary Additional Duty orders. 

From that point, MCOTEA began the process of assignment and orders through 

Manpower and Reserve Affairs (M&RA), Headquarters Marine Corps. Male and female 

volunteers who were not required to attend an FLC were issued Permanent Change of 

Station (PCS) or Permanent Change of Assignment (PCA) orders directly to the 

GCEITF at Camp Lejeune, NC, with reporting dates to coincide with their peers in their 

respective MOSs. Females who successfully completed the course of instruction at the 

FLCs were issued PCS/PCA orders just prior to graduation. 

Not all volunteers wanted, or were physically able, to complete the experiment. From 

initial notification in June 2014 through May 2015, SOME volunteers voluntarily 

withdrEw or were involuntarily withdrawn from the experiment. Initially, MCOTEA 

sought alternates to replace the volunteers. Volunteers were replaced on a case-bycase basis from the initial selections in June 2014 through November 2014 using the 

same procedures outlined in the Experimental Assessment Plan. Replacements were 

no longer sought after November, because the loss of training time would negatively 

impact the volunteer’s participation in the experiment. Figure R-1 illustrates the quantity 

of volunteers who were on orders, and those actively participating in an experimental 

activity. 
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Figure R-1. Volunteer Timeline from Notification through Deactivation

In Figure R-1, the vertical axis is the number of volunteers in the experiment; the 

horizontal axis is time. The timeline depicted begins on 10 June 2014 with the initial 

selection of volunteers, and ends on 15 July 2015, when the GCEITF deactivated. Thin 

gray vertical lines indicate times when significant experimental activities began along 

the timeline. The heavy dashed line represents the number of volunteers who were on 

orders but had not begun participating in any experimental activities. The solid black 

line represents the number of volunteers who actively participated in some experimental 

activity, including attending MOS training, GCEITF unit training, and formal 

experimentation. The dashed line shows a general downward trend as volunteers 

withdrew from the experiment. The upward spikes in the dashed line show where 

alternate selections took place, with the last significant selection event occurring in 

November 2014. 

R.1.3 FLC Training and GCEITF Unit Training

The solid black line in Figure R-1 trends upward on 7 July 2014, when the first of the 

female volunteers began training at MOS schools. The line continues to trend upward 

in steps as more females begin classes at subsequent MOS schools. The small 

downward dips in the lines—from the start of the first females attending MOS schools 

until volunteer training begins on 1 October 2014—represent volunteers who withdrew 

from the experiment. Most volunteers arrived from 1 October 2014 through 1 November 

2014, indicated by the steady incline of the solid black line. From 1 November 2014 
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through 7 January 2015, the number of volunteers remained relatively stable, with small 

numbers of volunteers withdrawing from the experiment, as indicated by the modest 

downward trend in the number of active volunteers. On 7 January 2015, MCOTEA 

reconciled with the GCEITF the number of volunteers who were on orders with those 

who were actually present at the unit. This is the point in the figure where the dashed 

and solid lines converge. Shortly after 7 January 2015, there is a large decrease in the 

volunteer population, as many male Marines voluntarily withdrew from the experiment 

after the holiday leave period.

R.1.4 Experiment Phase

On 18 February 2015, the GCEITF training period officially ended as the GCEITF

arrived with 285 volunteers at MCAGCC, Twentynine Palms, CA. From arrival at 

MCAGCC to 7 March 2015, when experimental trials officially began, the unit prepared

equipment, acclimatized, and practiced experimental tasks. By the time the first 

experimental trials began, the number of volunteers had dropped to 264. 

From 7 March to 11 April 2015, all elements of the experiment engaged in experimental 

trials with a modest decrease in the number of volunteers, due mostly to injuries. 

Beginning on 11 April 2015, the solid black line declines in a stepwise manner, as each 

of the MOSs concludes experimental activities and large numbers of volunteers 

conclude active participation. Artillery was the first to complete all experimental trials, 

followed by Tanks on 16 April 2015. By 28 April 2015, the Assault Amphibious Vehicle

(AAV), all Infantry MOSs (including Provisional Infantry), and Engineers were done with 

their experimental trials and moved on from MCAGCC to Camp Pendleton (AAVs) and 

Bridgeport (all Infantry MOSs, Provisionals, and Engineers). The next to conclude all 

experimental trials was the Light Armored Vehicle (LAV) crews, on 4 May 2015. The 

final elements of the experiment to conclude activities were all Infantry MOSs and 

Engineers, on 18 May, with AAVs concluding on 19 May 2015. From 20 May 2015 until 

the GCEITF shutdown on 15 July 2015, the volunteers were in an administrative status 

while awaiting orders to their follow-on units or released from active duty for Reservists. 

