2006 National Youth Tobacco Survey 

Methodology Report 
Introduction 

Overview of the National Youth Tobacco Survey (NYTS) 

In conjunction with the state Youth Tobacco Survey (YTS), the National Youth Tobacco Survey 

(NYTS) was developed to provide the data necessary to support the design, implementation, and 

evaluation of state and national tobacco prevention and control programs (TCPs).1,2

 In addition, 

NYTS data supplement other existing data sources that provide prevalence estimates for selected 

tobacco use behaviors among high school students, such as the Youth Risk Behavior 

Surveillance System (YRBSS), by providing more comprehensive data for both middle school 

and high school students (i.e., grades 6-8 and grades 9-12, respectively) that cover tobacco use 

(i.e., bidis,* cigarettes, cigars, kreteks,† tobacco pipes, and smokeless tobacco); exposure to 

secondhand smoke; smoking cessation; school curriculum; minors’ ability to purchase or obtain 

tobacco products; and, knowledge and attitudes about tobacco and familiarity with pro-tobacco 

and anti-tobacco media messages. NYTS data also serve as essential benchmarks against which 

TCPs can compare the magnitude of youth tobacco use and that monitor one of the 10 leading 

health indicators for Healthy People 20103

 that addresses tobacco use (27-2b: Reduce cigarette 

smoking by adolescents). 

First conducted during fall 19994 and again during spring 2000,5 2002,6 2004,7 2006,8 and 2009 

(unpublished) NYTS data are representative of all middle school and high school students in the 

50 states and the District of Columbia. 

Overview of the 2006 NYTS Methodology 

The 2006 NYTS employed a geographically stratified three-stage cluster sample design to 

produce a nationally representative sample of middle school and high school students in the 

United States. Non-Hispanic black, Hispanic, and Asian students were oversampled. Sampling 

procedures were probabilistic and conducted without replacement at all stages, and entailed 

selection of Primary Sampling Units (PSUs) (i.e., a county, or a group of small counties, or part 

of a very large county) within each created stratum, of schools within each selected PSU, and, 

lastly, of students within each selected school. Participating students completed the survey via 

pencil and paper self-administered scannable questionnaire booklet. 

Participation in the NYTS was voluntary at both the school and student level. At the student 

level, participation was also anonymous. Schools used either passive or active permission forms 

at their discretion to fulfill requirements of the No Child Left Behind Act whereby parents must 

be provided with a means to opt out of their child’s participation. The school response rate was 

91.6%, and the student response rate was 87.6%, resulting in an overall response rate (i.e., the 

school response rate multiplied by the student response rate) of 80.2%. 

*

 Bidis (or “beedies”) are small brown cigarettes from India consisting of tobacco wrapped in a leaf and tied with a 

thread.

†

 Kreteks (or “clove cigarettes”) are flavored cigarettes containing tobacco and clove extract.

1 
A weighting factor was applied to each student record to adjust for nonresponse and for varying 

probabilities of selection. Weights were adjusted to ensure that the weighted proportions of 

students in each grade matched national population proportions. Final adjusted weights were 

scaled to ensure that the weighted count of students was equal to the total sample size. 

The remainder of this report provides detailed information on the methodology used in 2006 

NYTS sample selection, data collection, and weighting of student response data. 

• Section I: NYTS Sampling Design 

• Section II: NYTS Sampling Methods 

• Section III: NYTS Data Collection 

• Section IV: Weighting of NYTS Response Data 

2 
SECTION I — NYTS SAMPLING DESIGN 

1.1 Sampling Design Overview

The objective of the 2006 NYTS sampling design was to support estimation of tobacco-related 

knowledge, attitudes, and behaviors‡

 in a national population of public, Catholic, and other 

private school students enrolled in grades 6 through 12 in the United States. More specifically, 

the study was designed to produce national estimates at a 95% confidence level by school level 

(middle school, defined as grades 6-8; and high school, defined as grades 9-12), by individual 

grade, by gender, and by race/ethnicity for non-Hispanic white, non-Hispanic black, Hispanic, 

and Asian students. Please note: subsequent use of the terms “white” and “black” in this report 

pertain to non-Hispanic respondents only; and the variable definition for “Asian” is exclusive of 

Native Hawaiian/Other Pacific Islander (NH/OPI).

Additional estimates, such as cross-tabulations of grade by gender and of race/ethnicity by 

school level, were also supported; however, precision levels will vary considerably according to 

differences in one sub-population’s cell sizes versus another’s. 

The universe for the study consisted of all public, Catholic, and other private school students 

enrolled in regular middle schools and high schools in grades 6 through 12 in the 50 states and the 

District of Columbia. Alternative schools, special education schools, Department of Defense

operated schools, vocational schools that serve only pull-out populations, and students enrolled in 

regular schools unable to complete the questionnaire without special assistance were excluded. 

The NYTS utilized a geographically stratified, three-stage sampling design. The sampling frame 

was stratified by Census Region,9

 Metropolitan Statistical Area (MSA) status10 and, implicitly, 

by state (i.e., the frame was sorted by state). Sampling procedures were probabilistic and 

conducted without replacement at all stages, and entailed selection of PSUs within each created 

stratum, of schools within each selected PSU, and, lastly, of students via whole classrooms (i.e., 

all students in any one class) within each selected school. Black, Hispanic, and Asian students 

were oversampled using a modified weighted measure of size (MOS) that increased the 

probability of selection of PSUs and schools with disproportionately high minority student 

enrollments. The measure of size was adjusted to equalize the expected sample size by grade. 

Stage I: Selection of PSUs 

At the first sampling stage, 91 main PSUs were selected from eight strata with probability 

proportional to the total number of eligible students enrolled in all eligible schools located 

within a PSU. 

Stage II: Selection of Schools 

At the second sampling stage, three schools were selected on average from each main PSU, 

and one school selected from each of 16 sub-sampled PSUs randomly selected from the 91 

‡

 See Section 3.1, Survey Instrument, for the specific indicators measured.

3 
main PSUs. Both were conducted with probability proportional to the total number of 

eligible students enrolled in a school. 

Stage III: Selection of Students

At the third sampling stage, students were selected via whole classrooms whereby all 

students enrolled in a selected class were by default chosen for participation. Classes were 

selected from course schedules provided by each school that agreed to participate. 

Schedules were constructed such that all eligible students were accounted for, each having 

one and only one chance of being selected. Classes were then randomly selected from 

each schedule using a fixed interval with a random start, with the start set within the initial 

interval. The interval used varied by school according to the total number of eligible 

students enrolled in a school, and thus how many students were anticipated to be enrolled 

on average in each class listed within a course schedule. 

1.2 Designed Sample Sizes 

Utilizing the same sampling plan as was used for the 2004 NYTS,7

 the sample was designed to 

employ a large enough sample size to yield reliable estimates within ± 5% confidence interval 

for the following variables: 

1. School level (univariate): All middle school students in total and all high school students 

in total. 

2. Individual grade (univariate): Grades 6, 7, 8, 9, 10, 11, and 12, separately. 

3. Gender (univariate and bivariate): Males and females separately in total, as well as each 

gender by school level (e.g., male middle school students, female high school students, etc.) 

and by individual grade (e.g., 6th grade males, 6th grade females, etc.). 

4. Race/ethnicity (univariate and bivariate): White, black, Hispanic, and Asian students 

separately in total, as well as each race/ethnicity by school level (e.g., Hispanic middle 

school students, Asian high school students, etc.). 

To achieve these precision requirements, the study required obtaining completed surveys from 

approximately 24,500 students. The sampling design specified the selection of approximately 

equal numbers of students from each grade: 

• 10,500 middle school students at 3,500 students per grade 

• 14,000 high school students at 3,500 students per grade 

It was necessary to draw an initial sample considerably larger than this target number of 

completed interviews to compensate for school and student non-participation. Response rates 

attained in prior cycles of the NYTS have ranged from 83% to 90% for schools and 91% to 93% 

for students. However, for sampling purposes more conservative response rates of 82% for 

schools, 85.5% for students, and, subsequently, a combined overall response rate of 

approximately 70% were assumed. 

4 
Projecting a large sample of this size permits analysis by individual grade and by gender without 

any special considerations in the sampling plan, as grade and gender subgroups both typically cut 

evenly across schools, and gender subgroups typically cut evenly across grades with males and 

females each constituting about half of the students selected, or an anticipated 12,250 students 

per gender group. As design effects are relatively small for subgroups that cut evenly across 

clusters11 (i.e., schools), gender group estimates will have better precision than other groups that 

are less evenly dispersed across schools (e.g., racial/ethnic groups). Thus, confidence intervals 

for univariate gender estimates will be within ± 3%. These same estimates will, however, be 

more precise at the high school level than those at the middle school level as the design expects 

to yield a greater number of completed surveys from high school students (i.e., 3,500 completes 

from each of four high school grades) than from middle school students (i.e., 3,500 completes 

from each of three middle school grades). In comparison, bivariate estimates of gender by grade 

will be within ± 5%, as within grade estimates by gender have slightly larger standard errors than 

those for estimates by grade alone. 

The number of students to be randomly selected per school served as another NYTS design 

parameter. This determination required balancing schools’ student enrollment size and the 

degree of burden that would be placed on schools if substantially more students were selected 

from those with higher enrollment counts. For consistency with prior survey cycles, a target 

sample size of 125 students per school was maintained, equating on average to the selection of 

five classes with a range typically between four to six classes. However, the actual number of 

classes needed to target 125 students within a school ultimately depends on the average 

enrollment count per eligible class. The design was based on an anticipated average yield of 

103.8 students per school across both large and small schools. This yield is similar to student 

yields attained in the 2002 and 2004 cycles of the NYTS but lower than student yields attained in 

the 1999 and 2000 NYTS surveys. 

Small Schools 

About 6.5% of U.S. students attend small schools, defined as those in which < 125 eligible 

students are enrolled. As they are unable to yield the targeted 125 students, they often require a 

census, or near-census, of all eligible students as compared to a random selection of eligible 

students in large schools. In turn, this typically equates to a larger average number of classes 

selected for participation among small schools than among large schools, as the former tend to 

have a lower average enrollment count per class as compared to the latter. 

Again, while there are a fair number of small schools in the U.S., they account for only a 

nominal proportion of the total eligible student population. As a result they are more expensive 

per student survey, as they incur all of the same costs involved with recruiting a school and 

dispatching a field data collector, but produce smaller samples. Thus, like previous NYTS 

cycles, small schools were assigned to a separate stratum within each PSU. The requisite sample 

allocation to the small school stratum was computed, creating a target number of small schools to 

be selected from the same PSUs used in the main sample. Coverage of the middle school and 

high school strata was guaranteed by the main sample draw; the supplemental draw guaranteed 

coverage of the small school segment of the population. 

5 
Middle School and High School Estimates

Estimates by school level are required to support separate analysis of students across middle 

school grades and across high school grades. However, schools tend to vary in their grade 

structures, an inconsistency that can compromise the ability to easily and efficiently cluster 

schools for sampling purposes in a manner that also uniformly divides students by grade. For 

example, 9th grade students are served by both grades 7-9 junior high schools and by grades 9-12 

high schools. Thus, an approach utilizing an implicit stratification scheme, whereby the 

sampling frame was sorted by grade, was used. 

Gender Group Estimates 

The large projected sample size permits analysis by gender without any special considerations in the 

sampling plan. During the class selection process for co-educational schools, any otherwise viable 

sampling frame configuration of eligible classes that would have included male-only enrolled or 

female-only enrolled classrooms were avoided whenever possible. 

Racial Group Estimates 

Probability Proportional to Size (PPS) sampling methods with a weighted MOS were used to 

increase the likelihood of selecting PSUs and schools with relatively high minority enrollment 

and, subsequently, the likelihood of selecting classrooms with relatively high concentrations of 

minority students. This approach yielded sample sizes sufficient enough to support separate data 

analysis for white, black, Hispanic, and Asian students, both in total and by school level. Sample 

sizes were not designed, however, to support detailed analyses by gender and school level within 

racial/ethnic subgroups (e.g., middle school Hispanic males). 

As wording of the race/ethnicity questions changed with the 2004 survey cycle, the 2004/2006 

NYTS race/ethnicity coding scheme described below was applied to 2000 and 2002 NYTS data 

in as consistent a manner as possible in order to compute and compare racial/ethnic distributions 

across all four spring-based survey cycles. Accordingly, Table 1 presents the reported numbers 

of white, black, Hispanic, Asian, NH/OPI, and American Indian or Alaska Native (AI/AN) 

students that participated in each implementation. 

