## Part B: Supporting **Statement for Paperw**  **ork Reduction**  **Ac t Submission** 
**Effectiv eness of**  **Promising Strategies in Federal College A** **ccess Programs: Study**  **Student Messaging in**

**GE AR** **UP**

Prepared for: Marsha Silverberg **U.S. Department of Education** 555 New Jersey Ave, NW

Room 502I Wa shington, DC 20208 - 5500

Submitted by: **Ab t A**  **ssociates Inc.** 55 W heeler Street Cambridge, MA 02138**Revised OMB Supporting Statement Promising S**  **trategies in Federal College Access Programs**

**Abt Associates Inc. Table of**  **Contents ▌**  **pg. i**  

## Part B: Supporting Statement for **Paperw ork Reduction**  **Ac t**  **Submission Table of Contents**  **B. Collection of Information Employing Statistical Methods**  **................................ .................**  **B -**  **1** Introduction
................................ ................................ ................................ .............................. B
- 1 B.1 Respondent Universe and Sampling Methods
................................ ............................... B
- 6 B.1.1 Respondent Universe
................................ ................................ ....................... B
- 6 B.1.2 Sampling Methods
................................ ................................ ........................... B
- 7 B.1. 3 Expected Response Rates
................................ ................................ ................ B
- 7 B.2 Statistical Methods for Sample Selection and Degree of Accuracy Needed
................. B
- 7 B.2.1 Sample Selection
................................ ................................ ............................. B
- 7 B.2. 2 Estimation Procedures
................................ ....... **Error! Bookmark not defined.** B.2.3 Degree of Accuracy Needed
................................ ................................ ............ B
- 7 B.2.4 Unusual Problems Requiring Specialized Sampling Procedures
.................. B
- 14 B.2.5 Use of Periodic Data Collection Cycles to Reduce Burden
........................... B
- 14 B.3 Methods to Maximize Response Rates and Deal with Nonresponse
........................... B
- 14 B.4 Test of Procedures and Methods to be Undertaken
................................ ..................... B
- 15 B.5 Individuals Consulted on Statistical Aspects of the Design
................................ ........ B
- 15 References
................................ ................................ ................................ .............................. B
- 16**Revised OMB Supporting Statement Promising S**  **trategies in Federal College Access Programs**

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **1** 

## B. **Collection of Information Employ ing Statistical Methods**  **Introduction** The U.S. Department of Education (ED) will conduct a demonstration to test the effectiveness of a promising strategy to improve college
-related outcomes in the federal college access program Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP). The demonstration will use a randomized controlled trial (RCT) design to test the effectiveness of sending customized messaging to students, first during the summer after high school graduation, and then in the fall and spring of their expected first year of college. This study is being sponsored by ED’s Institute of Education Sciences (IES) , in collaboration with the Office of Postsecondary Education, and implemented by Abt Associates Inc. and its partners, Survey Research Management (SRM), Program and Policy Insight (PPI), Digital Design Group (DDG), and consultant Ben Castleman (together, the “ study team”). **Overview of the GEAR UP Program** Section 404H of the Higher Education Act of 1965, amended by the 2008 Higher Education Opportunities Act (HEOA) (20 USC 1070A
-27) authorizes the GEAR UP program. The program provides funding

– over $300 million in FY 2014

– to state agencies and local partnerships to support disadvantaged students in obtaining a high school diploma and to prepare them for success in postsecondary education. Grantees are expected to provide a comprehensive set of intervention services such as academic support, counseling, mentoring, and outreach to disadvantaged middle and high school students, as well as information about college financial aid options and the benefits of postsecondary education to students and their families. State grantees may, and partnership grantees must, focus on a cohort of students (typically all those in 7 th or 8 th grade) and provide services to them through high school, though funds can be used to serve other students as well. State GEAR UP grantees are required to, and local partnership can, also provide scholarships to help participating students pay for college attendance. Importantly, starting with the 2008 Higher Education Opportunity Act, GEAR UP grantees may now apply for a seventh year of funding to support students into their first year of college in order to improve college enrollment and persistence
. The first group of grantees with this funding, those awarded grants in FY 2011, will begin providing extended services to 2016
-2017 seniors transitioning to po stsecondary education the following year. **Overview of the Student Messaging in GEAR UP**  **Demonstration** This demonstration is designed to address a new need among GEAR UP grantees for strategies to serve students during the 7 th year. According to recent focus groups conducted by Abt with GEAR UP grantees, grantees find it difficult to reach every GEAR UP student on a one
- on - one basis while in high school, or to track and support students as they leave s chool and transition to college, particularly since students may be scattered across a variety of postsecondary institutions both in and out of state. Nationally, a s many as 40 percent of first
- generation, low
- income high school seniors intending to go to college fail to enroll the following fall, with information gaps, logistical complexities, and concerns about in fitting identified as primary explanations of this “summer melt” (Castleman and Paige, 2014). Of those who matriculate, many students drop out during their first**Revised OMB Supporting Statement Promising S**  **trategies in Federal College Access Programs**

