NPSAS 2012 Full Scale Institution Part B

B. Collection of Information Employing Statistical Methods

A.Collection of Information Employing Statistical Methods

This submission requests clearance for the 2011-12 National Postsecondary Student Aid Study (NPSAS:12) full-scale institution contacting, enrollment list collection, list sampling, and student contacting activities. The student institution record and student survey instruments will be submitted in a separate package, to be delivered in September 2011. Specific plans are provided below.

1.Respondent Universe

a.Institution Universe

To be eligible for NPSAS:12, an institution will be required, during the 2011-12 academic year, to:

• offer an educational program designed for persons who had completed secondary education;

• offer at least one academic, occupational, or vocational program of study lasting at least 3 months or 300 clock hours;

• offer courses that are open to more than the employees or members of the company or group (e.g., union) that administered the institution;

• be located in the 50 states or the District of Columbia;

• be other than a U.S. Service Academy; and

• have a signed Title IV participation agreement with the U.S. Department of Education.

Institutions providing only avocational, recreational, or remedial courses or only in-house courses for their own employees will be excluded. U.S. Service Academies are excluded because of their unique funding/tuition base.

b.Student Universe

The students eligible for inclusion in the sample are those who are enrolled in a NPSAS-eligible institution in any term or course of instruction between July 1, 2011, and April 30, 2012, and who are:

• enrolled in either (a) an academic program; (b) at least one course for credit that could be applied toward fulfilling the requirements for an academic degree; (c) exclusively non-credit remedial coursework but who the institution has determined are eligible for Title IV aid; or (d) an occupational or vocational program that required at least 3 months or 300 clock hours of instruction to receive a degree, certificate, or other formal award;

• not currently enrolled in high school; and

• not enrolled solely in a GED or other high school completion program.

2.Statistical Methodology

a.Institution Sample

The NPSAS:12 full-scale institution sampling frame was constructed during the field test from the IPEDS:2008–09 header, Institutional Characteristics, 12-Month Enrollment, and Completions files.¹ For the small number of institutions on the frame that had missing enrollment information, we imputed the data using the latest IPEDS imputation procedures to guarantee complete data for the frame.

We selected the field test institution sample statistically, rather than purposively as had been done in past NPSAS cycles. A statistical sample provides more control to ensure that the field test and the full-scale institution samples have similar characteristics, and will allow inferences to be made to the target population, supporting the analytic needs of the field test experiments. In order to accomplish this, NPSAS:12 also changed the process by which the institution sample was selected. Previous cycles selected the full-scale sample prior to selecting the field test sample from the complement. NPSAS:12 selected both institution samples simultaneously. First, a sample of 1,971 institutions, comprising the institutions needed for both the field test and full scale studies, was selected from the stratified frame. Then, 300 of the 1,971 institutions were selected for the field test using simple random sampling within institutional strata. The remaining 1,671 institutions comprise the full-scale sample. Figure 1 displays the flow of institution sampling activities.

Figure 1. NPSAS:12 institution sample flow

We selected institutions for the initial sample using sequential probability minimum replacement (pmr) sampling (Chromy 1979), which resembles stratified systematic sampling with probabilities proportional to a composite measure of size (Folsom, Potter, and Williams 1987). This is the same methodology that we have used since NPSAS:96. PMR allows institutions to be selected multiple times but, instead of allowing that to happen, all institutions with a probability of being selected more than once were instead included in the sample one time with certainty, i.e., were a certainty institution. Institution measures of size were determined using annual enrollment data from the most recent IPEDS 12-Month Enrollment Component. Using composite measure of size sampling will ensure that target sample sizes are achieved within institution and student sampling strata while also achieving approximately equal student weights across institutions. Consistent with past procedures, we will use updated IPEDS files to freshen the institution sample in the summer of 2011 in order to add newly eligible institutions to the sample and produce a sample that is representative of institutions eligible in the 2011-12 academic year.

The 10 institutional strata are based on institutional level, control, and highest level of offering:²

1. public less-than-2-year

2. public 2-year

3. public 4-year non-doctorate-granting

4. public 4-year doctorate-granting

5. private not-for-profit less-than-4-year

6. private not-for-profit 4-year non-doctorate-granting

7. private not-for-profit 4-year doctorate-granting

8. private for-profit less-than-2-year

9. private for-profit 2-year

10. private for-profit 4-year.