6 
Table 1: 

Actual Racial/Ethnic Group Sample Sizes, NYTS 2000-2006 

Racial/ 

Ethnic Subgroup

2000 NYTS 

No. of Students 

Group 

Size

% of 

Sample

2002 NYTS 

No. of Students 

Group 

Size

% of 

Sample

2004 NYTS 

No. of Students

Group 

Size

% of 

Sample

2006 NYTS 

No. of Students 

Group 

Size

% of 

Sample

White 19,537 54.5% 12,627 48.3% 12,616 45.2% 11,736 43.4% 

Black 5,750 16.0% 4,913 18.8% 5,137 18.4% 5,302 19.6% 

Hispanic 7,445 20.8% 6,392 24.4% 7,288 26.1% 7,212 26.7% 

Asian 1,711 4.8% 1,282 4.9% 1,293 4.6% 1,405 5.2% 

NH/OPI 447 1.2% 305 1.2% 205 0.7% 297 1.1% 

AI/AN 637 1.8% 395 1.5% 351 1.3% 305 1.1% 

Missing 301 0.8% 235 0.9% 1,043 3.7% 781 2.9% 

Total 35,828 100.0% 26,149 100.0% 27,933 100.0% 27,038 100.0% 

In the 2000 and 2002 survey cycles, race/ethnicity was defined via the combination of two 

separate race/ethnicity questions.12,13 The response set was identical for both questions, each 

providing five race response options and one Hispanic ethnicity response option. The first 

question allowed respondents to select multiple responses if applicable, and the second asked for 

a single best response. Using a process developed by Centers for Disease Control and 

Prevention/Office on Smoking and Health (CDC/OSH), these responses were then combined into 

a single race for reporting purposes as follows: 

If a student selected only one response for the multi-response race/ethnicity question they 

were categorized according to the single race/ethnicity indicated therein, regardless of 

whether or how they may have answered the single-response race/ethnicity question that 

followed. 

Alternately, if a student selected multiple responses for the multi-response race/ethnicity 

question, of which one was “Hispanic”, they were categorized as Hispanic regardless of 

what additional response(s) may have been selected therein, and regardless of whether or 

how they may have answered the single-response race/ethnicity question that followed. 

Lastly, if a student selected multiple responses for the multi-response race/ethnicity 

question, but “Hispanic” was not among those chosen, and provided a response for (i.e., 

did not skip) the single-response race/ethnicity question that followed, they were 

categorized according to the single race/ethnicity indicated therein. 

With the transfer of NYTS administrative and operational oversight from the American Legacy 

Foundation to CDC/OSH beginning with the 2004 survey cycle, the race/ethnicity two-question 

7 
series was changed in order to comply with Office of Management and Budget (OMB) Directive 

No. 15, Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity.14 

The series was changed to a stand-alone yes/no question regarding Hispanic ethnicity, followed 

by a multi-response race question that uses the exact same five race response options as those 

used in the earlier surveys but with the previously used Hispanic ethnicity response option 

removed.15,16 As in prior cycles, responses were combined into one single race/ethnicity variable 

for reporting purposes, with the method modified for the 2004 and 2006 cycles per the following 

in order to account for the question changes: 

If a student selected “Yes” for the Hispanic ethnicity question they were categorized as 

Hispanic, regardless of whether or how they may have answered the multi-response race 

question that followed. 

Alternately, if a student selected “No” to the Hispanic ethnicity question, and selected 

only one response for the multi-response race question that followed, they were 

categorized according to the single race indicated therein. 

Lastly, if a student selected “No” to the Hispanic ethnicity question, but selected multiple 

responses for the multi-response race question that followed, a hierarchical coding 

scheme was used to assign them to a single race category. 

1.3 Actual Sample Yield and Participation Rates 

Of the 289 selected schools, those that had been selected in Louisiana (four in total) were later 

removed from the sample due to the emergency responses that were in effect following 

Hurricane Katrina. At that time, Louisiana schools were closed to all outside, non-essential 

research. Entirely removing these four schools rather than deeming them selected and eligible 

but non-participating was consistent with how selected schools that have been closed due to a 

natural disaster or a terrorist act or threat have been handled in the past by the National Youth 

Risk Behavior Survey (National YRBS) and NYTS. The response rates presented in this report 

are reflective of this decision, with the four schools removed from both the numerator and the 

denominator of response rate calculations. Please note: the number of schools selected for the 

2006 NYTS will be reported as 285 rather than 289 from this point onward. A comparative 

analysis of the Katrina affected schools can be found below. 

Participation rates for this survey were high (Table 2) and generally comparable to participation 

rates achieved in the prior cycles of NYTS. Of the 285 selected schools, 261 (91.6%) 

participated in the 2006 NYTS. Among the 30,875 selected students enrolled at the 261 

participating schools, 27,038 (87.6%) participated. This resulted in a combined overall response 

rate of 80.2%.§

§

As a point of comparison, if the Louisiana schools had been included in the response rate calculations as selected 

but non-participating, the school response rate would have been 90.3% (261/289) and, with the student response rate 

staying the same, the overall response rate would have been 79.1%.

8 
Table 2: 

Participation Rates and Number of Participants, 2006 NYTS 

Number Selected Number Participated Participation Rate (%) 

Schools 285 261 91.6% 

Students 30,875 27,038 87.6% 

Comparative Analysis of Katrina Affected Schools 

The four removed Louisiana schools were the only schools selected in the PSU from which they 

came. A comparative analysis was conducted to examine any potential data bias this may have 

introduced. Non-response biases are a function of two factors: 1) the magnitude of the nonresponse and 2) the extent to which non-responding students do or do not differ from those who 

responded. Thus, the extent to which non-response bias may have arisen is related to the 

proportion of all the eligible schools represented in the initial, full sampling frame that were 

impacted, and the extent to which the student population in the removed schools did or did not 

differ from the rest of the eligible U.S. student population. 

The Louisiana PSU in which the four removed schools were located, Acadia Parish (PSU 

22001), lies approximately 200 miles from New Orleans, LA and approximately 100 miles west 

of Baton Rouge, LA. It was a small PSU similar to many other non-urban Southern PSUs. 

According to 2004 U.S. Census data, it has a total population of about 60,000 of whom 

approximately 80% of the residents are white. Despite the removal of schools selected from this 

PSU, schools very similar to these were still well represented both in the sample of schools 

selected from the non-urban strata and in those that subsequently participated. 

Table 3 on the next page presents demographic characteristics of the four removed schools in 

comparison to those of the selected sample and to those of the full sampling frame from which 

they were selected, including within-selected sample and within-sampling frame comparisons 

(i.e., demographic characteristics of each with the four removed schools included vs. excluded). 

The four removed Louisiana schools represented a negligible proportion of the 64,816 total 

eligible schools in the initial sampling frame (magnitude = 4/64,816 = 6.2 x 10-5%). Likewise, 

the extremely low enrollment of Hispanic and Asian students—two of the three racial/ethnic subpopulations the 2006 NYTS sought to over-represent—implies negligible bearing on any 

potential compromising of the sample design. Table 3 also shows that the grade distribution 

among the four removed schools was almost identical to that overall, with a parallel skewing 

towards the high school grades. Lastly, the gender distribution was balanced in the four removed 

schools just as it was and remains in the U.S. as a whole.

9 
Table 3: 

Demographics of Removed Schools, 

Selected Sample, and Sampling Frame, 2006 NYTS 

Characteristic 

Four Removed 

Louisiana 

Schools 

Total Selected 

Sample (Incl. 

LA Schools) 

Total Selected 

Sample (Excl. 

LA Schools) 

Total Sampling 

Frame (Incl. 

LA Schools) 

Total Sampling 

Frame (Excl. 

LA Schools) 

Sex 

Female 50.4% 48.8% 48.8% 48.9% 48.9% 

Male 49.6% 51.2% 51.2% 51.1% 51.1% 

Race/Ethnicity 

White 71.2% 47.8% 47.7% 65.1% 65.1% 

Black 28.1% 20.9% 20.9% 15.4% 15.4% 

Hispanic 0.7% 23.5% 23.6% 14.1% 14.1% 

Asian 0.7% 6.8% 6.8% 3.9% 3.9% 

Grade 

6th 10.0% 8.6% 8.6% 15.9% 15.9% 

7th 9.2% 10.5% 10.5% 15.2% 15.2% 

8th 9.8% 10.2% 10.2% 14.9% 14.9% 

9th 21.6% 21.7% 21.7% 15.8% 15.8% 

10th 18.3% 18.3% 18.3% 13.9% 13.9% 

11th 16.5% 16.2% 16.2% 12.7% 12.7% 

12th 14.7% 14.4% 14.4% 11.6% 11.6% 

10 
SECTION II — NYTS SAMPLING METHODS

The sampling frame included public, Catholic, and other private schools in the 50 states and the 

District of Columbia with at least one grade in the 6th through 12th grade range. The sampling 

process employed a three-stage stratified cluster design whereby PSUs, schools within PSUs, and 

classrooms within schools were probabilistically selected without replacement. The sampling 

approach utilized PPS sampling methods, in which the probability of a particular PSU being 

selected was proportional to the total number of eligible students enrolled in all eligible schools 

located within the PSU, and the probability of a particular school being selected proportional to 

the total number of eligible students enrolled in the school. A weighted MOS that increased the 

chances of selecting PSUs and schools with relatively high minority enrollment was also used, 

thereby increasing the likelihood of selecting classrooms with relatively high concentrations of 

minority students. 

2.1 Measure of Size (MOS)

Oversampling of black, Hispanic, and Asian students was accomplished using a modified MOS 

during the PPS sample selection steps. This increased the chances of schools with relatively large 

minority enrollments entering the sample, with the effectiveness of this approach dependent upon 

the extent to which these sub-groups are or are not evenly distributed across eligible schools. 

The known uneven distribution of students by race in the U.S makes a weighted MOS a sound 

means of oversampling. In comparison, if all U.S. schools had identical percentages of 

minorities, then a sample of students from any sample of schools would mirror the national 

percentages and use of a weighted MOS would fail to oversample minority students. 

With regard to Asian students, oversampling was not conducted for the 1999 NYTS. For NYTS 

2000, 2002, and 2004, a MOS was used to oversample Asian and Pacific Islander students as a 

combined group, as this is how they are classified17 (Appendix A) by the Quality Education 

Data, Inc. (QED)18 files that served as the sampling frame. As this imposes notable limitations 

on the ability to oversample either population separately, the 2006 NYTS modified the 

oversampling approach in order to focus specifically on Asian students, exclusive of Pacific 

Islander students. In order to estimate the number of Asian students, and subsequently to permit 

a more accurate oversampling of this sub-population, Census data were used to create a ratio by 

county of Asians out of the combined Asian/Pacific Islander population. This ratio was then 

used for adjustment and was multiplied by the QED Asian/Pacific Islander enrollment data. 

Lastly, the adjusted enrollment data were used as the basis for applying the MOS to NYTS Asian 

student data. 

The weighting function used for 2006 NYTS was: 

raA + rbB + rhH + roO 

where the r's are the weighting factors for the Asian, black, Hispanic and Other non-Hispanic nonwhite populations, respectively. 

11 
The weighted measure of size was also modified by the ratio of a given grade’s enrollment to the 

12th grade enrollment. This had the effect of equalizing the size of the grade level enrollment so as 

to more equally distribute the sample across grades. 

The weighting function used was: 

Size = ∑ ER (1.0O +10.0H + 5.0B + 20.0A )

i∈grades i i i i i

where i denotes the grade, ERi denotes the enrollment ratio for the i

th grade, and Ai, Bi, Hi, and Oi

denote the minority enrollment for that grade as described above. 

This weighted measure of size was summed to compute stratum and PSU sizes. Disproportionate 

weighting subsequently increased the allocation of the sample to high-minority strata and increased 

the chances of PSUs with high minority concentrations in these strata being included in the sample. 

2.2 Stage 1 – Selection of PSUs

PSU Definition 

The following parameters were set in defining PSUs: 

• Each PSU should be large enough such that it contains no fewer than the average number 

of schools and students typically selected per PSU.**

• Each PSU should not be so large as to be selected with certainty. 

• Each PSU should be compact geographically so that field staff can go from school to 

school easily. 

• There should be recent data available (ideally, no more than one year old) to characterize 

the PSUs. 

Generally, PSUs were comprised of a single county. However, where needed, multiple counties 

with lower than the requisite population were combined to create a PSU of an acceptable size 

and, likewise, very large counties were broken down into multiple PSUs in order to minimize 

certainty of selection. 

County population figures were aggregated from school enrollment data for the grades of 

interest. Enrollment data were obtained from the most recent Common Core of Data (CCD)19

from the National Center for Education Statistics (NCES) and the current school and school 

district QED data files. The NYTS 2006 PSU definitions are consistent with those used in 

previous NYTS cycles. 

** See Section 1.2, Designed Sample Sizes, for requisite size details.

12 
Stratification and Selection of PSUs 

PSUs were explicitly stratified into eight first-stage strata according to Census Region9

 and 

urban/non-urban MSA10 status. PSUs were classified as “urban” if they were in one of the 54 

largest MSAs in the U.S.; otherwise, they were considered “non-urban”. In addition, the PSUs 

were implicitly stratified by five-digit zip code (i.e., the frame was sorted by zip code) in each 

first-stage stratum. 