R.1.5 Volunteer Summary

MCOTEA recruited and obtained informed consent from a total of 598 Marines, 

although the maximum active participation by volunteers at any one time was 382. Of 

the 598 volunteers, 422 volunteers actually participated in the experiment in some 

fashion, either by attending a formal school, training with the unit, and/or participating in 

the formal experiment. 
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R.2 Analysis Limitations 

R.2.1 Independence assumption

Some of the statistical analysis techniques used assume that the outcomes of each trial 

are statistically independent of one another. For many of the tasks, this assumption is 

justified because the number of volunteers were sufficient and their roles within tasks 

had little relationship to one another. Thus, if the same individual is sampled multiple 

times for the task but is performing different functions or is binned with different people, 

the data may be sufficiently independent for the purposes of the experiment. 

Where possible, we implemented mixed-model analysis with random effects for 

individuals to explicitly adjust for the fact that our trials were not, strictly speaking, 

independent. However, there are some tasks for which a mixed model was not possible 

to run, and the results we present in the descriptive statistics sections also do not 

account for the lack of independence. For these types of tasks, it is possible for lack of 

independence to result in higher power of the test to detect differences between groups, 

and increased Type I error rates.

R.2.2 Sample selection

As detailed in the EAP Section 7, the GCEITF experiment was likely to suffer from 

selection bias—the notion that the Marines’ decision to participate (volunteer) in the 

experiment may be correlated with the specific traits that affect the study itself. This 

could have manifested in the volunteers’ motivation, performance, survey answers, and 

other aspects of the experiment. To the extent that we could, we tried to ensure the 

sample was representative of the population of Marines, with respect to observable 

physical characteristics that the USMC collects and records. This analysis is reported in 

the Population Annex. Based on that analysis, our conclusion is that with respect to 

these characteristics, the GCEITF sample was representative of the Marine Corps at 

large, with a few small and substantively unimportant exceptions. However, the 

possibility remains that the sample was different from the population in unobserved 

ways.

R.2.3 Sample size

The details of how we originally determined the size of the experiment are in the EAP 

Section 7. However, as the number of volunteers decreased, so did the number of 

possible trials that could be run per day. As a result, many tasks saw a reduction in 

sample size, some only running one-third of the planned trials. Whenever reasonable, a 

comparison group (usually, the LD group) was eliminated from consideration by the 

research team, splitting the smaller sample size among two different concentrations—

control (C) and high-density (HD)—rather than three, to maintain better experimental 

power to detect differences. Still, with variation in some tasks, particularly high among 
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integrated groups, a larger sample size would have resulted in more-precise estimates 

and more confidence in stating observed differences.

R.2.4 Modeling group outcomes using individual data

The experiment was designed to detect differences in performance between genderintegrated and all-male units. It is reasonable to perform such analyses using ANOVA 

or mixed-modeling techniques, particularly because this was a genuine experiment, with 

random assignment of volunteers to groups of various integration levels. However, in 

additional analyses, we also tried to determine how individual characteristics contributed 

to group outcome in an attempt to inform gender-neutral standards. We did this using 

data from each individual volunteer in the group, sometimes combining variables, when 

sample size permitted. Ultimately, our models assume a specific functional form: we 

assume that the group outcome depended on some linear combination of all 

participants’ personnel variables. Intuitively, this need not be the case, and the poor fit 

of many of our models confirms that we gain little explanatory power by including 

personnel variables in the models. This is not to say that the variables do not have an 

impact on the outcome; more complex modeling may be needed to uncover these 

relationships.

R.3 Design of Experiment 

For each task identified, sample size of the unit needed to perform a task (a 12-person 

squad or a 4-person crew) were drawn repeatedly from the relevant participant 

population to represent various concentration groups. 

R.3.1 Integration Levels

The experimental plan specified that for each MOS, one experimental group would be

entirely male (control group), one would contain one female (low-density or LD), and the 

third would contain two female participants (high-density or HD). As volunteers left the 

experiment, some concentration levels had to be changed or dropped from evaluation 

altogether. For each MOS, trials were run for at least the control group and one of the 

integrated concentrations. The result of each trial for each of these units constitutes 

one observation for the collective tasks analysis. The final male-female concentrations 

per MOS are displayed below, in Table R-1. 

Table R-1. Integration Levels – by MOS

MOS Number of volunteers 

in the group

Number of females 

in LD group

Number of females 

in HD group

0311 12 NA 2

0313 3 1 2

0331 3 1 2

0341 4 NA 2

035X 4 NA 2,3,4
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MOS Number of volunteers 

in the group

Number of females 

in LD group

Number of females 

in HD group

PI 12 2 4,5

PIMG 3 NA 3

0811 6 1 2

1812 2 1 NA

1833 3 1 2

1371 8 2 4

Mountaineering

Closed MOS 12 NA 6 

Mountaineering

Open MOS 12 NA 6 

R.3.2 Sample Size and Statistical Significance

The experiment was sized to detect at least a 30% difference in task outcomes (see 

EAP, section 7 for relevant design parameters, as well as sample sizes and effect 

sizes). Throughout the course of the experiment, sample sizes for some MOSs and 

tasks dropped—substantially in some cases—mainly due to the loss of volunteers and 

to environmental and experimental constraints. Each MOS-specific annex details the 

number of planned and executed trials for each task.