Although prior NPSAS administrations aggregated private for-profit 2-year and 4-year institutions into one sampling strata, the two will be split in NPSAS:12 into separate strata to reflect the recent growth in enrollment in for-profit 4-year institutions. Conversely, due to a low absolute number of 2-year and less-than two-year not-for-profit institutions, these once separate strata have been combined. We expect to obtain about an overall 97 percent eligibility rate among sampled institutions.

The institutional response rate is expected to be about 85 percent. The eligibility and response rates will likely vary by institutional strata. Based on these expected rates, the estimated institution sample sizes and sample yield by the ten institutional strata are presented in table 7.

Within each institutional stratum, additional implicit stratification for the full-scale was accomplished by sorting the sampling frame within stratum by the following classifications: (1) historically Black colleges and universities indicator; (2) Hispanic-serving institutions indicator³ (3) Carnegie classifications of postsecondary institutions;⁴ (4) the Office of Business Economics (OBE) Region from the IPEDS header file (Bureau of Economic Analysis of the U.S. Department of Commerce Region); (5) state and system for states with large systems, e.g., the SUNY and CUNY systems in New York, the state and technical colleges in Georgia, and the California State University and University of California systems in California; and (6) the institution measure of size. The objective of this implicit stratification was to approximate proportional representation of institutions on these measures.

Table 7. NPSAS:12 full-scale institution sample sizes and yield

Institutional sector	Frame count1	Number sampled	Number eligible	Anticipated List respondents
Total	6,665	1,671	1,651	1,402
Public
Less-than 2-year	240	20	17	13
2-year	1,102	381	381	335
4-year non-doctorate-granting	356	130	130	117
4-year doctorate-granting	309	230	230	200
Private
Not-for-profit less-than-4-year	252	20	20	17
Not-for-profit 4-year non-doctorate-granting	1,019	260	260	218
Not-for-profit 4-year doctorate-granting	548	220	220	183
For-profit less-than-2-year	1,325	50	47	38
For-profit 2-year	952	110	106	86
For-profit 4-year	562	250	240	195

¹ Institution counts based on IPEDS:2008 09 header files.

b.Student Sample

In this section, we describe the student sample design, including our plans for sampling students from enrollment lists.

Based on past experience, we expect to obtain an overall 95 percent student eligibility rate and an overall 75 percent student interview response rate.⁵ The preliminary sample sizes and sample yield are presented in table 8. As indicated in the table, the sample will be designed to include about 117,000 students. The distribution of the sample by institution and student strata will be finalized after we complete institution sample freshening and identify key analytic domains (especially for FTBs).

Several student subgroups will be intentionally sampled at rates different than their natural occurrence within the population due to specific analytic objectives. We anticipate that two groups will be oversampled to increase our ability to better understand their unique experiences within postsecondary education. Specifically:

1. Undergraduates, both FTB and non-FTB, at all award levels enrolled in for-profit institutions, who receive about 25 percent of disbursed federal aid despite constituting only about 11 percent of the student population; and

2. First-time beginning undergraduates enrolled in sub-baccalaureate programs at all types of institutions, which have important early labor market experiences that can only be explored via BPS if sufficient starting sample is identified.

Similarly, we anticipate that two students groups will be undersampled: graduate students in business and education. Because of their sheer number, these sample members make it difficult to draw inference about the experiences of graduate students in other disciplines, particularly those related to science, engineering, technology, and mathematics (STEM), which we anticipate oversampling.

We will identify potential FTBs for longitudinal follow up, and the remaining undergraduate students will be classified as other undergraduates. The NPSAS sampling rates for students identified as potential FTBs and other undergraduate students will be adjusted based on field test results, as well as on results from both NPSAS:04 and BPS:04/06, to yield the appropriate sample sizes after accounting for expected false positive and false negative rates by sector. Table 8 does not include the adjusted sample sizes, but a large percentage of the sample may be comprised of potential FTBs in order to obtain a BPS:12/14 sample yield of at least 18,300.