A sampling interval was computed for each stratum by dividing the sum of the MOS for the 

PSUs in the stratum by the number of PSUs to be selected. Any PSUs larger than 80% of the 

sampling interval were split into equal-sized sub-PSU units, with schools from the regular 

selected PSU randomly assigned to the new sub-PSU units. A total of 91 main PSUs were then 

selected from the eight strata, and a subsample of 16 PSUs selected from the 91 main PSUs, both 

with PPS systematic random sampling methods. 

Table 4 summarizes the first-stage sample allocation, showing the number of PSUs on the 

sampling frame and the number of PSUs selected in each of the eight first-stage strata. Strata 

are labeled by Census Region (1-4) and urban or non-urban status (U, N). These first-stage strata 

should be distinguished from the second-stage school strata (large vs. small schools). 

Table 4: 

Summary of first-stage stratification, 2006 NYTS 

Stratum PSU Count 

Sampling Frame Selected 

1N 118 7 

1U 52 10 

2N 376 12 

2U 61 9 

3N 450 19 

3U 87 13 

4N 133 9 

4U 34 12 

Total 1,311 91 

2.3 Stage 2 – Selection of Schools 

Stratification and Selection of Schools

Prior to sampling schools within each PSU, eligible schools were implicitly stratified by grade 

(i.e., the frame was sorted by grade) to help equalize sample sizes for each grade in support of 

grade-specific estimates, and by geographic location to obtain good dispersion across schools 

with differing minority compositions. Schools were sorted from highest grade to lowest grade, 

by zip code and enrollment, and then explicitly assigned to either the “large” or “small” school 

strata. Refusing schools were not replaced. The sample sizes anticipated a certain amount of nonparticipation by allowing for refusals in calculating the number of schools initially drawn. 

13 
Large Schools 

Three large schools were selected on average per main selected PSU with probability proportional 

to the weighted measure of school enrollment size, using a PPS systematic sampling procedure with 

a random start. 

Small Schools 

One small school was selected per sub-sampled PSU with probability proportional to the weighted 

measure of school enrollment size. 

2.4 Stage 3 – Selection of Students 

Students were selected for participation by default via the random selection of whole classrooms, 

with all students enrolled in a selected class who are able to complete the questionnaire without 

special assistance eligible to take the survey. Refusing students were not replaced. 

Classes were selected from course schedules provided by each school that agreed to participate. 

Schedules were constructed such that all eligible students were accounted for, each having one 

and only one chance of being selected. The specific method then used to select classes varied from 

school to school according to how a school’s class schedule was structured and implemented. 

Typically, though, classes were selected from a list of required core courses such as English, social 

studies, math, or science. Among middle school students, and among high school students in a few 

states, physical education and/or health also were considered core courses. In a small number of 

schools, however, it was extremely difficult to develop an appropriate frame using this particular 

approach. Therefore, in such schools, classes were selected by using a time of day (e.g., second 

period) when all eligible students were scheduled to be attending a class of one kind or another, and 

randomly selecting from all classes held at that time. School homerooms were occasionally used as 

the frame for class selection; a less-favored arrangement, however, as relatively few schools hold 

homeroom of duration sufficient enough for conducting the survey. Lastly, as mentioned in Section 

1.2 (see Gender Group Estimates), the class selection process for co-educational schools avoided 

using any otherwise viable sampling frame configuration that would have included male-only 

enrolled or female-only enrolled classrooms whenever possible. 

The target number of students to be selected within a given school remained constant at 125 for 

large schools; but, by default, this number was lower in small schools with fewer than 125 students 

enrolled across the grades of interest. The subsequent number of classes needed to obtain these 

targeted students was estimated by dividing the total enrollment of the grades of interest by the 

number of eligible classes available in the chosen core subject area or during the time period from 

which classes would be selected. 

An Excel program using a fixed interval with a random start set within the initial interval was then 

used to identify the specific classes to be surveyed. On average this equated to the selection of five 

classes per large school (typical range of four to six classes) with the expectation that this would 

meet or exceed the 125 student yield requirement. However, because this process employed 

average class sizes, in practice the number of students actually selected in each school varied from 

14 
this 125 student target. Nonresponse at the student level was accounted for in the sample size 

using an average per class yield that assumed student response rates derived from historical 

experience with the NYTS.

2.5 Probabilities of Selection 

This section describes the probabilities of selection associated with the various sampling stages. 

These probabilities provide the basis for the sampling weights discussed in Section IV, Weighting 

of NYTS Response Data. 

If ni is the number of PSUs to be selected from stratum i, Si is the size of stratum i, and Sij is the size 

of PSUi in stratum i (in all cases "size" refers to MOS), then the probability of selection of PSUi is 

niSij/Si. For the three schools to be selected in PSUi, Sijk is the size of school k in PSU j in stratum i,

and then the conditional probability of selection of the school given the selection of the PSU is 

3Sijk/Sij. If Cijk is the number of classes in school ijk and m is the number of classes to be selected, 

then the conditional probability of selection of a class is m/Cijk. Since all students were selected, the 

conditional probability of selection of a student given the selection of the class is unity. 

The overall probability of selection of a student in stratum i is the product of the conditional 

probabilities of selection: 

Equation 1: 

⎛

⎜

⎜

⎜

⎝

n

i

S

ij

S

i

⎞

⎟

⎟

⎟

⎠

3S

ijk

S

ij

⎛

⎜

⎜

⎜

⎝

m

C

ijk

⎞

⎟

⎟

⎟

⎠

Note that if the number of classes were exactly proportional to the size of the school, then the 

probability of selection for a student would be constant throughout each stratum. This sort of 

self-weighting sample tends to be statistically efficient. The probabilities of selection were the 

same for all students in a given school, regardless of their ethnicity, but varied across schools 

depending upon the racial/ethnic mix of the schools and their surrounding regions. 

15 
SECTION III — NYTS DATA COLLECTION 

3.1 Survey Instrument 

The NYTS collects data on key short-term, intermediate, and long-term tobacco prevention and 

control outcome indicators. The 2006 survey instrument included a total of 81 questions, the 

first seven of which collect student demographic information and the remaining measuring a 

comprehensive set of tobacco-related topics (Appendix B). Specifically, areas covered by the 

survey included prevalence of tobacco use, knowledge of and attitudes towards tobacco use, proand anti-tobacco media and advertising, minors’ access to tobacco products, nicotine 

dependence, cessation attempts, exposure to second-hand smoke, and tobacco use prevention 

school curricula. 

3.2 Recruitment and Scheduling of Schools 

The schools selected to participate in the 2006 NYTS fell across 41 different states. Recruitment 

began in July 2005 with calls to State Departments of Education and Health. Letters of support 

were obtained from various national partner and other stakeholder agencies and organizations, 

and then used in mailings to districts and schools. A date for survey implementation was 

selected to optimize the efficiency of data collection while accommodating school schedules. In 

selecting a date, convenience to the school and its calendar were considered while also trying to 

schedule groups of schools from the same school district or PSU around the same time to 

facilitate efficient travel to and survey implementation within selected schools. Recruiters used 

an electronic calendar on a secure, shared drive to facilitate communication and to avoid 

scheduling two schools for the same data collector on the same day. 

3.3 Mailings to Schools 

After schools had been recruited, classes selected, and a date scheduled, each school received a 

packet of pre-survey materials. These materials included all the information necessary to prepare 

the school for data collection. Teacher packets contained the parental permission forms that had 

to be given out to all students in the selected classes prior to data collection. The timing of these 

pre-survey packet mailings was determined in part by the type of permission form being used by 

the school. Passive parental permission forms (forms required to be returned only if a parent or 

legal guardian does not want their child to participate) were sent approximately one week prior 

to the scheduled date of data collection. Active parental permission forms (forms required to be 

returned with a parent’s or legal guardian’s signature in order for the child to participate) were 

sent out at least two weeks prior to the scheduled date of data collection. Follow-up calls were 

made to the selected schools to answer any questions and make sure materials were received and 

distributed to selected classes and students. 

16 
3.4 Hiring and Training Data Collectors 

Data collectors were recruited from a pool of previously trained data collectors as well as retired 

teachers associations, school health networks, and a variety of health education listservs. Data 

collector training was conducted on March 2 – 4, 2006. Initially, data collectors observed 

everything they would have to say or do as “experts” performed it. Then they acquired these 

skills through practice, demonstrated them to each other, and finally refined each other’s 

performance through constructive feedback. Appendix C presents the training agenda from the 

2006 NYTS Data Collector Training. 

3.5 Management and Support of Data Collectors in the Field 

On a weekly basis, data collectors received mailings containing their assignments for the coming 

week, travel and logistical information to get them where they need to be, and their must-read 

weekly bulletin. Weekly bulletins underlined key performance issues, corrected misconceptions, 

provided consistent direction on any procedural changes, and kept everyone abreast of the latest 

must-have information. In addition to these mailings, boxes of survey supplies were sent to data 

collectors either to the data collector’s home or hotel. These boxes contained all supplies 

necessary for completing the data collection, including questionnaires, data envelopes, field 

forms, and pencils. Data collectors were supplied with extra materials for emergency packs as 

well, which they carried with them at all times. 

In addition to receiving multiple mailings, supervisors remained in close contact with the data 

collectors by phone and email, including daily contact during the first week and no less than 

twice-weekly contact thereafter. Phone calls were specifically used to review performance, 

provide reminders, and give emotional support. Further, the calls gave data collectors the 

opportunity to ask questions, provided feedback from schools, and discussed difficult or 

rewarding data collection experiences. 

3.6 Survey Administration 

Survey administration in the schools began on March 6, 2006 immediately after data collector 

training and continued until June 6, 2006. Each data collector visited an average of three schools 

per week. While the details of each data collection varied, there were six core steps followed for 

every school: 

1. Pre-contact call with the principal or lead contact prior to arrival at the school; 

2. Entry meeting with the principal or lead contact; 

3. Entry meeting with teacher or group of teachers prior to survey administration 

4. Survey administration; 

5. Post-survey meeting with the teacher or teachers; and, 

6. Post-survey meeting with the principal or lead contact prior to leaving the school. 

Most survey administrations could be completed in one day, while at other times, due to the 

number of classes selected or class schedules with an alternating block structure (e.g., class 

17 
schedule and implementation differs Monday-Wednesday-Friday vs. Tuesday-Thursday), the 

data collector needed to return for a second day. Procedures were designed to protect students’ 

privacy by assuring that student participation was anonymous and voluntary. Students 

completed a pencil and paper self administered scannable questionnaire booklet. 

3.7 Make-up Sessions 

A make-up list of students in selected classes who were eligible to participate but absent on the 

day of the survey were compiled. Copies of the make-up list were given to the applicable 

teacher and to the school’s principal/lead contact; one also was kept by the data collector. Every 

effort was made to have the data collector return to each of these schools at least once to conduct 

a make-up session if necessary. However, sometimes there was no opportunity for the data 

collector to return to a school prior to leaving for the next site; or, coming back while the data 

collector was still in the area was too soon for a make-up session. In these and other similar 

situations, teachers were asked to administer makeup surveys and send them back in the 

provided pre-paid business reply envelopes. These supplementary make-ups closely followed 

the National YRBS model for teacher-administered make-up sessions.20

Student anonymity was protected throughout the make-up process, with no means of connecting 

a make-up survey with a particular student. There were no student-level identifiers on the 

questionnaire, and school-level identifiers remain confidential and have not been released. Once 

data collection was completed, all make-up lists were destroyed. 

The use of make-up sessions ensured comparability of data and protected respondent anonymity 

while at the same time maximizing response rates. After the completion of all data collection in 

a school, data collectors sent thank-you letters to each of the participating teachers and the 

principal/lead contact. In addition to expressing appreciation for the cooperation received, this 

allowed the data collector an opportunity to connect once more with the staff at the school, 

inquire as to the status of make-ups expected, and encourage further participation.

18 
SECTION IV — WEIGHTING OF NYTS RESPONSE DATA 

This section describes the procedures used to weight the 2006 NYTS student response data, with 

focus on the development of these weights. The final student level response data were weighted to 

reflect the initial probabilities of selection and non-response patterns, to mitigate large variations in 

sampling weights, and to post-stratify the data to known sampling frame characteristics via a 

process involving the steps outlined below: 

• Sampling Weights 

• Non-response Adjustments 

• Adjusting Weights for National Estimates 

• Weight Trimming 

• Post-stratification to National Estimates of Racial Percentages by Grade 

4.1 Sampling Weights 

The basic weights were computed on a case-by-case basis as the reciprocal of the probability of 

selection of that case. A base weight, or sampling weight, incorporating adjustments for nonresponse and scaling to total school enrollment at the student level, was computed in three stages. 