Ultimately, many differences lower than 30% were detected to be statistically significant. 

The analysis of each task includes a section with comments on potential operational 

implications of all statistically significant and nearly statistically significant differences. 

R.3.3 Random assignment

For each MOS, prior to the beginning of each trial cycle, a run roster was drawn to 

randomly select Marines from the pool of volunteers to fill the rotating positions in each 

control and integrated group. In cases where the Marines were unavailable due to 

injury or from leaving the experiment, volunteers of the same gender were substituted 

for the empty spots at random. The ordering of integrated and control squads each day 

was randomized throughout the experiment to maintain balance between groups being 

exposed to various environmental factors.

R.3.4 Pilot Trial Cycles

To test data collection devices and protocol, and to ensure consistency between trials, 

pilot trial cycles consisting of two complete trial cycles were run prior to the start of 

experimental data collection. Because procedures used in executing the experiment 

and collecting data ultimately were not the same during pilot trial cycles as during the 

rest of the experiment, pilot data were not incorporated into the datasets analyzed for 

each MOS. 
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R.3.5 Outliers and Potentially Influential Points

Prior to data analysis, we removed points from the data that were clear outliers. By 

outliers, we mean points that were actually invalid data. Invalid data include data that 

were wrong because of human (data collector) error, results that were affected by trial 

interruptions and other test incidents, and points that were clearly erroneous due to data 

collection equipment.

For many tasks, we identified a small number of points that were valid data but were so 

unusual in their values that they could potentially drive the results. Because they were 

valid data that we could not exclude from analysis for good reason, we did not go 

through the formal process of computing Cook’s distance for these points to detect if 

they affected our analysis in a statistically significant way. Rather, we simply present 

results with and without these points to illustrate how our conclusions might change in 

their absence. 

R.4 Descriptive and Basic Inferential Statistics 

This section details the analysis techniques used to describe the data and make 

conclusions about the difference in performance between control and integrated units, 

without adjusting for other variables. The statistical procedures described below enable 

us to take the sample data from the experiment and make statements about the 

differences in performance that we would expect to observe in the broader USMC 

population. 

R.4.1 Critical Billets

For LAV, Tanks, AAV, and Artillery MOSs, there were metrics that involved only one or 

two volunteers in specific billets (we term them critical billets)—rather than the entire 

group—performing physically demanding tasks. In these cases, it no longer made

sense to analyze the data just by integration level: if a male was performing a task, we 

would expect the result to be the same, whether he was on an integrated or control 

team. Hence, we provide analyses of such tasks by the gender of the person or people 

in those billets. The analysis techniques remain the same as when we compare 

gender-integrated groups to control groups.

R.4.2 Welch’s t-test

The Welch’s t-test is a statistical test that can be used to compare differences in two 

means across groups to the variation among and between groups, allowing unequal 

variances in two groups. We use Welch’s t-test to describe whether differences 

between average responses for two integration groups are statistically significant or 

unlikely due to chance. The test is used for most of our descriptive analyses where 

there are only two groups to consider, and the outcomes are, or can be, assumed to be 

continuous (such as elapsed time or target hit probabilities). For each result, we
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provide a p-value, which we compare to the a-priori determined significance level of 

10% (0.10). P-values less than 10% are considered statistically significant and are an 

indication that the observed differences between group means cannot be attributed to 

chance.

Welch’s t-test is based on several assumptions. The first is that the observations are 

independent and identically distributed. Strictly speaking, the independence 

assumption may be violated in some of our analyses, since sampling was done with 

replacement. This is less problematic for the MOSs, where we had a large number of 

volunteers (0311s, for instance). In all cases, Marines were sampled to rotate through 

different positions on their respective squads and crews, and work with different 

Marines in other positions. All Marines within each MOS went through MOS school 

and, subsequently, trained together as a unit. For this reason, the violations of the 

independence assumption are unlikely to be strong. In section R.5.3.2, we try to 

address this concern whenever possible. The second assumption is that the response 

variable is normally distributed. We evaluate this assumption using the Shapiro-Wilk 

test for our task results, except where sample size is large enough (greater than 30) to 

use the Central Limit Theorem to make this assumption less important. We use a 

significance level of 1% for the Shapiro-Wilk test. In cases where at least one of the 

groups’ results is not normally distributed, we use a non-parametric equivalent of the ttest, described in section R.4.4. 