Table 8. NPSAS:12 preliminary student sample sizes and yield

Institutional sector	Sample students				Eligible students				Interview Respondents				Responding students per responding institution
	Total	FTBs	Other undergraduate Students	Graduate students	Total	FTBs	Other undergraduate students	Graduate students	Total	FTBs	Other undergraduate students	Graduate students
Total	117,256	39,404	64,786	13,067	111,420	37,191	61,489	12,740	83,553	28,867	45,492	9,194	60
Public
Less-than 2-year	1,250	652	598	0	1,006	525	482	0	643	353	289	0	51
2-year	41,626	13,482	28,145	0	38,875	12,590	26,284	0	28,035	9,690	18,345	0	84
4-year non-doctorate-granting	8,190	1,777	5,274	1,140	7,994	1,734	5,147	1,112	6,458	1,503	4,307	648	55
4-year doctorate-granting	19,560	3,514	11,883	4,162	19,180	3,446	11,652	4,081	15,842	3,053	9,708	3,081	79
Private not-for-profit
Less-than-4-year	1,606	852	754	0	1,443	766	677	0	838	471	368	0	49
4-year non-doctorate-granting	8,460	2,410	3,888	2,162	8,238	2,347	3,786	2,105	6,847	2,080	3,269	1,499	31
4-year doctorate-granting	7,275	1,546	1,629	4,100	7,112	1,512	1,593	4,008	5,756	1,325	1,416	3,014	32
Private for-profit
Less-than-2-year	3,888	2,123	1,765	0	3,343	1,825	1,518	0	1,816	1,051	765	0	48
2 year	6,245	3,410	2,836	0	5,973	3,261	2,712	0	4,288	2,447	1,841	0	50
4 year	19,156	9,638	8,015	1,503	18,255	9,185	7,638	1,432	13,029	6,893	5,184	952	67

NOTE: FTB = first time beginner.

At the present time, we plan to employ a variable-based (rather than source-based) definition of a study member, like that used in NPSAS:04 and NPSAS:08, updated as needed by any changes to the interview.⁶ Specifically, a NPSAS:12 study member will be defined as any sample member who is determined to be eligible for the study and, minimally, has valid data from any source for the following:

• student type (undergraduate or graduate);

• date of birth or age;

• gender; and

• at least 8 of the following 15 variables:

• dependency status;

• marital status;

• any dependents;

• income;

• expected family contribution (EFC);

• degree program;

• class level;

• FTB status;

• months enrolled;

• tuition;

• received federal aid;

• received non-federal aid;

• student budget;

• race; and

• parent education.

We expect the rate of study membership to be about 90 percent.⁷

The six student sampling strata will be:

1. first-time beginning undergraduate students

2. other undergraduate students

3. master’s degree students

4. doctoral-research/scholarship/other students

5. doctoral-professional practice students⁸

6. other graduate students.⁹

As was done in past rounds of NPSAS, certain student types (potential FTBs, other undergraduates, master’s students, doctoral-research/scholarship/other students, doctoral-professional practice students, and other graduate students) will be sampled at different rates to control the sample allocation. Differential sampling rates facilitate obtaining the target sample sizes necessary to meet analytic objectives for defined domain estimates.

Creating student sampling frames. Sample institutions will be asked to provide an electronic student enrollment list. The following data items will be requested for NPSAS-eligible students enrolled at each sample institution. Most of these items are the same as what was collected in past NPSAS studies:

• Name

• Social Security Number (SSN)

• Student ID number (if different from SSN)

• Student level (undergraduate, masters, doctoral-research/scholarship/other, doctoral-professional practice, other graduate)

• FTB indicator

• Class level of undergraduates (first year, second year, etc.)

• Date of birth (DOB)

• CIP or major

• Degree program

• High school graduation date (month and year)

• Contact information (local and permanent street address and phone number and school and home e-mail address)

These data items are described in greater detail in Part C.