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -** **2** year or fail to re
- enroll the second year (NSC, 2014b), and persistence is lower among students from low
- income and high minority high schools (NSC, 2014a). The demonstration will investigate a particular promising approach emerging from recent rigorous research of approaches to improve coll ege matriculation ( Castleman & Page 2013) and college persistence (Castleman & Page, 2014) through low
- cost student messaging, which may enhance the existing GEAR UP services. Customized messages will be sent to students identified as seniors, who intend to go to college, in high schools that are part of the GEAR UP program
. The messages, delivered via a digital format (phone texting) , will remind students about tasks related to enrolling in and persisting in college. All students will continue to be eligible for any regular GEAR UP services provided. Outcomes for this study will include college enrollment, FAFSA completion, and persistence, which will be drawn from administrative data. Student messaging will proceed in two phases and comprise two independent treatments. Phase 1 messages (Treatment 1) will be sent during the summer that follows students’ senior year in high school. Phase 2 messages (Treatment 2) will be sent during what would be students’ first year of college if they enroll in coll ege directly after high school. Students randomly assigned to Treatment 1 will receive a minimum of 10 messages designed to relay information that students may not be aware of or may not have easy access to. The messages will inform students about key enrollment
-related tasks they need to complete such as submitting a deposit, filling out the housing form, submitting their proof of health insurance form, registering for classes, etc. Students randomly assigned to Treatment 2 will receive a minimum of 8 me ssages designed to support students to complete their first semester and persist into the second semester. These messages will be focused on key tasks students must complete such as paying tuition and registering for the next semester as well as common challenges faced in the first semester such as academic unpreparedness and lack of knowledge about campus supports. All messages will be grounded in both social psychological and behavioral economic research suggesting that the messages be aligned to key time points such as housing deadlines, registration deadlines, tuition payment due dates, the add/drop period, and mid
-term exams and that the messages be action oriented such as submit your housing form and go to this webpage to register for classes. To the extent possible, messages will be customized for each student based on the information they provide on the baseline survey about college intentions. For example, deadlines for submitting particular forms and links to find more information will be specific to the college a student indicated as the planned college of enrollment on the baseline survey.**Revised OMB Supporting Statement Promising S**  **trategies in Federal College Access Programs**

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **3** Exhibit B
- 1 contains a preliminary outline of key prompts that are timed to key milestones or pressure points in enrolling and persisting in college. **Exhibi t**  **B -**  **1. Draft Outline of Student Messages Topic**  **Personalization** Enrollment Messages (Treatment 1) Log into college's web portal to access important paperwork and deadlines Link to specific website Register for orientation and plac ement tests Institution
- specific registration deadlines Complete housing forms Link to specific forms, include deadlines Sign up or waive health insurance (if relevant) Link to specific forms, include deadlines Submit deposit for fall enrollment Institution
- specifi c deposit deadlines Register for fall classes Institution
- specific registration deadlines Reminder of orientation and/or welcome activities dates Institution
- specific dates/activities Persistence Messages (Treatment 2) Provide links to campus resources for student support Links to specific resources Reminder about upcoming midterms Link to campus specific academic support center Mindset booster on overcoming challenges in college Link to campus counseling center Check financial aid eligibility for second year Link to requirements Register for spring classes Institution
- specific registration deadlines **Overview of the Evaluation** The study will use a rigorous random assignment design to test the effectiveness of sending customized messages to GEAR UP students. GEAR UP projects that were awarded awards in Federal Fiscal Year 2011 will be invited to volunteer for the demonstration (see Appendix A for invitation), because they are the first to have funds to support a 7 th year of services. To test the e ffectiveness of the customized messaging , the study will assign students within participating high schools selected by volunteer GEAR UP projects to either a control condition (eligible for all GEAR UP services), or a treatment condition (eligible for all GEAR UP services, plus receiving the customized messages). Students will be randomly assigned to conditions at two points in time (1) in the spring of their senior year of high school and (2) the end of summer after senior of high school. This two
-phase design maximizes our ability to investigate both the effects of messaging during the summer before college and the effects of messaging during freshman year of college.