PSU-level Probabilities 

The PSU component of the sampling weight was computed by the sampling program as part of the 

sampling process, with certainty PSUs handled as described in Section 2.2, Selection of PSUs. 

The resulting weight was: 

Equation 2: 

W P

ij = Si

ni Sij

For small schools, the PSU component of the weight was multiplied by the ratio of the number of 

PSUs to the number of PSUs selected to have a small school drawn; specifically, this ratio is 90/15, 

or 6.0. 

Appendix D gives, for each sampled PSU, the PSU size measure, the PSU-level sampling weight 

after removal of certainty PSUs, and the number of times the PSU was expected to be taken into the 

sample (i.e., probability of selection for non-certainty PSUs). 

19 
School-level Probabilities

The school level component of the sampling weight also was computed by the sampling program, 

accounting for schools selected with certainty. The weight was computed as in Equation 3 with 

Appendix E giving the school measure of size and the school component of the sampling weight. 

Note that for schools identified as small schools, only one school was selected per subsampled PSU. 

Equation 3: 

Student-level Probabilities 

The student level component of the sampling weight was computed to include a post-stratification 

adjustment to total school enrollment. If rijk is the number of responding students in the school k, 

PSU j, stratum i, and Eijk is the school enrollment in eligible grades, then the weight of student l

adjusted for non-response is: 

Equation 4: 

W R

ijkl = 

Eijk

rijk

4.2 Non-response Adjustments 

An overall adjustment for school non-response was made by stratum, adjusting the sum of the 

student weights to the weighted measure of size of that stratum. This adjustment was made 

separately for large and small schools. 

Equation 5: 

Fi ,l arg e =

⎛

⎜

⎜

⎜

⎝

∑

k

W S

ijkW Pij Sijk

∑

k∈Stratum i respondents

W S

ijk W P

ij S

ijk

⎞

⎟

⎟

⎟

⎠

The final weight of student l is Fi,l arg eW S

ijkW Pij W Rijkl . School response rates by strata and PSU, and the 

resulting non-response adjustment factors, are detailed in Table 5. For small schools, a similar 

adjustment was computed using the entire small school sample as the adjusting class as shown in 

Equation 6 below. 

20 
Equation 6: 

Fsmall =

∑

i, j,k

W S

ijkW Pij Sijk

∑

k∈small samplerespondents

W

S

ijkW P

ij Sijk

Table 5: 

School Non-Response Adjustments, 2006 NYTS

Selected Schools Participating Schools 

School 

Size 

Stratum 

Weighted 

Measure of Size 

(# of Students) 

Count 

(# Schools) 

Weighted 

Measure of Size 

(# of Students) 

Count 

(# Schools) 

School 

Response 

Rate (%) 

School NonResponse 

Adjustment 

Large 1N 3,215,436 21 3,061,992 20 95.2% 1.05011 

1U 8,918,512 30 8,015,811 27 90.0% 1.11262 

2N 5,103,389 36 4,960,074 35 97.2% 1.02889 

2U 6,516,893 27 6,278,702 26 96.2% 1.03794 

3N 12,893,809 54 11,969,171 50 92.6% 1.07725 

3U 13,269,020 39 11,555,259 34 87.2% 1.14831 

4N 8,162,800 27 6,936,037 23 85.2% 1.17687 

4U 17,491,901 36 15,515,553 32 88.9% 1.12738 

Overall 75,571,763 270 68,292,601 247 91.5% 1.05011 

Small Overall 4,175,869 15 4,158,699 14 93.3% 1.00413 

4.3 Adjusting Weights for National Estimates 

The results of the weighting steps described above were a set of weights useful for producing 

accurate estimates by stratum. However, because weighted measures of size were used, 

development of national estimates required a re-weighting of the strata to total student enrollment. 

This provides two benefits: the weights are adjusted to represent strata in the correct proportions, 

and simultaneously adjusted to sampling frame totals. 

The adjustment for stratum i was computed as: 

Equation 7: 

Afi = Ei

∑

i

W i

where Ei = enrollment totals for grades 6 - 12 and Wi is the sum of all adjusted weights for 

respondents in stratum i. 

21 
Table 6 gives the enrollment, weight and adjustment for each stratum. Adjustments were made 

based on the total enrollment in all eligible grades.

Table 6: 

Enrollment Weight Adjustments, 2006 NYTS 

Stratum Student Enrollment 

Number in Sampling 

Frame 

Sum of Adjusted Weights Enrollment Weight Adjustment 

Factor 

1N 1,891,422 1,833,701 1.03148 

1U 2,947,320 2,307,906 1.27705 

2N 3,528,691 2,829,195 1.24724 

2U 2,685,535 2,248,007 1.19463 

3N 5,554,795 5,456,187 1.01807 

3U 3,774,354 3,600,563 1.04827 

4N 2,447,658 2,270,783 1.07789 

4U 3,515,801 3,795,864 0.92622 

Total 26,345,580 24,342,210

4.4 Weight Trimming 

Extreme variation in sampling weights can cause inflated sampling variances and offset the 

precision gained from a well-designed sampling plan. This variation can occur, for example, if the 

number of respondents in a particular school is very low, causing a large non-response adjustment 

factor to be computed. One strategy to compensate for this is to trim extreme weights and distribute 

the trimmed weight among the untrimmed weights. The method we used is based on a similar 

procedure done for the National Assessment of Educational Progress (NAEP).21 The trimming was 

an iterative procedure. An optimal weight, Wo, was calculated in each iteration from the sum of the 

squared weights in the sample. Then, each weight, Wi, was marked and trimmed if it exceeded that 

optimal weight. The trimmed weight was summed within grade and spread out proportionally over 

the unmarked cases in the grade. The process was allowed to iterate until trimming produced a 

change in the design effect due to weighting of less than one percent. Weight trimming was done 

within strata. 

Wok is determined by the following: 

Equation 8: W ok = ⎛

⎜

⎜

⎝

c

n

∑

k=1

w

2

k

n

⎞

⎟

⎟

⎠

1

2

The constant c was set so that a maximum of three percent of the weight would be trimmed on the 

first iteration of the trimming process in each stratum. 

Let Wik and Wok be the weight for the ith case and the optimum weight for the kth iteration, 

respectively, and define Tik as 1 if Wik is greater than or equal to Wok, and zero otherwise. 

22 
Then the trimmed weight for the k + 1 iteration is defined as follows: 

Equation 9: Wi,k+1=

⎪

⎪

⎪

⎩

⎪

⎪

⎪

⎨

⎧ W ok if Wik ≥Wok

⎢

⎢

⎢

⎢

⎢

⎣

⎡ n

∑

i=1

⎜

⎜

⎝

⎛

1-tik ⎜

⎝

⎛Wok

Wik

⎟

⎠

⎞

⎟

⎠

⎞

⎟Wik

n

∑

i=1

Wik (1-tik )

⎥

⎥

⎥

⎥

⎥

⎦

⎤

if Wik <W ok

⎫

⎪

⎪

⎪

⎭

⎪

⎪

⎪

⎬

Table 7 presents the results of the weight trimming. 

Table 7: 

Summary of Trimming Factors, 2006 NYTS 

Stratum Trim 

Factor 

Number 

Cases 

Trim 

Iteration 

Adjusting Factor Weight 

Trimmed 

Design 

Effect 

1N 1.7 2,033 Initial 1.00000 2159.45 1.24 

Final 1.00295 2380.18 1.19 

1U 5.9 2,798 Initial 1.00000 2332.38 1.82 

Final 1.00221 2200.84 1.55 

2N 2.1 3,614 Initial 1.00000 1688.49 1.27 

Final 1.00227 2499.55 1.17 

2U 2.7 2,938 Initial 1.00000 1564.27 1.32 

Final 1.00145 1905.52 1.19 

3N 3.8 5,801 Initial 1.00000 1511.10 1.59 

Final 1.00123 1626.44 1.38 

3U 3.4 3,472 Initial 1.00000 2111.44 1.54 

Final 1.00137 2140.74 1.39 

4N 3.6 2,294 Initial 1.00000 3049.97 1.88 

Final 1.00223 3277.82 1.72 

4U 3.8 4,088 Initial 1.00000 973.84 1.51 

Final 1.00288 1655.41 1.34 

Total 27,038 

4.5 Post-stratification 

National estimates of student enrollment distribution by race/ethnicity and grade within stratum 

were obtained from the most recent CCD18 data from NCES and the current school and school 

district QED17 data files. Weights were post-stratified to national student enrollment estimates 

within the cross-classification of grade and race/ethnicity for the following categories: white, black, 

Hispanic, Asian,†† and AI/AN. 

Given a national estimate of Ra and a weighted population estimate of Pa for race/grade combination 

a, the simple post-stratification factor would be the ratio of Ra to Pa for each race and grade. 

†† See Section 2.1, Measure of Size, for information pertaining to estimation of Asian student enrollment data.

23 
However, this process sets weights for respondents who failed to answer either the grade or race 

questions, or gave a response of “Ungraded or other grade” to the grade question, to zero. Missing 

responses were imputed using a hot-deck method, with adjustable imputation classes prior to the 

post-stratification step. 

Table 8 gives for each post-stratification cell, the percentage of weight, the percentage of 

enrollment, and the post-stratification adjustment.

Table 8: 

Post Stratification, 2006 NYTS 

Grade Race/Ethnicity 

Control Total

Weighted 

Estimate 

Total 

Number 

Cases 

Control 

Percent 

Weighted 

Estimate 

Percent 

Ratio 

Adjustment 

06th White 2,601,150 2,008,213 1,645 9.87% 7.62% 1.29526

07th White 2,519,291 1,856,737 1,653 9.56% 7.05% 1.35684

08th White 2,479,348 1,722,689 1,556 9.41% 6.54% 1.43923

09th White 2,655,744 2,130,736 1,701 10.08% 8.09% 1.24640

10th White 2,418,079 2,378,191 1,928 9.18% 9.03% 1.01677

11th White 2,267,445 2,149,084 1,702 8.61% 8.16% 1.05508

12th White 2,104,340 1,737,896 1,416 6.60% 7.99% 1.21085

06th Black 683,681 680,477 824 2.60% 2.58% 1.00471

07th Black 651,856 714,521 796 2.47% 2.71% 0.91230

08th Black 621,530 828,475 906 2.36% 3.14% 0.75021

09th Black 695,855 814,561 959 2.64% 3.09% 0.85427

10th Black 551,435 824,344 874 2.09% 3.13% 0.66894

11th Black 470,216 584,138 679 1.78% 2.22% 0.80497

12th Black 418,880 459,874 533 1.59% 1.75% 0.91086

06th Hispanic 656,354 944,895 1,247 2.49% 3.59% 0.69463

07th Hispanic 605,444 838,567 1,215 2.30% 3.18% 0.72200

08th Hispanic 587,488 839,167 1,294 2.23% 3.19% 0.70008

09th Hispanic 614,124 774,503 1,158 2.33% 2.94% 0.79293

10th Hispanic 504,855 742,098 880 1.92% 2.82% 0.68031

11th Hispanic 434,450 556,993 786 1.65% 2.11% 0.77999

12th Hispanic 381,774 477,075 679 1.81% 1.45% 0.80024

06th Asian 171,589 232,583 279 0.65% 0.88% 0.73776

07th Asian 165,675 219,306 296 0.63% 0.83% 0.75546

08th Asian 162,546 290,749 397 0.62% 1.10% 0.55906

24 
Grade Race/Ethnicity 

Control Total

Weighted 

Estimate 

Total 

Number 

Cases 

Weighted 

Estimate 

Percent 

Control 

Percent 

Ratio 

Adjustment 

09th Asian 186,672 262,813 308 0.71% 1.00% 0.71028

10th Asian 167,435 273,467 318 0.64% 1.04% 0.61227

11th Asian 152,226 173,049 211 0.58% 0.66% 0.87967

12th Asian 138,157 156,716 175 0.52% 0.59% 0.88158

06th AI/AN 44,637 173,509 168 0.17% 0.66% 0.25726

07th AI/AN 43,390 124,293 117 0.16% 0.47% 0.34909

08th AI/AN 41,775 79,482 81 0.16% 0.30% 0.52559

09th AI/AN 43,114 78,068 72 0.16% 0.30% 0.55226

10th AI/AN 38,077 120,362 95 0.14% 0.46% 0.31635

11th AI/AN 34,947 49,743 46 0.13% 0.19% 0.70254

12th AI/AN 32,001 48,206 44 0.12% 0.18% 0.66384

Total 26,345,580 26,345,580 27,038 100% 100% 

25 
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26 
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27 
Appendix A 

Common Core of Data (CCD) 

Race/Ethnicity Definitions 

28 
Appendix A: Common Core of Data Race/Ethnicity Definitions 

American Indian/Alaska Native: A person having origins in any of the original peoples of 

North and South America (including Central America) and who maintains cultural identification 

through tribal affiliation or community recognition. 