As with NPSAS:04 and NPSAS:08, we will request locating data from institutions concurrent with the collection of student lists used for sample selection. This will allow web-based student record collection and interviewing to begin almost immediately after sample selection and thus help meet the very tight schedule for data collection, data processing, and file development. For institutions unwilling to provide locating data for all students on enrollment lists, we will request locating data only for sampled students immediately after the sample is selected.

The FTB indicator, class level, and date of birth will be used to identify and oversample potential FTBs, as described below.

High school graduation date has not been requested on lists in the past for NPSAS, so we tested the feasibility of this request in the field test. While the field test is ongoing, thus far the majority of institutions were able to provide this field, and no institution complained about being asked to do so. The information proved useful in identifying current high school students who were ineligible for the study.

CIP code and major have been collected in the past for NPSAS in order to help identify baccalaureate recipients who are business majors, so that they could be undersampled in NPSAS years that spin off the Baccalaureate and Beyond Longitudinal Study. In NPSAS:08, CIP code and major were also used to oversample science, technology, engineering, and math (STEM) majors who were not SMART grant recipients. For NPSAS:12, as discussed above, there is interest in undersampling business and education graduate students and oversampling graduate students in STEM fields. Therefore CIP code and major will be collected in the full scale study. Schools will also be asked to provide degree program which we anticipate using to identify FTBs in sub-baccalaureate programs.

In the field test, we requested an indicator of whether the institution received an ISIR (electronic record summarizing the results of the student’s FAFSA processing) from CPS. This was considered potentially useful in FTB analyses; however it has not proved useful for that purpose and, therefore, will not be requested in the full scale study.

Obtaining student enrollment lists. To ensure the secure transmission of sensitive information on the enrollment lists, we will provide the following options to institutions: (1) upload encrypted student enrollment list files to the project’s secure website using a login ID and “strong” password provided by RTI, or (2) provide an appropriately encrypted list file via e-mail (RTI will provide guidelines on encryption and creating “strong” passwords). In the field test, only two institutions e-mailed their lists, and the rest of the institutions uploaded them.

Based on NPSAS:08 and field test results we expect that few institutions will ask to provide a paper list. However, in the event that an institution is unable to transmit data via the secure electronic methods of transmission outlined above, we will accept faxes sent to a secure electronic fax machine. To ensure the fax transmission is sent to the appropriate destination, we will require a test run with nonsensitive data prior to submission of the transcripts to eliminate errors in transmission from misdialing. RTI will provide institutions with a fax cover page that includes a confidentiality statement to use when transmitting individually identifiable information.

List files received via e-fax are stored as electronic files on the e-fax server, which is housed in a secured data center at RTI. These files will be copied to a project folder that is only accessible to project staff members. Access to the project folder will be set so that only those who have authorized access will be able to see the included files. After being copied, the files will be deleted from the e-fax server. The files will be stored on the network that is backed up regularly to avoid the need to recontact the institution to provide the data again should a loss occur. RTI’s information technology service will use standard procedures for backing up data, so the backup files will exist for 3 months.

Identifying FTBs during the base year. Accurately qualifying sample members as FTBs is a continuing challenge. Correctly classifying FTBs is important because unacceptably high rates of misclassification (i.e.., false positives) can and have resulted in (1) excessive cohort loss with too few eligible sample members to sustain the longitudinal study, (2) excessive cost to “replenish” the sample with little value added, and (3) inefficient sample design (excessive oversampling of “potential” FTBs) to compensate for anticipated misclassification error.

We will take several steps early in the NPSAS:12 listing and sampling processes to improve the rate at which FTBs are correctly classified for sampling. First, in addition to an FTB indicator, we will request that enrollment lists provided by institutions (or institution systems) include class level, student level, date of birth, and high school graduation date. Students identified by the institution as FTBs, but also identified as in their third year or higher and/or not an undergraduate student, will not be classified as FTBs for sampling. Additionally, students appearing to be dually enrolled at the postsecondary institution and in high school based on the high school graduation date will also not be eligible for sampling. If the FTB indicator is not provided for a student on the list but the student is 18 years old or younger and does not appear to be dually enrolled, the student will be classified as an FTB for sampling. Otherwise, if the FTB indicator is not provided for a student on the list and the student is over the age of 18, then the student will be sampled as an “other undergraduate,” but will be part of the BPS cohort if identified during the interview as an FTB.