 At the first phase of random assignment ( end of 2016
-2017 school year), students in high schools served by GEAR UP projects who declare their intention to enroll in college will be randomly assigned to receive messages in the summer after high school (Treatment 1) or not (Control 1). The comparison of Treatment 1 to Control 1 will test the im pacts of messaging on college enrollment

– i.e., to see if it reduces summer melt among GEAR UP students.  At the second phase of random assignment ( end of summer 201 7 ), students will be randomly assigned to receive messages (Treatment 2) or not (Control 2) in what would be their first year of college if they go to college right after high school. Random assignment in this second phase will occur within both the Treatment 1 and Control 1 conditions, so that within**Revised OMB Supporting Statement Promising S**  **trategies in Federal College Access Programs**

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -** **4** the Treatment 1 and Control 1 groups, half of the students will be assigned to Treatment 2 and half assigned to Control 2
. Exhibit B
-2 displays the phases of random assignment and their relationship to each other. Comparison of Treatment 2 to Control 2 will test the im pacts of different messaging on college persistence. **Exhibit B -** **2: Two -**  **Phase Randomization Process and Treatment Received** 

**Timing of Randomization**  **College Intending Seniors** Phase 1 End of 2016
- 17

school year T 1 C1 (summer messaging) (no summer messaging)
Phase 2 End of summer

2017 T2 C2 T2 C2

(summer and frosh messaging) (only summer

messaging) (only frosh

messaging) (no messaging) Baseline data will be collected from all students via a survey, and college
-related outcome data will be extracted from national datasets (National Student Clearinghouse Data (NSC) and the Federal Student Aid (FSA) database). The study will address the three research questions: 1. To what extent do the messages
—above and beyond the services GEAR UP may already provide

—improve student college
-related outcomes? 2. What types of college advising are typically received by GEAR UP students ? 3. Is there variation in the impact of the messages, and to what extent is the variation associated with student characteristics or features of the GEAR UP project or school? To answer these questions we will conduct both impact and descriptive analyses. The first report, which will address each research question with a focus on college enrollment
-related outcomes will be published in 2018. The final report, which will also include college persistence, will be available in 2020. Exhibit B
- 3 presents the rese arch questions along with the data sources for each question, the analytic approach and outcomes of interest
.**Revised OMB Supporting Statement Promising S**  **trategies in Federal College Access Programs**

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **5 Exhibit B**  **- 3.**  **Evaluation Questions, Data Sources, A naly** **tic A pproach, and Outcomes of Interest**  **Research Question Data Sources**  **Anal yt**  **ic Approach O**  **utcomes of Interest**  1) To what extent do the messages —above and beyond the services GEAR UP may already provide
— improve student college - related outcomes?  Student rosters  Student baseline survey data  National Student Clearinghouse Data  Federal Student Aid (FSA) database  Impact analysis of RCT (HLM)  Baseline survey sample: 16 ,000 students in 80 schools.  Analytic sample size: approximately 5,600 students in 80 high schools that intend to enroll in college in Phase 1; approximately 4,000 students across a large number of colleges in Phase 2, equally divided between treatment and control groups.  College enrollment (Phase I)  College persistence into sophomore year (Phase II)  FAFSA completion

2) Wh at types of college advising are typically received by GEAR UP students ?  Student baseline survey data  Descriptive analysis  Survey sample: 16 ,000 students in 80 schools.  Description of GEAR UP program components provided and received 3) Is there variation in the impact of the messages, and to what extent is the variation associated with student characteristics or features of the GEAR UP project or school?  Student baseline survey data  National Student Clearinghouse Data  Federal Student Aid (FSA) database  Descriptive (subgroup) analysis  Sample size: 5,600 students in 80 high schools that intend to enroll in college in Phase 1; approximately 4,000 students across a large number of colleges in Phase 2.  College enrollment (Phase I)  College persistence into sophomore year (Phase II)  FAFSA completion Altogether, we expect that 80 GEAR UP high schools will participate in the first phase of the research project, with an estimated total of 16 ,000 seniors
. 1 All seniors will be surveyed, with the consent process giving them (or the parents) an option to opt of completing the baseline survey or other data collection activities. The survey will gather information from students for participation in the student messaging intervention (see Appendix C for the consent letter).