Asian/Pacific Islander: A person having origins in any of the original peoples of the Far East, 

Southeast Asia, the Indian subcontinent, or the Pacific Islands. This area includes, for example, 

Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, Thailand, Vietnam, Guam, the 

Philippine Islands, Samoa, and other Pacific Islands.

Black: A person having origins in any of the black racial groups of Africa; African American. 

Hispanic: A person of Mexican, Puerto Rican, Cuban, Central or South American, or other 

Spanish culture or origin, regardless of race. 

White: A person having origins in any of the original peoples of Europe, North Africa, or the 

Middle East.

29 
Appendix B 

2006 NYTS Survey Instrument 

30 
31 

Appendix B: 2006 NYTS Survey Instrument 

OMB No.: 0920-0621 

Expiration Date: 

12/31/2008

National Youth 

Tobacco Survey (NYTS) 

2006 Questionnaire

This survey is about tobacco. We would like to know about you and 

things you do that may affect your health. Your answers will be used for 

programs for young people like yourself. 

DO NOT write your name on this survey. The answers you give will 

be kept private. 

NO one will know what you write. Answer the questions based on 

what you really do and know. 

Completing the survey is voluntary. Whether or not you answer the 

questions will not affect your grade in this class. Try to answer all the 

questions. If you do not want to answer a question, just leave it blank. 

There are no wrong answers. 

The questions that ask about your background will only be used to 

describe the types of students completing this survey. The information will 

not be used to find out your name. No names will ever be reported. 

Please read every question. Try to answer all the questions. Fill in 

the circles in the booklet completely. When you are finished, follow the 

instructions of the person giving you the survey. 

Thank You Very Much For Your Help. 
32 

TODAY’S DATE 

Month Day 

0 March 0 0 0 1 

0 April 0 1 0 2 

0 May 0 2 0 3 

0 June 0 3 0 4 

0 5 

0 6 

0 7 

0 8 

0 9 

The first questions ask for some background information 

about you. 

1. How old are you? 

a. 9 years old 

b. 10 years old 

c. 11 years old 

d. 12 years old 

e. 13 years old 

f. 14 years old 

g. 15 years old 

h. 16 years old 

i. 17 years old 

j. 18 years old 

k. 19 years old 

l. 20 years old 

m. 21 years old 

2. What is your sex? 

a. Female 

b. Male 

3. What grade are you in? 

a. 6th

b. 7th

c. 8th

d. 9th

e. 10th

f. 11th

g. 12th

h. Ungraded or other grade 

4. Are you Hispanic or Latino? 

a. Yes 

 b. No 

5. What race or races do you consider yourself to be? 

(Please select one or more than one category) Would 

you say: 

a. American Indian or Alaska Native 

b. Asian 

c. Black or African American 

d. Native Hawaiian or Other Pacific Islander 

e. White 

6. During an average week, how much money do you get 

from a job and other sources (allowance, etc.)? 

a. None 

b. Less than $1 

c. $1 to $5 

d. $6 to $10 

e. $11 to $20 

f. $21 to $50 

g. $51 to $100 

h. $101 to $150 

i. $151 or more 

7. During the past 30 days, how many days did you miss 

school for any reason, with or without permission? 

a. 0 days 

b. 1 day 

c. 2 to 5 days 

d. 6 to 10 days 

e. 11 or more days 

The next questions ask about your use of tobacco. 

The first group of questions is about cigarette smoking. 

8. Have you ever tried cigarette smoking, even one or two 

puffs? 

a. Yes 

b. No 

9. How old were you when you smoked a whole cigarette for 

the first time? 

a. I have never smoked a whole cigarette 

b. 8 years old or younger 

c. 9 

d. 10 

e. 11 

f. 12 

g. 13 

h. 14 

i. 15 

j. 16 

k. 17 years old or older 

10. About how many cigarettes have you smoked in your 

entire life? 

a. None 

b. 1 or more puffs but never a whole cigarette 

c. 1 cigarette 

d. 2 to 5 cigarettes 

e. 6 to 15 cigarettes (about 1⁄2 a pack total) 

f. 16 to 25 cigarettes (about 1 pack total) 

g. 26 to 99 cigarettes (more than 1 pack but less than 5 

packs) 

h. 100 or more cigarettes (5 or more packs) 
33 

11. Now think back 12 months ago. At this time last year, 

about how much were you smoking? 

a. I have never smoked cigarettes 

b. I have smoked in my life, but I wasn’t smoking at this 

time last year 

c. I smoked on some days at this time last year 

d. I smoked on most days at this time last year 

e. I smoked every day at this time last year 

12. Have you ever smoked cigarettes daily, that is, at least 

one cigarette every day for 30 days? 

a. Yes 

b. No 

13. During the past 30 days, on how many days did you 

smoke cigarettes? 

a. 0 days 

b. 1 or 2 days 

c. 3 to 5 days 

d. 6 to 9 days 

e. 10 to 19 days 

f. 20 to 29 days 

g. All 30 days 

14. During the past 30 days, on the days you smoked, how 

many cigarettes did you smoke per day? 

a. I did not smoke cigarettes during the past 30 days 

b. Less than 1 cigarette per day 

c. 1 cigarette per day 

d. 2 to 5 cigarettes per day 

e. 6 to 10 cigarettes per day 

f. 11 to 20 cigarettes per day 

g. More than 20 cigarettes per day 

15. During the past 30 days, what brand of cigarettes did you 

usually smoke? (Choose only one answer)

a. I did not smoke cigarettes during the past 30 days 

b. I do not have a usual brand 

c. American Spirit 

d. Camel 

e. GPC, Basic, or Doral 

f. Kool 

g. Lucky Strike 

h. Marlboro 

i. Newport 

j. Parliament 

k. Virginia Slims 

l. Some other brand 

16. What type of cigarette did you usually smoke in the past 

30 days? 

a. I have never smoked 

b. I have smoked but not in the past 30 days 

c. I do not have a usual type 

d. Regular/Full flavor 

e. Light 

f. Ultra Light 

17. Are the cigarettes you usually smoke menthol cigarettes? 

a. I do not smoke cigarettes 

b. Yes 

c. No 

18. When was the last time you smoked a cigarette, even one 

or two puffs? 

a. I have never smoked even one or two puffs 

b. Earlier today 

c. Not today but sometime during the past 7 days 

d. Not during the past 7 days but sometime during the 

past 30 days 

e. Not during the past 30 days but sometime during the 

past 6 months 

f. Not during the past 6 months but sometime during the 

past year 

g. 1 to 4 years ago 

h. 5 or more years ago 

19. Where do you smoke cigarettes? 

(Choose one or more answers) 

a. I do not smoke now 

b. At home 

c. At school 

d. At work 

e. In the car 

f. At friends’ houses 

g. At sports events, parties, dances, raves, or other 

social events 

h. In public buildings (restaurants, fast food places, 

shopping malls, or other hangouts) 

i. Outdoors (sidewalks, parking lots, parks, or other 

places) 

20. Have you ever tried any of these tobacco products? 

(Choose one or more answers)

a. Eclipse cigarettes 

b. Omni 

c. Advance Lights 

d. Accord 

e. Ariva 

f. I have not tried any of these products 

21. During the past 30 days, how did you usually get your own 

cigarettes? (Choose only one answer)

a. I did not smoke cigarettes during the past 30 days 

b. I bought them in a store such as a convenience store, 

supermarket, or gas station 

c. I bought them from a vending machine 

d. I gave someone else money to buy them for me 

e. I borrowed them from someone else 

f. I stole them 

g. A person 18 years old or older gave them to me 

h. I got them some other way 

22. During the past 30 days, where did you buy the last pack 

of cigarettes you bought? (Choose only one answer)

a. I did not buy a pack of cigarettes during the past 30 

days 

b. A gas station 

c. A convenience store 

d. A grocery store 

e. A drugstore 

f. A vending machine 

g. I bought them over the Internet 

h. Other 
34 

23. When you bought or tried to buy cigarettes in a store 

during the past 30 days, were you ever asked to show 

proof of age? 

a. I did not try to buy cigarettes in a store during the past 

30 days 

b. Yes, I was asked to show proof of age 

c. No, I was not asked to show proof of age 

24. During the past 30 days, did anyone ever refuse to sell 

you cigarettes because of your age? 

a. I did not try to buy cigarettes in a store during the past 

30 days 

b. Yes, someone refused to sell me cigarettes because 

of my age 

c. No, no one refused to sell me cigarettes because of 

my age 

25. During the past 30 days, on how many days did you 

smoke cigarettes on school property? 

a. 0 days 

b. 1 or 2 days 

c. 3 to 5 days 

d. 6 to 9 days 

e. 10 to 19 days 

f. 20 to 29 days 

g. All 30 days 

26. Do you want to stop smoking cigarettes? 

a. I do not smoke now 

b. Yes 

c. No 

27. Are you seriously thinking about quitting smoking? 

a. I have never smoked 

b. I do not smoke now 

c. Yes, within the next 30 days 

d. Yes, within the next 6 months 

e. Yes, but not within the next 6 months 

f. No, I am not thinking of quitting smoking 

g. Not sure 

28. How many times during the past 12 months have you 

stopped smoking for one day or longer because you were 

trying to quit smoking? 

a. I have not smoked in the past 12 months 

b. I have not tried to quit 

c. 1 time 

d. 2 times 

e. 3 to 5 times 

f. 6 to 9 times 

g. 10 or more times 

29. When you last tried to quit, how long did you stay off 

cigarettes? 

a. I have never smoked cigarettes 

b. I have never tried to quit 

c. Less than a day 

d. 1 to 2 days 

e. 3 to 7 days 

f. More than 7 days but less than 30 days 

g. 30 days or more but less than 6 months 

h. 6 months or more but less than a year 

i. 1 year or more 

30. During the past 12 months, did a medical doctor, dentist, 

or nurse ask you whether you smoke cigarettes? 

a. Yes 

b. No 

c. I don’t know/I can’t remember 

 

31. During the past 12 months, did a medical doctor, dentist, 

or nurse tell you to stop smoking? 

a. I have never smoked 

b. Yes 

c. No 

d. I don’t know/I can’t remember 

32. In the past 12 months, did you do any of the following to 

help you stop smoking? (Choose one or more answers)

a. I have never smoked 

b. I have not smoked in the past 12 months 

c. I did not try to quit in the past 12 months 

d. Attended a program in my school 

e. Attended a program in the community 

f. Called a help line or quit line 

g. Used nicotine gum 

h. Used nicotine patch 

i. Used any medicine to help quit 

j. Visited an internet quit site 

k. Got help from family or friends 

l. I tried to quit but did something else 

m. I tried to quit but did not do any of these things 

33. In the past 12 months, did you have to go to a stop 

smoking class because you were caught smoking? 

a. I have never smoked 

b. I have not smoked in the past 12 months 

c. Yes, I had to go to a stop smoking class 

d. No, I did not have to go to a stop smoking class 

34. Do you think you would be able to quit smoking cigarettes 

now if you wanted to? 

a. I do not smoke now 

b. Yes 

c. No 

35. How long can you go without smoking before you feel like 

you need a cigarette? 

a. I have never smoked cigarettes 

b. I do not smoke now 

c. Less than 1 hour 

d. 1 to 3 hours 

e. More than 3 hours but less than a day 

f. A whole day 

g. Several days 

h. A week or more 

36. How true is this statement for you? After not smoking for a 

while, I feel restless and irritable. 

a. I have never smoked cigarettes 

b. I don’t smoke now 

c. Not at all true 

d. Not very true 

e. Fairly true 

f. Very true 
35 

37. How true is this statement for you? When I go without a 

smoke for a few hours, I experience craving. 

a. I have never smoked cigarettes 

b. I don’t smoke now 

c. Not at all true 

d. Not very true 

e. Fairly true 

f. Very true 

The next questions are about smokeless tobacco—

chewing tobacco, snuff, or dip. 

38. Have you ever used chewing tobacco, snuff, or dip, such 

as Redman, Levi Garrett, Beechnut, Skoal, Skoal Bandits, 

or Copenhagen? 

a. Yes 

b. No 

39. How old were you when you used chewing tobacco, snuff, 

or dip for the first time? 

a. I have never used chewing tobacco, snuff, or dip 

b. 8 years old or younger 

c. 9 

d. 10 

e. 11 

f. 12 

g. 13 

h. 14 

i. 15 

j. 16 

k. 17 years old or older 

40. During the past 30 days, on how many days did you use 

chewing tobacco, snuff, or dip? 

a. 0 days 

b. 1 or 2 days 

c. 3 to 5 days 

d. 6 to 9 days 

e. 10 to 19 days 

f. 20 to 29 days 

g. All 30 days 

41. During the past 30 days, on how many days did you use 

chewing tobacco, snuff, or dip on school property? 

a. 0 days 

b. 1 or 2 days 

c. 3 to 5 days 

d. 6 to 9 days 

e. 10 to 19 days 

f. 20 to 29 days 

g. All 30 days 

The next questions are about cigars and pipes. 