R.4.3 Analysis of Variance (ANOVA)

ANOVA provides a statistical test that can be used to compare differences in two or 

more means across groups to the variation among and between groups. We use 

ANOVA to describe whether differences between average responses for the different 

integration groups are statistically significant, or unlikely due to chance. ANOVA is used 

for most of our descriptive analyses where outcomes are, or can be, assumed to be 

continuous, such as elapsed time or target hit probabilities. For each result, we provide 

a test statistic (denoted by F in relevant tables), as well as a p-value, which we compare 

to the a-priori determined significance level of 10% (0.10). P-values less than 10% are 

considered statistically significant and are an indication that the observed differences 

between group means cannot be attributed to chance.

ANOVA tests all the means simultaneously—that is, in the case of comparing three 

means, a significant result shows only that the three means in consideration are not all 

the same and that further testing needs to be done to describe the size and direction of 

the differences between them. For more details on this type of analysis, see section 

R.4.5. 

ANOVA is based on a few assumptions. The first two are identical to those for Welch’s 

t-test listed above. The third assumption is that the variances of the result are similar 
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across groups. This assumption is considered violated when the biggest variance 

under consideration is at least twice the smallest variance. ANOVA is sensitive to the 

violation of this assumption. For that reason, when variances across groups appear 

unequal, we use Robust ANOVA based on the Huber M-estimation method, which is a 

more robust fit procedure. 

In the sections on descriptive statistics, we present ANOVA results for comparing 

means of two and three groups, although Welch’s t-test, described in section R.4.2, is 

also used for comparing two groups. For two groups, the difference between Welch’s 

t-test and ANOVA lies in the assumption of equal variances between groups (ANOVA 

assumes it, Welch’s t-test does not), so the results are usually similar but not always 

exactly the same.

R.4.4 Nonparametric tests

The t-test and ANOVA assume that the data are normally distributed for each group 

under consideration. For some MOSs and tasks, that assumption failed and the sample 

sizes in each group were not sufficient to use the Central Limit Theorem. In those 

cases, we use non-parametric techniques to test for differences between groups.

The non-parametric equivalent of a t-test is the Mann-Whitney U-test, also called the 

Wilcoxon rank-sum test. It is designed to test whether two samples come from the 

same population or whether one sample comes from a population with higher values 

than the other. Rather than comparing means for the two samples, the Mann-Whitney 

U-test compares ranks of observations between the two groups, and indicates whether 

there is a pattern in the magnitude of observations from each population (i.e., if higher 

observations tend to fall more under the control or the integrated group). 

The non-parametric equivalent of an ANOVA is the Kruskal-Wallis test. It is designed to 

test whether at least two samples come from the same distribution and is an extension 

of the Mann-Whitney U-test to three or more groups. Just like the Mann-Whitney U-test, 

the Kruskal-Wallis test looks for patterns in ranks. Significant results from the KruskalWallis test are an indication that the comparison groups are stochastically different.

In tables of descriptive statistics, where necessary, we simply replace the value of the 

t-statistic, or the F-statistics and relevant p-values, with their non-parametric 

equivalents, indicating where the change was made.

R.4.5 Multiple Comparisons

In cases where ANOVA or Kruskal-Wallis test identified that the groups compared were 

not all the same, we compared each pair of groups to identify how they were different. 

Using multiple t-tests or Mann-Whitney tests for this purpose may result in inflated 

familywise Type I error rates: each test on its own has a 10% such rate, and if we are 

comparing three groups, we perform three such comparisons. Thus for post-hoc 
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analyses of tasks that were identified significantly different across groups using ANOVA, 

we further analyzed the differences using the Tukey procedure in place of the regular 

t-test. Such a procedure does not have a clear non-parametric equivalent, so where a 

Kruskal-Wallis test gave significant results, we proceeded with Mann-Whitney tests for 

each pair of interest. However, to adjust for the inflated familywise Type I error rate, 

instead of comparing our p-values to 10%, we use the Bonferroni adjustment (known to 

be conservative for a large number of comparisons) and compare our p-values to 10% 

divided by the number of comparisons we make.

R.4.6 Additional Descriptive Analyses 

Differences between groups may meet statistical significance criteria, but we also seek 

to provide operation context for their interpretation. For many of the tasks in the MOSspecific annexes, we include additional descriptive—often, qualitative analyses—based 

on the Marine Corps doctrine and subject matter expertise. These analyses fall into 

three possible categories: Contextual Comments, Additional Insights, and Subjective 

Comments. In the Contextual Comments sections, we try to put the observed 

differences into operation context, comparing results with Marine Corps standards, 

where they exist, and giving operationally realistic examples. In the Additional Insights 

sections, we provide some subject matter expert observations and judgments on the 

differences, as well as commentary based on literature outside the USMC, where 

relevant. Subjective Comments, which are primarily located in the MOS-specific 

appendices, provide trial-specific comments and observations of the GCEITF staff, 

broken into broad categories.

For those tasks that did not produce a statistically significant result, we still provide 

some interpretation if the differences were close to being statistically significant, since it 

is unclear if there is truly a lack of difference between the populations, or if a bigger 

sample size would have resulted in a statistically significant finding. 