1 An estimate of the number of seniors in each school is 200, given that the average secondary school enrollment in 2011
- 2012 was 788 students (NCES, 2013).**Revised OMB Supporting Statement Promising S**  **trategies in Federal College Access Programs**

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **6** Itis expected that 70 percent of seniors will express intent to attend college 2 and 50 percent of these seniors would provide assent and information for texting, resulting in 2,800 students in the Treatment 1 group, and 2,800 students in the Control 1 group . Assuming a matriculation rate for seniors of 50 percent3 the phase 2 sample will include 4,000 students entering college, 2,000 students in Treatment 2 group and 2,000 students in the Control 2 group
. 

### B.1 **Respondent Universe and Sampling Methods B.1.1**  **Respondent Universe** The respondent universe includes the FY 2011 GEAR UP grantees and associated schools that volunteer for the demonstration. Up to 12 GEAR UP grantees will be recruited involving approximately 80 schools. To participate in the demonstration, schools will need to agree to allow students to be randomly assigned to the intervention. The seniors in these schools in the 2016
-2017 academic year who intend to go to college and who who do not opt
- out in the consent process will be the target population. As noted above an estimate of the number of seniors in each school is 200 , given that the average secondary school enrollment in 2011
-2012 was 788 students (NCES, 2013)
. 4 Of these, we expect 70 percent of these to express intent to attend college, and 50 percent of these to assent to receive text messages, resulting in a total of 5,600 students in Phase I. 5 Assuming a matriculation rate of high school seniors of 50 percent6 the Phase II sam ple will include 4,000 students entering college. Exhibit B
-4 indicates the estimated population sizes for the evaluation.

2 Among 2010 seniors, 82 percent of graduating students planned to attend a postsecondary institution and the percent among parents with no college education was 71 percent (Aud et al. 2012). 3 This is the immediate college enrollment rate in the first fall after high school graduation for students graduating from low income schools according to the national student clearinghouse research center (National Student Clearinghou se 2014a). 4 The estimate of the number of seniors in GEAR
-UP schools is based on the average enrollment of 788 in regular secondary schools in 2011
- 2012 , assuming four grades per school (NCES 2013). 5 Among 2010 seniors, 82 percent of graduating students planned to attend a postsecondary institution and the percent among parents with no college education was 71 percent (Aud et al. 2012). 6 This is the immediate colle ge enrollment rate in the first fall after high school graduation for students graduating from low income schools according to the national student clearinghouse research center (National Student Clearinghou se 2014a).**Revised OMB Supporting Statement Promising S**  **trategies in Federal College Access Programs**

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **7 Exhibit B**  **- 4**  **. Population Size Estimates** Estimated number of GEAR UP high schools 80 schools Estimated number of 12 th graders in GEAR UP cohort per school 200 students TOTALS High schools 8 0 1 2 th grade rs in GEAR UP high schools 16,000 12 th grade GEAR UP Phase 1 demonstration participants 5,600 Phase 2 demonstration participants 4,000
**B.1.2 Sampling Methods**  There will be no sampling of schools for the evaluation. The entire universe of GEAR UP schools within the demonstration grant s who have agreed to random assignment will participate in the evaluation study. All 12 th grade students in these schools will par ticipate in the evaluation. Those who assent to participate in the intervention and intend to go to college will be involved in the impact study. **B.1.3 Expected Response Rates**  We expect to obtain a 100 percent response on the rosters from schools. We expect an 8 5 percent response rate on the baseline survey. Outcome data including college matriculation and persistence will be drawn from extant NSC data. The NSC includes more than 3,600 enrolling 98 percent of all students in public and private U.S. institutions, (NSC 2014c ), and NSC the primary reason enrolled students are not found in NSC is because the student suppressed their data; for the academic years of 2006
-2007, 2008
-2009, and 2010
-2011 was this rate was 4.7 percent (NSC 2012). 