Second, prior to sampling, we will match those students over the age of 18 and listed as potential FTBs to National Student Loan Data System (NSLDS) records to determine if any have a federal financial aid history pre-dating the NPSAS year (earlier than July 1, 2010 for the field test and July 1, 2011 for the full-scale). Since NSLDS maintains current records of all Title IV grant and loan funding, any students with data showing disbursements from prior years can be reliably excluded from the sampling frame of FTBs. Given that about 60 percent of FTBs receive some form of Title IV aid in their first year, this matching process will not be able to exclude all listed FTBs with prior enrollment, but will significantly improve the accuracy of the listing prior to sampling, yielding fewer false positives. Only students over 18 years of age will be sent to NSLDS because most students 18 and younger are FTBs. In the field test, matching to NSLDS identified about 19 percent of the cases sent for matching as false positives. The field test showed that it is feasible to send all potential FTBs to NSLDS for matching. NSLDS has a free process to match the FTBs, and lists were usually returned to us in one day.

Third, simultaneously with NSLDS matching, we will match potential FTBs over the age of 18 to the Central Processing System (CPS) to identify students who, on their FAFSA, indicated that they had attended college previously. In the field test, we evaluated this process for potential FTBs from a subset of 94 institutions, mainly public and private not-for-profit institutions, and found that we identified as false positives an additional 2.4 percent of the initial pool of potential FTBs who were not identified by NSLDS and NSC. CPS has an automated, free process for matching that we have used for other purposes in the past for NPSAS sample students. This matching can handle large numbers of cases, and the matching usually takes one day. Because there is a cost for matching to another source, described below, we plan to continue matching to CPS.

Fourth, after NSLDS and CPS matching, we will match a subset of the remaining potential FTBs to the NSC for further narrowing of FTBs based on the presence of evidence of earlier enrollment. In the field test, matching to National Student Clearinghouse (NSC) identified about 14 percent of the remaining potential FTBs, after NSLDS matching, as false positives. NSC worked with us to set up a process that can handle a large number of potential FTBs and return FTB lists to us within two or three days. There is a “charge per case matched” for NSC matching, so we plan a targeted approach to the matching. After field test data collection ends, we will examine the number of false positives identified in the interview by sector and, in conjunction with the pre-sampling matching results, will determine how best to use NSC matching.

Fifth, in setting our FTB selection rates, we will take into account error rates observed in the field test, in NPSAS:04, and in BPS:04/06, within each sector. As shown in table 9, some NPSAS:04 institution sectors were better able to accurately identify their students as FTBs. While the sample selection rates will take into account false positive rates, we do anticipate achieving an improvement in accuracy from the NSLDS and NSC record matches and, based on field test results, will adjust selection rates accordingly. Table 10 shows the preliminary field test false positive identification from NSLDS and NSC matching by sector.

Table 9. Weighted false positive rate observed in FTB identification, by sector: NPSAS:04

Sector in NPSAS:04	False positive rate (weighted)
Public
Less-than 2-year	64.4
2-year	72.5
4-year non-doctorate-granting	26.8
4-year doctorate-granting	27.0
Private not-for-profit
Less-than-4-year	63.1
4-year non-doctorate-granting	43.4
4-year doctorate-granting	15.2
Private for-profit
Less-than-2-year	63.1
2 years or more	70.0

FTB = first time beginner.

Table 10. Preliminary unweighted false positive rates based on matching enrollment lists to NSLDS and NSC matching, by sector: NPSAS:12 field test

Sector in NPSAS:12	False positive rate
	NSLDS	NSC1	Overall
All institutions	19.2	14.1	30.6
Public
Less-than 2-year	29.8	29.1	50.2
2-year	22.0	13.7	32.8
4-year non-doctorate-granting	6.7	7.0	13.3
4-year doctorate-granting	4.2	13.0	16.6
Private not-for-profit
Less-than-4-year	8.7	16.3	23.6
4-year non-doctorate-granting	20.1	12.3	29.9
4-year doctorate-granting	13.0	14.1	25.3
Private for-profit
Less-than-2-year	33.6	25.4	50.4
2 year	25.5	20.8	41.0
4-year	48.4	22.7	60.1

FTB = first time beginner

1 = Only potential FTB’s not identified as false positives in NSLDS matching were sent to NSC for matching.