42. Have you ever tried smoking cigars, cigarillos, or little 

cigars, even one or two puffs? 

a. Yes 

b. No 

43. How old were you when you smoked a cigar, cigarillo, or 

little cigar for the first time? 

a. I have never smoked a cigar, cigarillo or little cigar 

b. 8 years old or younger 

c. 9 

d. 10 

e. 11 

f. 12 

g. 13 

h. 14 

i. 15 

j. 16 

k. 17 years old or older 

44. During the past 30 days, on how many days did you 

smoke cigars, cigarillos, or little cigars? 

a. 0 days 

b. 1 or 2 days 

c. 3 to 5 days 

d. 6 to 9 days 

e. 10 to 19 days 

f. 20 to 29 days 

g. All 30 days 

45. Have you ever tried smoking tobacco in a pipe, even one 

or two puffs? 

a. Yes 

b. No 

46. During the past 30 days, on how many days did you 

smoke tobacco in a pipe? 

a. 0 days 

b. 1 or 2 days 

c. 3 to 5 days 

d. 6 to 9 days 

e. 10 to 19 days 

f. 20 to 29 days 

g. All 30 days 

The next questions are about bidis and kreteks. Bidis (or 

“beedies”) are small brown cigarettes from India made of 

tobacco wrapped in a leaf tied with a thread. They can 

taste like vanilla, chocolate, cherry or other flavors. 

Kreteks (or “clove cigarettes”) are cigarettes containing 

tobacco and clove extract. 

47. Have you ever tried smoking any of the following: 

a. Bidis 

b. Kreteks 

c. I have tried both bidis and kreteks 

d. I have never smoked bidis or kreteks 

48. During the past 30 days, on how many days did you 

smoke bidis? 

a. 0 days 

b. 1 or 2 days 

c. 3 to 5 days 

d. 6 to 9 days 

e. 10 to 19 days 

f. 20 to 29 days 

g. All 30 days 
36 

49. During the past 30 days, on how many days did you 

smoke kreteks? 

a. 0 days 

b. 1 or 2 days 

c. 3 to 5 days 

d. 6 to 9 days 

e. 10 to 19 days 

f. 20 to 29 days 

g. All 30 days 

The next questions ask about other people smoking and 

using tobacco around you. 

50. During the past 7 days, on how many days were you in the 

same room with someone who was smoking cigarettes? 

a. 0 days 

b. 1 or 2 days 

c. 3 or 4 days 

d. 5 or 6 days 

e. 7 days 

51. During the past 7 days, on how many days did you ride in 

a car with someone who was smoking cigarettes? 

a. 0 days 

b. 1 or 2 days 

c. 3 or 4 days 

d. 5 or 6 days 

e. 7 days 

52. Do you think the smoke from other people’s cigarettes is 

harmful to you? 

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not 

53. Does anyone who lives with you now smoke cigarettes? 

a. Yes 

b. No 

54. Does anyone who lives with you now use chewing 

tobacco, snuff, or dip? 

a. Yes 

b. No 

55. How many of your four closest friends smoke cigarettes? 

a. None 

b. One 

c. Two 

d. Three 

e. Four 

f. Not sure 

56. How many of your four closest friends use chewing 

tobacco, snuff, or dip? 

a. None 

b. One 

c. Two 

d. Three 

e. Four 

f. Not sure 

57. Which statement best describes the rules about smoking 

inside your home? 

a. Smoking is not allowed anywhere inside my home 

b. Smoking is allowed in some places or at some times 

c. Smoking is allowed anywhere in my home 

d. There are no rules about smoking in my home 

The next questions ask about your thoughts about 

tobacco. 

58. Do you think you will smoke a cigarette at anytime during 

the next year? 

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not 

59. Do you think you will be smoking cigarettes 5 years from 

now? 

a. I definitely will 

b. I probably will 

c. I probably will not 

d. I definitely will not 

60. If one of your best friends offered you a cigarette, would 

you smoke it? 

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not 

61. Do you think that you will try a cigarette soon? 

a. I have already tried smoking cigarettes 

b. Yes 

c. No 

62. During the past 12 months, has either of your parents (or 

guardians) told you not to smoke cigarettes? 

a. Mother (female guardian) only 

b. Father (male guardian) only 

c. Both 

d. Neither 

63. In the past 12 months, how often have your parents or 

guardians discussed the dangers of tobacco use with you? 

a. Never 

b. Rarely 

c. Sometimes 

d. Often 

e. Very often 

64. Do you think it is safe to smoke for only a year or two, as 

long as you quit after that? 

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not 
37 

65. Do you think smoking cigarettes makes young people look 

cool or fit in? 

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not 

Some tobacco companies make items like sports gear, tshirts, lighters, hats, jackets, and sunglasses that people 

can buy or receive free. 

66. During the past 12 months, did you buy or receive 

anything that has a tobacco company name or picture on 

it?

a. Yes 

b. No 

67. Would you ever use or wear something that has a tobacco 

company name or picture on it such as a lighter, t-shirt, 

hat, or sunglasses? 

a. Definitely yes 

b. Probably yes 

c. Probably not 

d. Definitely not 

The next questions ask about events you may have 

attended or what you have seen or heard on the TV, radio, 

movies, billboards, signs, newspapers, magazines, stores, 

or the Internet. 

68. During the past 12 months, have you participated in any 

community activities to discourage people your age from 

using cigarettes, chewing tobacco, snuff, dip, or cigars? 

a. Yes 

b. No 

c. I did not know about any activities 

69. During the past 30 days, how many times did you see antismoking messages on TV? 

a. I did not watch TV in the past 30 days 

b. None 

c. 1 to 3 times in the past 30 days 

d. 1 to 3 times per week 

e. Daily or almost daily 

f. More than once a day 

70. During the past 30 days, how many times did you hear 

anti-smoking messages on the radio? 

a. I did not listen to the radio in the past 30 days 

b. None 

c. 1 to 3 times in the past 30 days 

d. 1 to 3 times per week 

e. Daily or almost daily 

f. More than once a day 

71. During the past 30 days, how many times did you see antismoking messages on the Internet? 

a. I did not use the Internet in the past 30 days 

b. None 

c. 1 to 3 times in the past 30 days 

d. 1 to 3 times per week 

e. Daily or almost daily 

f. More than once a day 

72. During the past 30 days, how many times have you seen 

anti-smoking messages on billboards or outdoor signs? 

a. None in the past 30 days 

b. 1 to 3 times in the past 30 days 

c. 1 to 3 times per week 

d. Daily or almost daily 

e. More than once a day 

73. During the past 30 days, how many times did you see antismoking messages in magazines or newspapers? 

a. I did not read magazines or newspapers 

b. None in the past 30 days 

c. 1 to 3 times in the past 30 days 

d. 1 to 3 times per week 

e. Daily or almost daily 

f. More than once a day 

74. When you watch TV or go to movies, how often do you 

see actors using tobacco? 

a. I don’t watch TV or go to movies 

b. Most of the time 

c. Some of the time 

d. Hardly ever 

e. Never 

75. When you are using the Internet, how often do you see 

ads for tobacco products? 

a. I do not use the Internet 

b. Most of the time 

c. Some of the time 

d. Hardly ever 

e. Never 

76. When you read newspapers or magazines, how often do 

you see ads or promotions for cigarettes and other 

tobacco products? 

a. I do not read newspapers or magazines 

b. All of the time 

c. Most of the time 

d. Some of the time 

e. Hardly ever 

f. Never 

77. When you go to a convenience store, supermarket, or gas 

station, how often do you see ads for cigarettes and other 

tobacco products or items that have tobacco company 

names or pictures on them? 

a. I never go to a convenience store, supermarket, or 

gas station 

b. All of the time 

c. Most of the time 

d. Some of the time 

e. Hardly ever 

f. Never 
38 

The last questions ask if you were taught about tobacco in 

your classes. 

78. During this school year, did you practice ways to say “No” 

to tobacco in any of your classes (for example, by role 

playing)?

a. Yes 

b. No 

c. Not sure 

79. During this school year, were you taught in any of your 

classes the reasons why people your age smoke? 

a. Yes 

b. No 

c. Not sure 

80. During this school year, were you taught in any of your 

classes that most people your age do not smoke 

cigarettes? 

a. Yes 

b. No 

c. Not sure 

81. During this school year, were you taught in any of your 

classes about the dangers of tobacco use? 

a. Yes 

b. No 

c. Not sure 
Thank you for participating in this survey. 

DO NOT WRITE BELOW THIS LINE 

OFFICE USE ONLY 

1. Who administered this survey? 

a. Teacher or other school staff person 

b. Data collector 

2. When was this survey administered? 

a. As part of the original survey administration 

b. As part of a make-up session 

School ID 

0 0 0 0 0 0 0 0

1 1 1 1 1 1 1 1

2 2 2 2 2 2 2 2

3 3 3 3 3 3 3 3

4 4 4 4 4 4 4 4

5 5 5 5 5 5 5 5

6 6 6 6 6 6 6 6

7 7 7 7 7 7 7 7

8 8 8 8 8 8 8 8

9 9 9 9 9 9 9 9

39 
Appendix C 

 

Data Collector Training Agenda 

40 
Appendix C: Data Collector Training Agenda 

National Youth Tobacco Survey 2006 - Data Collector Training Agenda 

Day 1 - Thursday March 2, 2006

4:00 - 5:00 Module 1 Orientation and Introductions 

5:00 - 5:15 Module 2 Purpose and Overview of Training 

5:15 - 5:30 Module 3 National Youth Tobacco Survey 

5:30 - 5:45 Module 4 Break 

5:45 - 6:15 Module 5 Steps Leading to Data Collection 

6:15 - 6:45 Module 6 Data Collector Roles and Responsibilities 

6:45 - 7:45 Module 7 Dinner 

7:45 - 8:15 Module 8 Time and Expense Reporting 

8:15 - 8:30 Module 9 Q & A/General Discussion

Day 2 - Friday March 3, 2006

8:45 - 9:00 Module 10 Coffee and Juice 

9:00 - 9:30 Module 11 Overview of Data Collection Process 

9:30 - 9:45 Module 12 Receipt of Assignments and Materials Preparation 

9:45 - 10:15 Module 13 Advance Calls to Schools 

10:15 - 10:45 Module 14 Entry Meeting with Principal/Contact Person 

10:45 - 11:00 Module 15 Break 

11:00 - 11:30 Module 16 Teacher Meeting Before Survey 

11:30 - 12:30 Module 17 Survey Administration 

12:30 - 2:00 Module 18 Working Lunch & Distribution and Review of Materials Needed to 

Call Week 1 Schools 

2:00 - 2:30 Module 19 Post-survey Teacher Meeting and Make-up Session Scheduling 

2:30 - 3:00 Module 20 Principal/Contact Person Exit Meeting 

3:00 - 3:15 Module 21 Break 

3:15 - 3:45 Module 22 What Happened Today and What About Tomorrow? 