### B.2 **Statistical Methods for Sa mple Selection and Degree of A** **ccuracy Needed**  **B.2.1 Sample Selection**  Random assignment will be conducted twice, once prior to each phase. The first random assignment will take place at the end of the 2016
-2017 school year; students in high schools served by GEAR UP projects who declare their intention to enroll in college will be randomly assigned to receive messages in the summer after high school (Treatment 1) or not (Control 1). The second random assignment will take place at the end of summer 2017 and students within each Phase 1 condition will be randomly assigned to receive messages in what would be sent during their first year of college if they go to college right after high school (Treatment 2) or not (Control 2). **B.2.2 Estimation Procedures**  Impact and descriptive analyses will be conducted to answer the study research questions, as described below. Part B of this Supporting Statement provides additional methodological detail.**Revised OMB Supporting Statement Promising S**  **trategies in Federal College Access Programs**

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **8 1.**  **To w hat extent do the**  **messages —** **above and beyond the services GEAR UP may already provide** 

**— improve student outcomes?**  Given that participating schools are volunteering to participate in the study (rather than being selected at random) and inferences will be focused on students in these or similar schools, the study will use a model with fixed treatment effects to assess the effect of messaging on student outcomes (Schochet, 2008). 7 The study team will control for student demographic characteristics, including gender, race/ethnicity, and f

irst generation college student status. Reflecting the randomization of students within schools, the study team will include a set of dummy variables for schools and a treatment indicator to provide an estimate of the average impact of the messaging demonstration on students across all schools. The study team will conduct a test of the null hypothesis of no treatment impact for each outcome variable. The study team will interpret a positive and statistically significant impact at the 5
-percent level (using a two -tailed test) as compelling scientific evidence that the intervention improves the targeted outcome (e.g., college enrollment, college persistence, FAFSA completion). For continuous outcome variables, the study team will estimate multilevel linear models; for dichotomous outcomes (e.g., college enrollment, FAFSA completion), the study team will estimate multilevel logistic regression models. **Multilevel Logistic Regression** For dichotomous outcomes (e.g., enrollment, persistence, and FAFSA completion), a logistic regression will be used. This model is: 

### (1) [ = 1 ] = ( 

###  0 + 

###  1 ( T ij ) + 

###  2 (Y ∗ ij ) + 

#  

 1
1 J j 

###  2 + j 

### Sch

j + 

# 

 M

m 1 

###  2 + (J
− 1 ) + m 

### X mij ) Where is the covariate
- adjusted log
- odds of the outcome occurring (e.g., enrolled in college, completed FAFSA) versus not occurring (e.g., did not enroll in college, did not complete FAFSA) for students in school j ; is a regression coefficient indicating the difference in log
- odds of the outcome between the treatment and control group , controlling for all other variables in the model ; and through parameter estimate for the average effect (in log
- odds) of each student
- level covariate on the outcome , controlling for all other variables in the model. To convert estimates produced by logistic regression to an impact measured in percentage point increases in probability of the binary outcome, we calculate the individual level probability of the outcome given treatment implied by individual level covariates and model estimates, we repeat this calculation if the individual were assigned to control, and find the mean difference between these two probabilities. **Hi erarchical Linear Model**  The following model will be used to estimate program impacts on continuous outcome variables. Given that our core outcome measures (i.e., confirmatory contrasts) are all dichotomous (i.e., college enrollment, FAFSA completion, and p ersistence into the second year of college), this HLM describes our methodology for assessing exploratory contrasts.
7 If we suspect that treatment effects differ by school, we will interact schools with the treatment indicator.**Revised OMB Supporting Statement Promising S**  **trategies in Federal College Access Programs**

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -** **9** Y ij = 

###  0 + 

###  1 (T ij ) + 

###  2 (Y * ij ) + 

#  

 1
1 J j 

###  2+j 

### Sch

j + 

# 

 M

m 1 

###  2+(J
- 1)+m 

### X mij + ij

 where Y ij is the value of the outcome (e.g., amount of Federal financial aid received) for the i th student in the j th GEAR UP school; T ij is 1 if student i is randomize d to the treatment condition in schools j and 0 if assigned to the control condition in school j ; Y * ij is the baseline score for the outcome of interest for student i in school j ; 

### Sch j 

### = 1 if student is in school j, =0 else; 

### X mij are 

###  additional covariates representing demographic characteristics of student i at school j (e.g., race/ethnicity, English language learner status); 

###  0 is the conditional mean follow
-up score for the outcome of interes t for control students; 1 

###  is the treatment effect i.e. the mean difference of the outcome between intervention and control students. The overall treatment estimate ( 

###  1 ) and will be a precision
-weighted estimate, where the weights are inversely proportional to the variance of the treatment effect in each school. ij 