Quality control checks for lists. Several checks on the quality and completeness of student lists will be implemented before the sample students are selected. For example, the lists will fail quality control checks if student level and/or the FTB indicator are not included on the list. Additionally, the unduplicated total of students at the undergraduate and graduate levels on each institution’s student list will be checked against the latest IPEDS unduplicated enrollment data from the 12-Month Enrollment Survey. Contact information will be checked carefully for each enrollment list as well as for each student sampled. If an institution does not provide high school graduation date, but includes many students who are less than 18, the list will fail quality control checks because it may erroneously contain high school students.

Institutions failing quality control checks will be re-contacted to resolve the discrepancy and verify that the institution coordinator who prepared the student list(s) clearly understood our request and provided a list of the appropriate students. Should we determine that the initial list provided by an institution is not satisfactory, we will request a replacement list. We will proceed with selecting sample students when we have either confirmed that the list received is correct or have received a corrected list. If the list is incorrect, but the institution will not or cannot correct it, we will determine if we can proceed with selecting sample students, depending on the problem.

Selection of sample students. Students will be sampled on a flow basis, as student lists are received, using a stratified systematic sampling procedure. Sample yield will be monitored by institution and student sampling strata, and the sampling rates will be adjusted early, if necessary, to achieve the desired sample yield. Student contact materials are presented in appendix D, along with the script for a stop action video to be sent to students to encourage participation. The effectiveness of the video in improving participation rates is being evaluated in the field test data collection and will be reported in the OMB submission scheduled for September 2011.

Quality control checks for sampling. RTI has developed technical operating procedures (TOPs) that describe how to properly implement statistical procedures and QC checks. We will employ a checklist for use by all NPSAS:12 statisticians to ensure that appropriate QC checks are performed.

Some specific sampling QC checks will include, but will not be limited to, checking that the:

• students on the sampling frames all have a known, non-zero probability of selection;

• number of students selected match the target sample size; and

• sample weight for each student is the inverse of the probability of selection.

Tracing prior to the start of data collection. Once the sample is selected, RTI will conduct several batch database searches to prepare the sample for the start of student interviews. The first step in the batch tracing process will be to match to the U.S. Department of Education's CPS and the National Change of Address (NCOA) database to obtain updated contact information. Any new information collected from CPS or NCOA matches will be added to the NPSAS locator database and will be used to attempt to match to Telematch to capture any updated telephone numbers needed for the start of computer-assisted telephone interview (CATI) data collection. Batch locating is the final step before the start of data collection.

To achieve the desired response rate, we propose an integrated tracing approach that consists of several steps designed to yield the maximum number of locates with the least expense. The steps of our tracing plan include the following elements:

• Matching student list information with NCOA, Phone Append, CPS, and other databases, which will yield locating information for the students sampled for NPSAS:12.

• Advance tracing prior to the start of CATI efforts. Not all schools will be able to give complete or up-to-date locating information on each student, and some cases will require more advance tracing, before mailings can be sent or the cases can be worked in CATI. RTI plans to conduct batch tracing on all cases to obtain updated address information prior to mailing the lead letters. This step will minimize the number of returned letters and maximize the number of early completes. To handle cases for which mailing address, phone number, or other contact information is invalid or unavailable, RTI plans to conduct advance tracing of the cases prior to lead letter mailout and data collection. This advance tracing will involve searching for address, telephone and email information. As lead information is found, additional searches can be conducted through interactive databases to provide more comprehensive information for the individual.

• Pre-intensive tracing including FastData and Accurint. We plan to send cases to both FastData and Accurint to identify a new phone number, to minimize the number of cases requiring more expensive intensive interactive tracing. Through FastData we can tap into 260 million consumer records and over 33 million public records. We are also able to access a national directory assistance database—updated daily—of over 156 million phone numbers. FastData has also recently added a more comprehensive cell phone search (SuperPhones & Phone+Premium) built into existing searches; obtaining reliable cell phone numbers is becoming an increasingly critical component of locating and interviewing this population. Accurint is a flexible search vendor capable of providing a variety of contact information for a very low cost per case. This vendor provides an indicator that the phone number returned has been verified as accurate and belonging to a subject in the past 24 hours. Accurint uses SSN to search, making it a viable tool for NPSAS:12 and the follow-up studies due to the high percentage of SSNs we expect to obtain on the student enrollment lists and through tracing sources and student interviews.