R.5 Statistical Models 

The previous section discussed descriptive analyses as they pertain to differences in 

performance due to integration level only. This section details the analysis techniques 

used to make conclusions about the difference in performance between control and 

integrated units, adjusting for other variables. The goal of modeling, as applied here, is 

to estimate, simultaneously, the effect of gender-integration levels and other relevant 

variables on group performance, and to see whether accounting for the volunteers’ 

physical attributes affects the conclusions of descriptive analyses above. This kind of 

model can be helpful in identifying which physical attributes best predict group 

performance measure and can be helpful in establishing gender-neutral physical 

standards.
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R.5.1 USMC Personnel Variables

Personnel data for this portion of the analysis refers to the following variables found in 

the Marine Corps Total Force Management System (TFMS), commonly measured for 

every Marine: age, height, weight, Armed Forces Qualification Test (AFQT) score, 

general technical (GT) score, the Combat Fitness Test (CFT) maneuver-under-fire 

(MANUF) time, the CFT movement-to-contact (MTC) time, the Physical Fitness Test 

(PFT) three-mile run time, the PFT Crunch Score (number of crunches), and the annual 

combined rifle score. The personnel variables used in the statistical modeling are 

described below.

R.5.1.1 Age 

The age of the volunteer in years as reported in TFMS. 

R.5.1.2 Height 

The height of the volunteer in inches as reported in TFMS.

R.5.1.3 Weight

The weight of the volunteer in pounds as reported TFMS.

R.5.1.4 Armed Forces Qualification Test (AFQT)

AFQT scores are computed using the standard scores from four Armed Services 

Vocational Aptitude Battery (ASVAB) subtests: arithmetic reasoning (AR), mathematics 

knowledge (MK), paragraph comprehension (PC), and word knowledge (WK). The 

formula used to derive the AFQT score is 2VE + AR + MK. The verbal expression (VE) 

score is used to measure communicative ability and consists of a scaled score derived 

from adding the value of the word knowledge (WK) raw score to the paragraph 

comprehension (PC) raw score. The AFQT composite score, as reported in TFMS, was 

used in the analysis. 

R.5.1.5 General Technical (GT)

The GT score is calculated by adding the verbal expression (VE) and the arithmetic 

reasoning (AR) scores from the ASVAB. The GT composite score as reported in TFMS 

was used in the analysis.

R.5.1.6 Combat Fitness Test (CFT)

The CFT is used to assess a Marine’s physical capacity in a broad spectrum of combatrelated tasks. The CFT was designed to evaluate strength, stamina, agility, and 

coordination, as well as overall aerobic capacity. The CFT is a complement to the PFT 

and measures the functional elements of combat fitness through execution of a series of 

events that represent every Marine’s combat experience, emphasizing the Corps’ ethos 

of “every Marine a rifleman.” The CFT is a scored, calendar-year annual requirement for 
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all active duty Marines, regardless of age, gender, grade, or duty assignment. It is 

required to be conducted between 1 July and 31 December of each year.

The CFT is a three-part combat physical-fitness evaluation that consists of a movement 

to contact (MTC) simulated by an 880-yard run, a maximum set of ammunition lifts (AL) 

using a 30-pound ammo can, and a 300-yard maneuver-under-fire (MANUF) course. 

Both the MTC and MANUF are timed events and are thus comparable. However, the 

male and female standard for the ammunition-can lift varies based on age. Therefore, 

the modeling included the MTC and MANUF times, but excluded the AL number score.

R.5.1.7 Physical Fitness Test (PFT)

The PFT is a collective measure of general fitness throughout the Marine Corps. The 

PFT was designed to test the strength and stamina of the upper body, midsection, and 

lower body, as well as efficiency of the cardiovascular and respiratory systems. The 

PFT is a scored, calendar-year annual requirement for all active duty Marines, 

regardless of age, gender, grade, or duty assignment. It is required to be conducted 

between 1 January and 30 June of each year. It consists of a three-part test: a timed 

3-mile run, a maximum set of crunches performed in a time of 2 minutes, and either a 

flexed-arm hang (for females) or pull-ups (for males and an option for females).

The modeling considered the 3-mile run time and the number of crunches performed 

during the PFT, but excluded the number of pull-ups and the flexed-arm hang time. 

Females have the option either to do a flexed-arm hang or complete the pull-ups portion 

of the PFT. Males are limited to pull-ups only, no flexed-arm hang. A passing score for 

females consists of 3 pull-ups; the maximum pull-ups are 8. The male Marine passing 

score consists of 3, but the maximum is 20. Currently, female Marines who opt for pullups and execute more than 8 pull-ups still receive a score of 8 in the system. Because 

there is no direct comparison between males and females in this category, the flexedarm hang/pull-ups portion of the PFT is excluded for analysis. 