###  is the residual error term assumed to be normally distributed with mean 0 and variance 

###  2

. **2. What types of college advising are typically received by GEAR UP students?**  Descriptive analyses will be used to provide information on the types of college advising GEAR UP students typically receive. It is important to understand the existing college advising to which the messaging will be added. Further, this collection and analysis has the added benefit of filling a gap in program information about the intensity of and emphasis on college advising. The study team will describe the types and intensity of college advising regularly received by GEAR UP students at the high school level as reported on the student survey. One example of the type of college advising that mi ght be received by students is one - on - one counseling or advising session s about applying to college ; the study team would describe the percent of students that attending such sessions. These results will provide another important source of contextual information for interpreting impact findings. **3. Is there variation in the impact of the messages, and to what extent is the variation**  **associated with student characteristics or features of the GEAR UP project or school?** To examine variation in program impacts by student characteristics or features of t he GEAR UP project or school, the study team will include an interaction of the treatment indicator with the subgroup variable of interest in the impact models described above. 8 The study team will include interaction terms in the model for our core dichotomous outcomes of college enrollment, FAFSA completion, and college persistence (i.e., equation 1 above), allowing the treatment impact to vary by student characteristics, such as knowledge of the college application process, understanding of financial ai d options and college costs, or amount of college advising received (e.g.one
- on - one counseling or advising sessions about applying to college )

– or by program characteristics such as whether the GEAR UP program was funded under a state grant or a partnerships grant. If significant interaction effects are found, the sample will be broken into subgroups, the treatment effect will be estimated for each subgroup, and the means and variances of the subgroup will be compared

8 This approach requires the assumption that gender is not correlated with the marginal effect of the other mo del covariates. We will evaluate whether this assumption is tenable during preliminary data exploration.**Revised OMB Supporting Statement Promising S**  **trategies in Federal College Access Programs**

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **10 B.2.3**  **Degree of A ccuracy Needed**  This section presents the power analyses conducted to estimate the minimum detectable effect sizes (MDES) for the treatment/control differences on student outcomes. The power analysis conducted utilizes a slightly modified9 version of the MDE formula provided by Scho chet (2008) for an RCT design that entails random assignment of student within schools and the corresponding 2
- level impact model:

= ( , , ) ∗ ( 1
− ) ( 1
− )
**Where** : estimated minimum detectable effect size for the treatment impact;

( , , ) : a constant that is a function of the significance level (α), statistical power (β), and the number of degrees of freedom (df);
s: number of schools;
m: average number of students in each school; p: proportion of students assigned to the treatment condition;

: Student
- level variance in the outcome; : Proportion of student
- level variance in the outcome explained by covariates;
σ: standard deviation of the outcome measure. **Using the equation above we make the following assumptions:** (1) Randomization of students within schools to treatment or control conditions (2) S tudent level outcome of interest is measured on a continuous sc ale (3) 80 percent power (4) Two -tailed testing at the 5 percent level (alpha level=0.05) (5) The demonstration includes s= 80 schools (6) The demonstration includes m= 70 students per school (7) 35 students are assigned to each group (p=0.5) (8) The variance of the outcome across students (σ 2 students ) = σ=1 (because of standardization) (9) The proportion of variation explained by student level covariates ( R ) is 0.1 Because our key outcomes (i.e., college enrollment, college, FAFSA completion, and college persistence) are all dichotomous variables , the power calculations also present the minimum

9 The Schochet (2008) formula was modified to include the term .**Revised OMB Supporting Statement Promising S**  **trategies in Federal College Access Programs**

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **11** detectable effect size (MDES) expressed as a difference in percentage points between successes in the treatment and control groups using the following formula: **Conversion of MDES to MD E.PP**  Since the standard deviation of a proportion (P) is 

### ) 1 ( * P P

 and MDES are expressed in standard deviation units, we used the following formula to convert MDES to MDE.PP (the MDE expressed as a difference in percentage points between successes in the treatment and control groups): 

### ) 1 ( * *
. BaseRate

BaseRate MDES PP MDE

  ; where the B aseRate is the rate (percent) of success in absence of treatment i.e. success in the control condition. Exhibit B
- 3 shows the minimum detectable effect size (MDES) we would be powered to detect for Phase 1 with 80 schools and 70 students per school (35 in each group) would be approximately 2
-4 percentage points depending on the base rate. Exhibit B
- 5 shows the minimum detectable effect size (MDES) we would be powered to detect for Phase 2 with 50 students per school (25 in each group) would be approximately 2 to 4 percentage points 10 depending on the base rate.