• Conducting intensive in-house tracing, including proprietary database searches. RTI’s tracing specialists conduct intensive interactive searches to locate contact information for sample members. In NPSAS:08, about 60 percent of sample members requiring intensive tracing were located, and about 59 percent of those located responded to the interview. Intensive interactive tracing differs from batch tracing in that a tracer can assess each case on an individual basis to determine which resources are most appropriate and the order in which they should be used. Intensive interactive tracing is also much more detailed due to the personal review of information. During interactive tracing, tracers utilize all previously obtained contact information to make tracing decisions about each case. These intensive interactive searches are completed using a special program that works with RTI’s CMS to provide organization and efficiency in the intensive tracing process. Sources that may be used, as appropriate, include credit database and insurance database searches through Experian, ChoicePoint, various public websites, and other integrated database services. (Although LexisNexis and TransUnion have been used in the past on RTI studies, they are no longer used for batch or interactive searches because the costs have increased while the results have become substandard. FastData has replaced TransUnion as a source for obtaining SSNs because FastData does this more cost-effectively).

• Conducting searches for hard-to-locate sample members on university, college, or personal web pages and social networking sites such as MySpace, Facebook. We propose to set up a project Facebook page that can be used to send a message to sample members located on Facebook. Facebook is currently the fastest-growing social networking site with about 500 million users at the time of this writing.

3.Institutional Contacting

Establishing and maintaining contact with sampled institutions throughout the data collection process is vital to the success of NPSAS:12. Institutional participation is required in order to draw the student sample and collect institutional student records. The process in which institutions will be contacted is depicted in figure 2 and described below.

Figure 2. Flow chart of institutional contacting activities

Experienced staff from RTI’s Call Center Services will be responsible for contacting institutions. Each staff member will be assigned a set of institutions that is their responsibility throughout the data collection process. This allows RTI staff members to establish rapport with the institution staff and provides a reliable point of contact at RTI. Staff members are thoroughly trained in basic financial aid concepts and in the purposes and requirements of the study, which helps them establish credibility with the institution staff.

Verification calls will be made to each sampled institution to confirm eligibility and verify contact information prior to mailing study information. This information will be obtained from the IPEDS header files. A sample of the script used for these calls can be found in appendix E. Once the contact information is verified, we will prepare and send an information packet to the chief administrators of each sampled institution. A copy of the letter and brochure can be found in appendix D. The materials will provide information about the purpose of the study and the nature of subsequent requests. Approximately one week after the information packet is mailed, institutional contactors will conduct follow-up calls to secure study participation.

The choice of an appropriate institutional coordinator will be left to each institution. As with NPSAS:08, the NPSAS:12 institutions will be urged to appoint their Financial Aid director as institution coordinator. Financial Aid directors are typically more familiar with the NPSAS study than are their colleagues in the institutional research or the registrar’s office. These staff are most likely to have access to student data, and are equipped to forward each data request to the most appropriate office for completion. RTI institution contactors will work with the chief administrator’s office in attempting to designate the most appropriate coordinator. Campus offices other than financial aid (e.g., registrar, admissions) usually provide part of the institution data for sample students. For NPSAS:12, RTI will identify relevant multicampus systems within the full-scale sample as these systems can supply enrollment list data at the system level, minimizing burden on individual campuses. Even when it is not possible for a system to supply system-wide data, they can lend support in other ways, such as by prompting institutions under their jurisdiction to participate.

The institutional coordinator will receive a mailing containing study materials and, as a first step, will be asked to complete the online Institutional Registration Page (IRP). A copy of the IRP is included in Appendix D. The primary function of the IRP is to confirm the date the institution will be able to provide the student enrollment list. Based on the information provided, a customized timeline will be created for each institution.