R.5.1.8 Annual Combined Rifle Score

The intent of the Marine Corps annual rifle training is to sustain, improve, and evaluate 

marksmanship skills, to include demonstration of proficiency in fundamental 

marksmanship skills and combat shooting skills. Qualification scores are based on an 

aggregate of Table 1A (a known distance range with the capability to fire from 100, 200, 

300, and 500 meters), and Table 2 (which requires Marines to fire at stationary targets 

from 25 meters and at moving targets from 100 meters). The aggregate rifle range 

score as reported in TFMS was used in the analysis.

R.5.2 Multicollinearity

Several variables listed above measure similar dimensions of a Marine. For instance, 

height and weight measure a person’s size; GT and AFQT scores measure mental 
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aptitude; and PFT and CFT scores and times measure physical fitness; these variables 

are correlated. Within the GCEITF, height and weight were correlated with the 

coefficient of 0.63 for females and 0.58 for males. For GCEITF females, the correlation 

coefficient between GT and AFQT scores is 0.92; it is 0.90 for males. We present the 

correlations for the physical fitness variables in Table R-2. 

Table R-2. Correlations between Physical Fitness Measures for GCEITF Females

CFT, Movement 

to contact

CFT, Maneuver 

under fire

PFT Run Time 

(minutes)

PFT, Crunches

CFT, Movement 

to contact

1.00 0.54 0.69 -0.07

CFT, Maneuver 

under fire

0.54 1.00 0.42 -0.14

PFT Run Time 

(minutes)

0.69 0.42 1.00 -0.08

PFT, Crunches -0.07 -0.14 -0.08 1.00

Some of these correlations are quite high, indicating that when used in a linear model, 

these variables will attempt to explain the same type of variation in the outcome. This 

typically results in volatility of the model coefficients but does not reduce the reliability of 

the model overall. Because our goal is to have models that are as complete as 

possible, and because we do not interpret the coefficients of these variables, we 

proceed with using all variables in our models, acknowledging this multicollinearity 

issue. However, we do use variable selection methods, discussed in section R.5.3.4, to 

reduce the complexity of resulting models.

R.5.3 Modeling Techniques

R.5.3.1 Ordinary Least Squares Regression

Ordinary Least Squares (OLS) regression is an analysis technique that evaluates a 

linear relationship between a set of independent variables—which for us are integration 

levels, the USMC personnel variables, and the dependent variable (or the outcome of 

interest). OLS can be used to evaluate the simultaneous impact of all these variables 

and identify which variables predict the response the best. It also enables us to 

comment on how each variable affects the outcome, holding other variables constant. 

This is especially useful as we try to evaluate whether integration levels of the units 

matter, given the physical attributes of all the trial participants. 

OLS regression models assume that the residuals are independent and identically 

distributed (IID) per the normal distribution with a mean of zero. We do not check this 

assumption, because the poor fit of the models precludes us from recommending them 

as useful.
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R.5.3.2 Linear Mixed Models

The traditional OLS model, described above, assumes “fixed effects” for the variables 

that it includes. This means that the variables take only the fixed values. For instance, 

gender can take values of male and female only, so it is considered a fixed effect. 

A random effect, by contrast, can be evaluated for a variable for which we observed 

only a random sample in our dataset, or a variable that contributes to a hierarchy of 

observations. For instance, we could say that all the Marines in our data represent a 

sample of the USMC, and, furthermore, that to the extent that the same Marine is 

placed in the same billet more than once, the data are nested in that way. Thus, we can 

include a random effect for the volunteers who fill each billet. This not only models the 

fact that our volunteers are a sample from a bigger population but also helps us 

explicitly account for the fact that we sample with replacement and our trials are not, 

strictly speaking, independent of one another. A model that incorporates fixed and 

random effects is called a mixed model. Whenever sample size was sufficiently large to 

generate reasonable model estimates, we ran mixed models due to these advantages.

Mixed models assume that the residuals are IID normal for each level of the random 

effect. Because each Marine participated in only a handful of trials—thus providing a 

very small sample of residuals with which to test this assumption—it is not testable in 

our models.

R.5.3.3 Multinomial models

We use multinomial logistic regression to model Shoulder-launched Multipurpose 

Assault Weapon (SMAW) accuracy in Annex E of this report. Each squad got to fire 

four shots, so the only possible outcomes of the model are 0, 1, 2, 3, and 4 when we 

are counting the number of hits on target. The model assumes that using the 

covariates—which include integration levels and our USMC personnel variables—each 

trial outcome can be classified into one of the five categories of the number of hits. 

Then the model quantifies the relationships between these independent variables and 

the categories, and provides a predicted probability that each integration level has of 

obtaining 0, 1, 2, 3, and 4 hits per target.

R.5.3.4 Variable selection

Prior to model fitting, we selected a set of individual covariates that the Marine Corps 

records on each Marine that could theoretically be related to the outcomes we modeled. 