3:45 - 4:00 Module 23 Q & A/Assignment of Saturday Role-play Scenarios

4:00 - 5:00 Module 24 Role Play Preparation and Group Meetings 

41 
Day 3 Saturday March 4, 2006

9:15 - 10:00 Module 25 Expense Report Problems and Procedures 

10:00 - 11:00 Module 26 Presentation and Discussion of Role Plays 

11:00 - 11:15 Module 27 Break 

11:15 - 12:30 Module 28 Presentation and Discussion of Role Plays 

12:30 - 1:30 Module 29 Lunch 

1:30 - 2:30 Module 30 Presentation and Discussion of Role Plays 

2:30 - 2:45 Module 31 Break 

2:45 - 3:00 Module 32 Distribution and Return of Project Materials 

3:00 - 3:30 Module 33 Areas for Priority Attention 

3:30 - 4:00 Module 34 Staying Sane and Keeping in Touch 

4:00 - 4:15 Module 35 Closure/Final Q & A 

4:15 - ? Module 36 Dinner

42 
Appendix D 

Primary Sampling Unit (PSU) 

Sampling Weights

43 
Appendix D: Primary Sampling Unit (PSU) Sampling Weights 

Stratum PSU Size Measure 

Expected Number 

of Draws 

Sampling 

Weight 

Sub-sampled 

For Small 

Schools 

1N 090010 240395.97 0.49121 2.0358 0

1N 330170 12718.07 0.02599 38.4806 0

1N 340010 74973.2 0.15319 6.5276 0

1N 360210 8238.88 0.01683 59.4011 0

1N 360730 13601.53 0.02779 35.9811 0

1N 420430 56572.85 0.1156 8.6508 0

1N 421030 32822.45 0.06707 14.9105 0

1U 090030 251395.04 0.26485 3.7758 1

1U 250250 268249.1 0.2826 3.5386 1

1U 340230 341379.77 0.35964 2.7805 0

1U 340390 185037.99 0.19494 5.1298 0

1U 360470 892209.8 0.93994 1.0639 0

1U 360590 377031.8 0.3972 2.5176 0

1U 360610 592807.94 0.62452 1.6012 0

1U 360810 892715.13 0.94048 1.0633 0

1U 361030 343203.66 0.36157 2.7657 0

1U 421010 561827.3 0.59189 1.6895 0

2N 170070 78812.02 0.17506 5.7124 0

2N 180430 13009.05 0.0289 34.607 0

2N 190930 20892.16 0.04641 21.549 0

2N 201730 120915.08 0.26858 3.7233 0

2N 260730 16425.32 0.03648 27.4092 0

2N 261390 52659.61 0.11697 8.5493 0

2N 271090 28479.82 0.06326 15.8078 0

2N 291330 11187.94 0.02485 40.2401 0

2N 310190 7666.32 0.01703 58.7249 0

2N 390390 8843.4 0.01964 50.9085 0

2N 391510 52171.46 0.11588 8.6293 0

2N 550090 50769.57 0.11277 8.8676 1

2U 170310 532860.74 0.68272 1.4647 0

2U 170312 513697.37 0.65816 1.5194 0

2U 170430 302115.01 0.38708 2.5835 0

2U 170970 216145.23 0.27693 3.611 1

2U 261630 496364.67 0.63596 1.5724 0

2U 291890 241688.92 0.30966 3.2294 0

2U 390410 233559.85 0.29924 3.3418 1

2U 390610 181071.28 0.23199 4.3105 0

2U 550890 305438.4 0.39134 2.5553 0

44 
Stratum PSU Size Measure 

Expected Number 

of Draws 

Sampling 

Weight 

Sub-sampled 

For Small 

Schools 

3N 010170 12436.86 0.0166 60.2549 0

3N 010730 173669.98 0.23175 4.315 1

3N 050010 14700.88 0.01962 50.9753 0

3N 100010 155528.27 0.20754 4.8183 1

3N 120730 47512.06 0.0634 15.7724 0

3N 120990 295032.48 0.3937 2.54 0

3N 131330 48142.6 0.06424 15.5659 0

3N 220010 14141.15 0.01887 52.993 1

3N 280430 11962.5 0.01596 62.6442 0

3N 371330 25529.42 0.03407 29.3536 1

3N 400530 14340.75 0.01914 52.2554 0

3N 450730 20112.26 0.02684 37.2599 0

3N 470690 31113.45 0.04152 24.0854 1

3N 480390 92842.63 0.12389 8.0715 0

3N 482150 567341.31 0.75708 1.3209 0

3N 482430 644541.78 0.8601 1.1627 0

3N 482950 14853.83 0.01982 50.4504 0

3N 483110 57988.57 0.07738 12.9229 0

3N 540110 13568.39 0.01811 55.2299 0

3U 110010 162533.5 0.15251 6.5571 0

3U 120110 552528.58 0.51844 1.9289 0

3U 120860 631677 0.59271 1.6872 0

3U 120970 392554.39 0.36834 2.7149 0

3U 132550 108145.05 0.10147 9.8548 1

3U 245100 200432.76 0.18807 5.3173 0

3U 370590 23956.65 0.02248 44.4867 0

3U 481130 1044341.99 0.97991 1.0205 0

3U 482011 821314.94 0.77064 1.2976 0

3U 482310 15827.48 0.01485 67.3356 0

3U 484730 250697.92 0.23523 4.2511 1

3U 484930 859344.57 0.80633 1.2402 0

3U 510590 411934.25 0.38652 2.5872 0

4N 020680 97053.33 0.09608 10.4077 0

4N 060530 246153.94 0.24369 4.1036 0

4N 060950 201864.74 0.19985 5.0039 0

4N 061070 253113.81 0.25058 3.9907 0

4N 061110 374647.81 0.3709 2.6961 0

4N 150030 533426.1 0.52809 1.8936 0

4N 350530 282197.06 0.27937 3.5794 0

4N 410330 42327.18 0.0419 23.8642 1

4N 490490 65636.54 0.06498 15.3894 0

45 
Stratum PSU Size Measure 

Expected Number 

of Draws 

Sampling 

Weight 

Sub-sampled 

For Small 

Schools 

4U 040210 75238.22 0.04832 20.6954 0

4U 060010 851463.37 0.54683 1.8287 0

4U 060370 1221015.31 0.78417 1.2752 0

4U 060371 1230910.92 0.79052 1.265 0

4U 060373 1246720.47 0.80068 1.2489 0

4U 060374 1261188.52 0.80997 1.2346 0

4U 060591 800797.55 0.51429 1.9444 1

4U 060650 847341.02 0.54419 1.8376 1

4U 060710 1049473.89 0.674 1.4837 1

4U 060850 1052430.17 0.6759 1.4795 0

4U 320230 506023.95 0.32498 3.0771 0

4U 530330 551275.1 0.35404 2.8245 0

46 
Appendix E 

 