As a second step, institutional coordinators will be asked to provide electronic enrollment lists of all students enrolled during the academic year. Depending on the information provided from the IRP, the earliest enrollment lists will be due to RTI in late January. Since enrollment lists are collected for the entire academic year, January is the earliest enrollment lists can be collected. The lists will serve as the population from which the student sample will be drawn. Email prompts will be sent to institutional coordinators based on the customized schedule for each institution. A reminder letter directing institution coordinators to the website for complete instructions will be sent, typically three weeks prior to the deadline.

4.Tests of Procedures or Methods

There will be no tests of procedures or methods as part of the NPSAS:12 institution contacting, enrollment list collection, and list sampling.

5.Reviewing Statisticians and Individuals Responsible for Designing and Conducting the Study

Names of individuals consulted on statistical aspects of study design along with their affiliation and telephone numbers are provided below.

Name Affiliation Telephone Number

Dr. Jennifer Wine RTI 919-541-6870

Dr. James Chromy RTI 919-541-7019

Mr. Peter Siegel RTI 919-541-6348

Dr. Natasha Janson RTI 919-316-3394

Dr. John Riccobono RTI 919-541-7006

Dr. Alexandria Radford MPR 202-478-1027

Dr. Susan Choy MPR 510-849-4942

Ms. Christina Wei MPR 510-849-4942

Dr. Jennie Woo MPR 510-849-4942

In addition to these statisticians and survey design experts, the following statisticians at NCES have also reviewed and approved the statistical aspects of the study: Dr. Tom Weko, Dr. Tracy Hunt-White, Mr. Matthew Soldner, Dr. Sean Simone, and Mr. Ted Socha.

6.Other Contractors’ Staff Responsible for Conducting the Study

The study is being conducted by the Postsecondary, Adult, and Career Education (PACE) division of the National Center for Education Statistics (NCES), U.S. Department of Education. NCES’s prime contractor is the RTI International (RTI). RTI is being assisted through subcontracted activities by MPR Associates, Branch Associates, KForce Government Solutions, Inc. (KGS), Research Support Services, Millennium Services 2000+, Inc., and consultants. Principal professional staff of the contractors, not listed above, who are assigned to the study are identified below:

Name Affiliation

Mr. Jeff Franklin RTI

Ms. Christine Rasmussen RTI

Ms. Kristin Dudley RTI

Mr. Brian Kuhr RTI

Ms. Tiffany Mattox RTI

Dr. Cynthia Decker Consultant

Ms. Andrea Sykes Consultant

Mr. Dan Heffron KGS

Mr. Bart Ecker Millennium Services

Ms. Vicky Dingler MPR

Ms. Laura Horn MPR

Dr. Alisú Shoua-Glusberg RSS

1 A preliminary sampling frame has been created using IPEDS:2007-08 data, and frame counts in tables 1 and 2 are based on this preliminary frame. The frame will be re-created with more recent IPEDS data prior to sample selection.

2 The institutional strata can be aggregated by control or level of the institution for the purposes of reporting institution counts.

3 The Hispanic-serving institutions (HSI) indicator no longer exists in IPEDS, so an HSI proxy was created using IPEDS Hispanic enrollment data.

4 Some Carnegie categories were collapsed for the purposes of implicit stratification.

5 The expected 75 percent response rate is preliminary and may be adjusted in the student clearance package based on field test results.

6 A final decision has not yet been made regarding using a variable-based study member definition, pending the results of a current research study.

7 NPSAS has many administrative data sources, along with the student interview. Key variables have been identified across the various data sources to determine the minimum requirements to support the analytic needs of the study. Sample members who meet these minimum requirements will be classified as study members. These study members will have enough information from these multiple sources to be included in the NPSAS analysis files.

8 Past rounds of NPSAS have included samples of first-professional students. However, IPEDS is in the process of replacing the term first-professional with doctoral-professional practice. We will work with the sample institutions when requesting enrollment lists to ensure that they understand how to identify doctoral-research and doctoral-professional practice students.

9 “Other graduate” students are those who are not enrolled in a degree program, such as students just taking graduate courses.

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