Each model that we fit started out with as many of these covariates as was possible, 

given the sample sizes for each task. After the models were fit, however, we sought to 

reduce their complexity by taking away the variables that were not related closely 

enough to the outcome. We did so using the Akaike Information Criterion (AIC), which 

can help select a model out of many candidate models by quantifying the tradeoff 

between model complexity and the goodness of fit. 
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Specifically, the calculation of AIC includes the number of model parameters and the 

maximized likelihood. The number of model parameters represents a penalty for model 

complexity and overfitting; the model with the lowest value of AIC is considered the best 

balance of fit and complexity. Note, however, that although AIC can be used to 

compare models, it ultimately will not indicate if all models under consideration fit poorly, 

which was the case for some of our results. 

Whenever it was possible to estimate a model using maximum likelihood methods, we 

used AIC for variable selection and commented only on the reduced models. We 

always started out with the fullest model we could fit and reduced it by eliminating one 

variable at a time, a technique known as backward elimination. 

When maximum likelihood estimations failed to converge, we could no longer compute 

the AIC and had to comment on individual variables’ significance in the full model.

Note that we used AIC even in cases where we modeled the result as a function of 

integration and one variable at a time, to see whether the model needed to include 

integration and that variable or just one of them.

R.5.3.5 Modeling when sample sizes are too small

In many cases, we did not have sufficient sample size to run full models that include all 

covariates for all trial participants. For instance, a rifle squad is composed of 12 

individuals, meaning that we would have to include 12 variables for each covariate of 

interest. The problem grows quickly with the number of covariates, and the sample size 

did not support running full models for many tasks. Thus the next step in our analysis 

was to run the models for one variable at a time and include the integration level to see 

if any patterns emerged. For instance, we would model the group outcome as a 

function of the integration level and the height of all participants to see if all or most 

heights were predictive of the outcome. Next, we regressed the outcome on integration 

level and weight of all the participants, and so on. In the modeling sections of the 

annexes, we comment on whether the integration level was significant in these models, 

as well as whether the individual variables were significantly correlated with the 

outcomes.

As far as deciding how to model continuous data, we followed the following logic for 

choosing models:

1) Attempt to run a full mixed-model with all variables for all participants. 

2) If 1) fails, attempt to run a mixed model with one variable at a time. 

3) If 1) and 2) fail, attempt to run an OLS regression model with all variables for all 

participants. 

4) If 1), 2), and 3) fail, run an OLS regression model with one variable at a time.
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For the extremely small sample sizes of the mountaineering portion of the experiment, 

modeling the outcomes did not make sense because of the large number of participants 

in each trial. Thus, we limited those analyses to descriptive statistics only.

R.5.3.6 Interpreting model results

As discussed in section R.2.4, the main shortcoming of OLS regression is that we are 

forced to assume a very specific functional form. In most cases, the models did not fit 

the data well, giving results that did not make much sense from a theoretical or a policy 

perspective. This is also likely a consequence of the multicollinearity of the data, 

established in 0. As is common in linear models (where independent variables are 

strongly correlated), many of our significant model coefficients had signs opposite of 

what one would expect (less fit Marines performing tasks faster), or contradicting signs 

(a variable having a positive impact on the group response for one of the team 

members, but a negative for another).

An additional complication was presented when we could not fit models with all the 

personnel variables for all the trial participants due to sample size issues. In these

cases, we had to resort to fitting one model per variable. For instance, we would 

regress the outcome on the integration level of the unit and the age of each participant. 

The interpretation of the model results would be whether the ages of individual 

participants are correlated with the outcome of the unit. Then we would repeat this 

analysis for weight and other variables. The limitation of this type of analysis is that we 

never get to see how each variable affects the response while other variables are held 

constant. In addition, it is difficult to combine the results of such models into one final 

model. 

With a few exceptions, our models did not identify any discernable patterns. For 

instance, it was typical to see that a variable mattered for one group member but not the 

rest. The policy implication of such a finding is unclear: an Infantryman, for instance, is 

expected to be able to perform any duty out of the 12 squad positions, not just one. 

Thus, such findings could not be used, effectively, to shape gender-neutral standards 

for an MOS, as opposed to a finding where a variable consistently came out as 

significant for all or most group members. In most of our models, no discernable 

patterns were obvious, limiting us to considering only integration level as a plausible, 

useful predictor of the response.

R.5.3.7 Lanchester models

Lanchester’s laws are common analysis techniques used to model battles by comparing 

strengths of two military forces over time. We use Lanchester’s Square Law, which has 

assumptions that are more in line with contemporary Infantry engagements, in which fire 

can come from multiple directions and multiple targets can be attacked. The models 

assume that each unit can kill only one equivalent unit at a time, and our simulations 
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further assume that the enemy units are comparable to the experimental all-male units 

in strength and equipment. The last assumption is notably strong, but it presents a 

conservative scenario that is worth considering. The models ultimately use differential 

equations to help predict the winner of an engagement and forecast the rate of attrition 

and losses on both sides.