10 This difference is smaller than the 12 percentage points difference in persistence rates into the fall of sophomore year between community college freshmen who received a text intervention and those that did not receive the intervention, Castleman, B.L., & Page, L.C. (2014).**Revised OMB Supporting Statement Promising Strategies in Federal College Access Programs** 

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **12 Exhibit**  **B -**  **5 : Power Calculations for**  **Dichotomous Outcomes in Phase 1 of the Study**  **Number of schools**  **Number of students**  **Number of school**

**X Number of students**  **R 2**  **student Mi**  **nimum Detectable Effect**  **Sizes (MDEs) in standard**  **deviations Base Rate** 

**(success in absence of**  **treatment i.e. success in the**  **control condition)**  **MDE expressed**

**as a difference in percentage points**  **between successes in the**  **treatment and control groups**  80 70 5600 0.00 0.075 10 2.2 80 70 5600 0.05 0.073 10 2.2 80 70 5600 0.10 0.071 10 2.1 80 70 5600 0.20 0.067 10 2.0 80 70 5600 0.00 0.075 25 3.2 80 70 5600 0.05 0.073 25 3.2 80 70 5600 0.10 0.071 25 3.1 80 70 5600 0.20 0.067 25 2.9 80 70 5600 0.00 0.075 50 3.7 80 70 5600 0.05 0.073 50 3.6 80 70 5600 0.10 0.071 50 3.6 80 70 5600 0.20 0.067 50 3.4 80 70 5600 0.00 0.075 60 3.7 80 70 5600 0.05 0.073 60 3.6 80 70 5600 0.10 0.071 60 3.5 80 70 5600 0.20 0.067 60 3.3 80 70 5600 0.00 0.075 75 3.2 80 70 5600 0.05 0.073 75 3.2 80 70 5600 0.10 0.071 75 3.1 80 70 5600 0.20 0.067 75 2.9 80 70 5600 0.00 0.075 86 2.6 80 70 5600 0.05 0.073 86 2.5 80 70 5600 0.10 0.071 86 2.5 80 70 5600 0.20 0.067 86 2.3**Revised OMB Supporting Statement Promising Strategies in Federal College Access Programs** 

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **13 Exhibit**  **B -**  **5 : Power Calculations for Dichotomous Outcomes in Phase 2 of the Study**  **Number of schools**  **Number of students**  **Number of school**

**X Number of**  **students R** **2 student**  **Mi nimum**  **Detectable Effect Sizes (MDEs) in**  **standard deviations**  **Base Rate**

**(success in absence of**  **treatment i.e. success in the**  **control condition)**  **MDE expressed**

**as a difference in percentage points**  **between successes in the**  **treatment and control groups**  80 50 4000 0.00 0.106 10 2.7 80 50 4000 0.05 0.103 10 2.6 80 50 4000 0.10 0.101 10 2.5 80 50 4000 0.20 0.095 10 2.4 80 50 4000 0.00 0.106 25 3.8 80 50 4000 0.05 0.103 25 3.7 80 50 4000 0.10 0.101 25 3.6 80 50 4000 0.20 0.095 25 3.4 80 50 4000 0.00 0.106 50 4.4 80 50 4000 0.05 0.103 50 4.3 80 50 4000 0.10 0.101 50 4.2 80 50 4000 0.20 0.095 50 4.0 80 50 4000 0.00 0.106 60 4.3 80 50 4000 0.05 0.103 60 4.2 80 50 4000 0.10 0.101 60 4.1 80 50 4000 0.20 0.095 60 3.9 80 50 4000 0.00 0.106 75 3.8 80 50 4000 0.05 0.103 75 3.7 80 50 4000 0.10 0.101 75 3.6 80 50 4000 0.20 0.095 75 3.4 80 50 4000 0.00 0.106 86 3.1 80 50 4000 0.05 0.103 86 3.0 80 50 4000 0.10 0.101 86 2.9 80 50 4000 0.20 0.095 86 2.8**Revised OMB Supporting Statement Promising Strategies in Federal College Access Programs** 

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **14 B.2.4**  **Unusual Problems Requiring Specialized Sampling Procedures** Unusual problems that require specialized sampling procedures are not anticipated. **B.2.5 Use of Periodic Data Collection Cycles to Reduce Burden**  The data collection plan reflects sensitivity to issues of efficiency and respondent burden. In this study, the study team planned data collection at the fewest intervals possible to reduce burden and ensure the quality of the data . The student rosters will only be collected once. Student surveys will be fielded once during this study
. Administrative records, rather than surveys, will be used to gather data on outcomes. 