School Sampling Weights 

47 
Appendix E: School Sampling Weights

Stratum PSU School ID 

School Size 

Class 

School Size 

Measure 

Expected 

Number of 

Draws 

Sampling 

Weight 

1N 090010 00232144 Large 1270.2 0.01704 58.685

1N 090010 00234549 Large 1970.4 0.02643 37.831

1N 090010 00242629 Large 6410.2 0.08599 11.629

1N 330170 00851594 Large 160.97 0.03897 25.66

1N 330170 00854143 Large 2128.09 0.51522 1.941

1N 330170 00858931 Large 1417.72 0.34323 2.913

1N 340010 00870868 Large 13626.73 0.59487 1.681

1N 340010 00903341 Large 2165.18 0.09452 10.58

1N 340010 01921483 Large 5573.91 0.24333 4.11

1N 360210 00936548 Large 258.39 0.09545 10.476

1N 360210 00952184 Large 567.31 0.20957 4.772

1N 360210 04137439 Large 585.74 0.21638 4.622

1N 360730 00947323 Large 1105.67 0.25927 3.857

1N 360730 00965182 Large 598.44 0.14033 7.126

1N 360730 02923719 Large 1070.31 0.25098 3.984

1N 420430 01214485 Large 1489.46 0.09112 10.975

1N 420430 01220466 Large 1009.34 0.06175 16.195

1N 420430 01895699 Large 1980.94 0.12118 8.252

1N 421030 01230441 Large 931.12 0.08903 11.232

1N 421030 01241726 Large 845.14 0.08081 12.374

1N 421030 01248776 Large 2280.43 0.21806 4.586

1U 090030 00236885 Large 5640.22 0.07183 13.921

1U 090030 00239106 Small 325.15 0.02052 48.725

1U 090030 00244502 Large 1170.55 0.01491 67.077

1U 090030 01893352 Large 4975.98 0.06337 15.779

1U 250250 00609306 Large 6611.12 0.08259 12.108

1U 250250 00609452 Small 892.82 0.03177 31.473

1U 250250 00609496 Large 3940.98 0.04923 20.312

1U 250250 90177412 Large 3422.42 0.04275 23.39

1U 340230 00877513 Large 10687.83 0.09696 10.314

1U 340230 00887893 Large 11721.12 0.10633 9.405

1U 340230 00900861 Large 3414.89 0.03098 32.28

1U 340390 00863431 Large 2651.74 0.04515 22.147

1U 340390 00883866 Large 2106.51 0.03587 27.879

1U 340390 00902971 Large 5747.25 0.09786 10.218

1U 360470 00973874 Large 15510.68 0.05496 18.195

1U 360470 02123122 Large 4460.07 0.0158 63.277

1U 360470 03127997 Large 323.5 0.00115 872.405

1U 360590 00939039 Large 342.78 0.00295 339.549

1U 360590 00959157 Large 3273.56 0.02813 35.554

48 
Stratum PSU School ID 

School Size 

Class 

School Size 

Measure 

Expected 

Number of 

Draws 

Sampling 

Weight 

1U 360590 00968638 Large 2222.27 0.01909 52.374

1U 360610 00973965 Large 28420.12 0.15489 6.456

1U 360610 00974222 Large 12594.1 0.06864 14.569

1U 360610 00978191 Large 6898.86 0.0376 26.597

1U 360810 00926223 Large 6366.38 0.0233 42.91

1U 360810 02184550 Large 7682.02 0.02812 35.561

1U 360810 05492970 Large 2144.3 0.00785 127.399

1U 361030 00948699 Large 6274.74 0.05683 17.598

1U 361030 00967237 Large 3099.79 0.02807 35.622

1U 361030 00996723 Large 3841.13 0.03479 28.747

1U 421010 01185645 Large 3500.65 0.01956 51.129

1U 421010 01234876 Large 9006.44 0.05032 19.873

1U 421010 01235701 Large 2897.04 0.01619 61.782

2N 170070 00350805 Large 1354.23 0.05519 18.119

2N 170070 00407274 Large 1724.66 0.07029 14.227

2N 170070 00407296 Large 6131.77 0.24989 4.002

2N 180430 00429232 Large 656.63 0.17659 5.663

2N 180430 00444192 Large 1813.85 0.48781 2.05

2N 180430 00444341 Large 1322.06 0.35555 2.813

2N 190930 00458627 Large 1261.08 0.18675 5.355

2N 190930 00482354 Large 4287.31 0.63491 1.575

2N 190930 00482365 Large 2438.64 0.36114 2.769

2N 201730 00497757 Large 282.23 0.00717 139.484

2N 201730 00511944 Large 4595.02 0.11672 8.567

2N 201730 00512686 Large 7602.86 0.19313 5.178

2N 260730 00678052 Large 2341.46 0.44611 2.242

2N 260730 00678201 Large 811.91 0.15469 6.465

2N 260730 00687996 Large 654.69 0.12474 8.017

2N 261390 00669831 Large 3037.64 0.18121 5.519

2N 261390 00671738 Large 2218.49 0.13234 7.556

2N 261390 05950728 Large 4769.25 0.28451 3.515

2N 271090 00725027 Large 2325.55 0.25353 3.944

2N 271090 00725049 Large 5451.15 0.59429 1.683

2N 271090 00725071 Large 4035.39 0.43994 2.273

2N 291330 00782813 Large 1407.65 0.39973 2.502

2N 291330 00782824 Large 1286.25 0.36526 2.738

2N 291330 00782868 Large 1313.55 0.37301 2.681

2N 310190 00835415 Large 945.53 0.40084 2.495

2N 310190 00835426 Large 2165.08 0.91784 1.09

2N 310190 90072337 Large 639.92 0.27128 3.686

2N 390390 01075392 Large 1999.49 0.74158 1.348

49 
Stratum PSU School ID 

School Size 

Class 

School Size 

Measure 

Expected Number 

of Draws 

Sampling 

Weight 

2N 390390 01099777 Large 587.42 0.21787 4.59

2N 390390 03253762 Large 390 0.14464 6.913

2N 391510 01115575 Large 2327.76 0.13788 7.253

2N 391510 01115746 Large 801.49 0.04747 21.064

2N 391510 01116273 Large 292.89 0.01735 57.643

2N 550090 01508613 Large 203.16 0.01244 80.397

2N 550090 01525399 Large 2661.04 0.16292 6.138

2N 550090 01525457 Large 5000.78 0.30616 3.266

2N 550090 02067948 Small 70.33 0.03978 25.14

2U 170310 00342146 Large 1692.64 0.01041 96.073

2U 170310 00405583 Large 1826.31 0.01123 89.041

2U 170310 00412852 Large 1565.09 0.00962 103.902

2U 170312 00367229 Large 3798.08 0.02435 41.074

2U 170312 00371563 Large 2011.12 0.01289 77.57

2U 170312 00412783 Large 10028.18 0.06428 15.557

2U 170430 00382859 Large 5815.51 0.06095 16.407

2U 170430 00397333 Large 10856.57 0.11379 8.788

2U 170430 00404681 Large 4780.04 0.0501 19.961

2U 170970 00396996 Large 2924.15 0.04198 23.819

2U 170970 00404207 Large 12802.38 0.18381 5.4405

2U 170970 00418708 Small 276.37 0.03844 26.0157

2U 261630 00661082 Large 6550.38 0.0423 23.6383

2U 261630 00670916 Large 1737.01 0.01122 89.1414

2U 261630 04125751 Large 1874.61 0.01211 82.5983

2U 291890 00768865 Large 1856.14 0.02538 39.3983

2U 291890 00768887 Large 3457.96 0.04729 21.1479

2U 291890 04126041 Large 4059.59 0.05551 18.0138

2U 390410 01073395 Small 408.77 0.0491 20.3671

2U 390410 01073759 Large 5004.11 0.06665 15.0033

2U 390410 01100988 Large 3970.65 0.05289 18.9083

2U 390410 04146567 Large 1194.06 0.0159 62.8763

2U 390610 01069367 Large 1395.75 0.0259 38.6149

2U 390610 01084636 Large 6051.57 0.11228 8.9063

2U 390610 01084716 Large 4361.39 0.08092 12.3577

2U 550890 01531846 Large 4660.61 0.05042 19.8348

2U 550890 01532158 Large 5446.64 0.05892 16.9723

2U 550890 01532533 Large 7254.96 0.07848 12.7419

3N 010170 00006997 Large 1532.68 0.38755 2.5803

3N 010170 00007006 Large 1530.81 0.38707 2.5835

3N 010170 00013927 Large 1012.99 0.25614 3.9041

3N 010730 00003216 Small 164.01 0.02538 39.4013

3N 010730 00005698 Large 4791.16 0.08596 11.6331

3N 010730 00011792 Large 2210.64 0.03966 25.2126

50 
Stratum PSU School ID 

School Size 

Class 

School Size 

Measure 

Expected Number 

of Draws 

Sampling 

Weight 

3N 010730 00013439 Large 1401.83 0.02515 39.7594

3N 050010 00053744 Large 727.23 0.16744 5.9724

3N 050010 00056745 Large 3632.79 0.8364 1.1956

3N 050010 00056778 Large 1245.43 0.28674 3.4874

3N 100010 00250957 Large 1940.86 0.0383 26.1091

3N 100010 00251098 Large 3018.86 0.05957 16.7858

3N 100010 00251112 Large 5274.66 0.10409 9.6071

3N 100010 00251688 Small 163.99 0.04677 21.3821

3N 120730 00283042 Large 2186.88 0.14207 7.039

3N 120730 00283086 Large 3710.14 0.24102 4.149

3N 120730 06116950 Large 2628.03 0.17072 5.8574

3N 120990 00287943 Large 6062.14 0.06334 15.7871

3N 120990 00288029 Large 5102.06 0.05331 18.7578

3N 120990 00288051 Large 12336.98 0.12891 7.7574

3N 131330 00305975 Large 5954.44 0.3759 2.6603

3N 131330 00320144 Large 2109.17 0.13315 7.5104

3N 131330 90072767 Large 1786.59 0.11278 8.8665

3N 220010 00543149 Large 1416.81 0.32438 3.0828

3N 220010 00549027 Large 819.89 0.18771 5.3273

3N 220010 02028727 Small 76.46 0.07367 13.5736

3N 220010 06116483 Large 267.82 0.06132 16.3084

3N 280430 00736094 Large 363.42 0.09815 10.1887

3N 280430 00740329 Large 2855.87 0.77128 1.2965

3N 280430 00749547 Large 1561.25 0.42165 2.3717

3N 371330 01010426 Small 201.08 0.37142 2.6924

3N 371330 01032439 Large 2431.07 0.29187 3.4262

3N 371330 01032676 Large 3208.79 0.38524 2.5958

3N 371330 02944091 Large 1351.52 0.16226 6.1629

3N 400530 01149651 Large 518.63 0.12537 7.9761

3N 400530 01150292 Large 125.58 0.03036 32.9405

3N 400530 02880059 Large 264.59 0.06396 15.634

3N 450730 01276431 Large 1348.09 0.20306 4.9247

3N 450730 01276453 Large 904.05 0.13617 7.3435

3N 450730 01276464 Large 200.37 0.03018 33.1337

3N 470690 01306504 Large 3999.89 0.39923 2.5048

3N 470690 01306548 Large 1532.87 0.153 6.536

3N 470690 01309811 Large 1817.97 0.18145 5.511

3N 470690 01310725 Small 147.67 0.13974 7.1563

3N 480390 01333119 Large 6216.35 0.20544 4.8675

3N 480390 01338922 Large 3598 0.11891 8.4097

3N 480390 01387448 Large 11483.85 0.37953 2.6348

3N 482150 02905631 Large 8051.26 0.04375 22.858

51 
Stratum PSU School ID 

School Size 

Class 

School Size 

Measure 

Expected Number 

of Draws 

Sampling 

Weight 

3N 482150 03238530 Large 16230.57 0.08819 11.3388

3N 482150 05962992 Large 9869.99 0.05363 18.646

3N 482430 01354707 Large 12136.21 0.05925 16.8771

3N 482430 01355096 Large 10185.51 0.04973 20.1094

3N 482430 05446027 Large 5636.98 0.02752 36.3359

3N 482950 01338401 Large 2548.22 0.54979 1.8189

3N 482950 01338412 Large 2461.83 0.53115 1.8827

3N 482950 01396361 Large 426.41 0.092 10.8695

3N 483110 01360572 Large 1612.75 0.08852 11.2965

3N 483110 01378105 Large 2479.18 0.13608 7.3486

3N 483110 01389219 Large 3956.84 0.21719 4.6043

3N 540110 01489224 Large 377.57 0.08508 11.7542

3N 540110 01491277 Large 682.27 0.15373 6.5048

3N 540110 01501389 Large 248.74 0.05605 17.8422

3U 110010 00255365 Large 4277.78 0.09399 10.6389

3U 110010 00255729 Large 1915.5 0.04209 23.7593

3U 110010 03244452 Large 5574.53 0.12249 8.1641

3U 120110 00269298 Large 5526.06 0.03086 32.4038

3U 120110 00270066 Large 8603.12 0.04804 20.814

3U 120110 00270215 Large 13874.11 0.07748 12.9064

3U 120860 00262601 Large 3216.13 0.01562 64.0203

3U 120860 00272518 Large 10512.22 0.05106 19.5865

3U 120860 00272711 Large 6458.28 0.03137 31.8812

3U 120970 02122683 Large 15785.5 0.12175 8.2137

3U 120970 02868065 Large 15792.11 0.1218 8.2103

3U 120970 02876532 Large 8299.48 0.06401 15.6224

3U 132550 00297587 Small 205.17 0.66978 1.493

3U 132550 00306527 Large 2365.84 0.06582 15.1939

3U 132550 00306571 Large 8861.62 0.24652 4.0564

3U 132550 03214643 Large 3428.75 0.09539 10.4838

3U 245100 00579277 Large 1320.8 0.02063 48.4747

3U 245100 00585473 Large 3759.03 0.05871 17.0324

3U 245100 00585473 Large 3759.03 0.05871 17.0324

3U 245100 00585509 Large 4338.91 0.06777 14.7561

3U 370590 01035054 Large 1020.89 0.13257 7.5434

3U 370590 01035236 Large 2039.93 0.26489 3.7751

3U 370590 01035688 Large 2495.42 0.32404 3.0861

3U 481130 01348522 Large 8330.02 0.02629 38.0377

3U 481130 01349297 Large 8728.97 0.02755 36.2992

3U 481130 01380679 Large 3487.84 0.01101 90.8455

52 
Stratum PSU School ID 

School Size 

Class 

School Size 

Measure 

Expected Number 

of Draws 

Sampling 

Weight 

3U 482011 01366541 Large 11038.25 0.04099 24.3939

3U 482011 04125514 Large 4118.03 0.01529 65.387

3U 482011 05939329 Large 12130.95 0.04505 22.1966

3U 482310 01390643 Large 1088.17 0.20947 4.774

3U 482310 01624811 Large 4253.56 0.81878 1.2213

3U 482310 05734398 Large 218.02 0.04197 23.8278

3U 484730 01326994 Small 80.72 0.10238 9.7672

3U 484730 02881186 Large 17305.1 0.20774 4.8138

3U 484730 05513062 Large 4077.95 0.04895 20.4277

3U 484730 90069636 Large 6520.15 0.07827 12.7763

3U 484930 01384389 Large 9489.85 0.03397 29.4355

3U 484930 01385429 Large 20061.76 0.07182 13.9239

3U 484930 01395517 Large 6296.42 0.02254 44.3646

3U 510590 01441554 Large 9494.37 0.07691 13.0027

3U 510590 01441612 Large 10651.59 0.08628 11.59

3U 510590 01918856 Large 6435.78 0.05213 19.1821

4N 020680 00024939 Large 4356.6 0.16725 5.979

4N 020680 00025003 Large 3018.18 0.11587 8.6303

4N 020680 00025604 Large 8001.94 0.3072 3.2552

4N 060530 00125165 Large 5921.83 0.07931 12.6095

4N 060530 00186344 Large 6450.85 0.08639 11.5754

4N 060530 03267334 Large 9521.39 0.12751 7.8425

4N 060950 00118941 Large 4723.52 0.07649 13.0741

4N 060950 00191037 Large 6630.82 0.10737 9.3135

4N 060950 00192926 Large 13619.87 0.22054 4.5342

4N 061070 00193952 Large 16346.17 0.21947 4.5564

4N 061070 05447734 Large 8284.33 0.11123 8.9905

4N 061070 90069684 Large 11128.03 0.14941 6.693

4N 061110 00111742 Large 4846.35 0.0426 23.4724

4N 061110 00161432 Large 25884.49 0.22754 4.3947

4N 061110 00193227 Large 3191.72 0.02806 35.6408

4N 150030 00328041 Large 14993.66 0.09351 10.6945

4N 150030 00329952 Large 8262.5 0.05153 19.407

4N 150030 05486060 Large 10127.94 0.06316 15.8325

4N 350530 00910654 Large 7766.88 0.08555 11.6896

4N 350530 00910734 Large 7081.64 0.078 12.8208

4N 350530 00911341 Large 13919.14 0.15331 6.5228

4N 410330 01163155 Large 1981.51 0.15438 6.4776

4N 410330 01165899 Large 2908.37 0.22659 4.4133

4N 410330 01170173 Large 1187.77 0.09254 10.8063

4N 410330 01173651 Small 169.64 0.0444 22.5235

53 
54 

Stratum PSU School ID 

School Size 

Class 

School Size 

Measure 

Expected Number 

of Draws 

Sampling 

Weight 

4N 490490 01418398 Large 1887.48 0.09829 10.1742

4N 490490 01419369 Large 4018.98 0.20928 4.7782

4N 490490 02122027 Large 2053.74 0.10695 9.3506

4U 040210 00038522 Large 2044.09 0.08959 11.162

4U 040210 00038919 Large 2915.43 0.12778 7.826

4U 040210 00039901 Large 4031.49 0.1767 5.659

4U 060010 00121047 Large 6386.21 0.02465 40.566

4U 060010 00121433 Large 1636.07 0.00632 158.343

4U 060010 00164422 Large 4251.44 0.01641 60.935

4U 060370 00124809 Large 3483.51 0.00901 111.012

4U 060370 00166317 Large 12743.62 0.03295 30.345

4U 060370 00171236 Large 7640.79 0.01976 50.611

4U 060371 00115372 Large 7866.33 0.02017 49.582

4U 060371 00136337 Large 7972.9 0.02044 48.919

4U 060371 00141799 Large 13198.65 0.03384 29.551

4U 060373 00101406 Large 17439.87 0.04412 22.664

4U 060373 00178038 Large 14590.99 0.03692 27.089

4U 060373 00196181 Large 16320.75 0.04129 24.218

4U 060374 00162265 Large 1282.74 0.0032 312.984

4U 060374 04142143 Large 4860.03 0.01211 82.608

4U 060374 05483477 Large 13010.29 0.03241 30.858

4U 060591 00075316 Small 324.43 0.00434 230.514

4U 060591 00123088 Large 11438.09 0.04726 21.158

4U 060591 00123827 Large 8566.98 0.0354 28.248

4U 060591 00191773 Large 15529.9 0.06417 15.583

4U 060650 00110363 Small 860.58 0.02147 46.581

4U 060650 00112098 Large 6523.57 0.02424 41.248

4U 060650 02114639 Large 11172.35 0.04152 24.085

4U 060650 03260248 Large 7710.32 0.02865 34.899

4U 060710 00110749 Small 874.63 0.01263 79.185

4U 060710 00168267 Large 10087.68 0.03087 32.39

4U 060710 00173732 Large 16716.02 0.05116 19.546

4U 060710 03268043 Large 25508.19 0.07807 12.809

4U 060850 00103221 Large 14242.23 0.04411 22.673

4U 060850 00120826 Large 8826.47 0.02733 36.584

4U 060850 00153385 Large 7893.65 0.02445 40.907

4U 320230 00849993 Large 1971.33 0.01186 84.283

4U 320230 03237343 Large 10096.91 0.06077 16.455

4U 320230 03237412 Large 8059.78 0.04851 20.615

4U 530330 01470712 Large 4343.6 0.0261 38.313

4U 530330 01482772 Large 8269.69 0.04969 20.124

4U 530330 01483142 Large 3969.32 0.02385 41.926