R.5.4 Readiness Data

Data on individual readiness look quite different from our group performance data, so 

they are analyzed differently from the rest. Injuries and related data are recorded for 

individual Marines, and some have multiple observations. This section details the 

analysis techniques used to make conclusions about differences in readiness by 

gender, accounting for other variables. 

R.5.4.1 Modeling counts

For our models of numbers of medical visits or days missed from the experiment, the 

outcome of interest is a count of days. There are two distributions that are frequently 

used to model counts: the Poisson distribution and the Negative Binominal distribution. 

We use the Negative Binomial distribution in our analyses because our data are 

overdispersed and the variance is much bigger than the mean (the variance is equal to 

the mean for the Poisson distribution).

A complicating factor in these analyses is that the outcome of interest is zero for most 

volunteers: most Marines did not miss experimental days; many did not get injured or go 

to see a medic. For data like these, where the number of zeros is more than one would 

expect (given the Negative Binomial distribution), a model that explicitly takes this into 

account is appropriate. This model is called the Zero-Inflated Negative Binomial model, 

which models the outcome in two parts: The first part of the model simply predicts, for 

each person, the likelihood of a non-zero outcome. For instance, for each person, it 

predicts (given a set of covariates) the probability of visiting a medic at all or missing at 

least one experimental day. Then the model predicts the number of times the event will 

happen for those whose outcome is nonzero. In other words, given that this Marine will 

miss experimental days, based on his personal characteristics, how many days do we 

expect him to miss? The data did not allow for estimation of the first part of the model 

using all the personnel variables, so we used only gender. However, the count part of 

the model did include additional personnel variables.

R.5.4.2 Time to first injury or medical visit

In our analysis of who is likely to get injured sooner, we modeled the number of days to 

first occupational injury, as well as the number of days to first medical visit for all 

volunteers. This analysis was done using a Cox Proportional Hazards model—a 

technique in survival analysis that is frequently used to analyze time to an event. The 
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purpose of it is to model the amount of time before an event occurs as a function of 

observed covariates. However, the data are censored: we stopped observing Marines 

when they dropped out of the experiment or when the experiment was over, whichever 

came first. Survival analysis models two attributes of the risk of the outcome of interest 

simultaneously: how it changes over time and how it varies with independent variables 

included in the model. The model results in coefficients indicating the effect of each 

variable, as well as p-values indicating the variables’ statistical significance. 

R.5.4.3 Frailty analyses

Over the course of the experiment, volunteers often got injured more than once. 

Moreover, it is likely that that those injuries are not independent of one another: once a 

person gets hurt, they are more likely to get hurt again than they were to get injured in 

the first place. This can be because they are simply more prone to injuries or because 

some injuries or illnesses tend to manifest themselves multiple times. To model risk of 

injury (per unit of time, an experimental day in our case), we use a frailty model. 

Frailty models are similar to survival models in the sense that the outcome of interest is 

an instantaneous hazard rate. However, a frailty model can be used to describe not just 

time to the first event but also time between events. This is done by incorporating a 

random effect (the frailty), which has a multiplicative effect on the hazard—meaning that 

once someone experiences an injury, he or she is considered more prone to other 

injuries. Thus this model is particularly useful when we have repeated measures for 

some individuals. The random effect in the frailty model allows the estimation of the 

hazard rate for a heterogeneous sample so that individuals have different hazards of 

getting injured.

In a frailty model, two distributions need to be specified ahead of time: the distribution of 

the baseline hazard, and that of the frailty. Several choices exist for each, but it is 

possible to use AIC and Bayesian Information Criterion (BIC) to pick the optimal 

combination of both. For our readiness data, the two criteria chose the Weibull 

distribution for the hazard and the Gamma distribution for the frailties. The estimation of 

the model is based on maximizing a marginal likelihood. The results show the impact of 

included risk factors on a person’s predicted frailty rates and include statistical 

significance. 

R.5.5 Population Variables

We compare the distribution of personnel variables in the GCEITF to that in the USMC 

at large to evaluate whether our volunteer sample is representative of the population 

with respect to these variables. To do so, we compare GCEITF males to the USMC at 

large and also USMC males within their MOS, and GCEITF females to USMC females 

at large (except for 1371s, for whom we provide comparisons within MOS and to all 
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USMC females). The comparison group was picked out to match GCEITF on pay grade 

and other dimensions detailed in Annex Q.

To compare our sample to the population—since we are interested in the entire 

distribution rather than comparing a particular statistic, like the mean—we use the 

Kolmogorov-Smirnov (K-S) test. The K-S test is a nonparametric technique that can 

help decide whether it is likely that a sample came from a particular reference 

probability distribution. To do this, the test compares the empirical distribution function 

for each variable in our GCEITF sample to the cumulative distribution function of the 

comparison population. A significant p-value in this test is an indicator that the two 

distributions differ, and that, on the relevant variable, the sample may not represent the 

population well.
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