### B.3 **Methods to Maximize Response Rates and Deal with Nonresponse** In order to obtain responses from the study sample, the study team has developed strategies to facilitate communication with respondents during data collection activities and to maximize response rates . These strategies have proven successful in the study team’s extensive experience conducting large
- scale evaluation studie s (e.g., Reading First Impact Study, Evaluation of the U.S. Department of Education’s Student Mentoring Program, Evaluation of the Massachusetts Expanded Learning Time Initiative; Enhanced Reading Opportunities Study; Career Academies Evaluation; The Teacher Incentive Fund Evaluation , and Study of Enhanced College Advising in Upward Bound). The study team will follow several procedures to maximize response rate s and handle nonresponse
. **Student Rosters .**  During the August 2016 meeting of the association of GEAR UP grantees organized by the National Council for Community and Education Partnerships , the study team will provide an evaluation session for participating project directors and school coordinators that will clearly explain the importance of the study and the role s and responsibilities of project directors and school coordinators , including the process for submitting student rosters
. During the 2016
-2017 school year, each school will be assigned a study liaison to answer questions and explain the demonstration requirements. Next, the liaison will send an email to each site coordinator explaining the request that will be made of site coordinators (see Appendix B ). School coordinators will be asked to submit rosters of 12 th grade students through a password protected secure file transfer portal (SFTP). One week after sending out the email request, a member of the study team will reach out to each coordinator via a telephone call during to answer any questions about the roster submission. The submission of student rosters via a password protected SFTP will allow coordinators to submit rosters at a time most convenient for them and will assure coordinators that student confidentially is protected as permitted by law. **Baseline student surveys.** The baseline student surveys will be administered in electronic or paper format
. To assist data collection, the site liaison will work with each GEAR UP school to determine whether in
- school administration is feasible and to : facilitate the logistics for the baseline student survey data collection; track response rates per project and communicate with project directors, as needed; remind students about the survey; and distribute individualized thank you or reminder letters to students near the end of the survey field period. The study team will make the survey available in multiple modes (electronic and paper) and individual follow
-up will be conducted to reach students who were absent during in
-person administration.**Revised OMB Supporting Statement Promising Strategies in Federal College Access Programs** 

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **15** 

### B.4 **Test of Procedures and Methods to be Undertaken** We do not believe pretesting is necessary for the collection of student rosters , as the study team will be following a procedure that has been successful in studies such as the Evaluation of Citizen Schools: School

-Level Expanded Learning Time and the Study of Enhanced College Advising in Upward Bound
. During the 60
- day comment period, the baseline survey will be pilot tested. The pilot tests will ensure that the survey administration procedures are effective, the instructions are understandable, the content is comprehensible, and the length is reasonable. High school seniors from GEAR UP will be recruited for the pilot testing; no more than nine students will be selected to participate in the pilot test. 

### B.5 **Individuals Consulted on Statistical A spects of the Design**  The fol lowing individuals were consulted on the statistical aspects of the study: **Name Title/A**  **ffiliation Telephone**  Mr. Cristofer Price Principal Scientist, Abt Associates 301 - 634 - 1852 Dr. Alina Martinez Principal Associate , Abt Associates 617 - 349 - 2312 Dr. Rob Olsen Principal Scientist, Abt Associates 301 - 634 - 1716 Dr. Allan Porowski Principal Associate, Abt Associates 301 - 634 - 1765 Dr. Anne W olf Associate, Abt Associates 301 - 634 - 1738 Ms. Am anda Parsad Senior Scientist , Abt Associates 301 - 634 - 1791 The following individuals will be responsible for the Data Collection and Analysis: **Name Title/A**  **ffiliation Telephone**  Dr. Alina Martinez Principal Associate , Abt Associates 617 - 349 - 2312 Mr. Cristofer Price Principal Scientist, Abt Associates 301 - 634 - 1852 Dr. Rob Olsen Principal Scientist, Abt Associates 301 - 634 - 1716 Dr. Amanda Parsad Senior Scientist , Abt Associates 301 - 634 - 1791 Dr. Tamara Linkow Associate, Abt Associates 617 - 520 - 2978 Ms. Linda Kuhn President, Survey Research Management 303 - 247 - 0140**Revised OMB Supporting Statement Promising Strategies in Federal College Access Programs** 

**Abt Associates Inc. Part B:**  **Collection of Information Employ ing Statistical Methods**  **▌ pg.**  **B -**  **16** 

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