BPS 2012-14 Field Test Appendixes A-G

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2012/14 Beginning Postsecondary Students Longitudinal Study: (BPS:12/14) Field Test

BPS 2012-14 Field Test Appendixes A-G

OMB: 1850-0631

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Appendix A
Linkages to Administrative Data Sources

A.1 Develop Linkages with Administrative Data Sources

We will develop linkages with existing data sources to supplement the Beginning Postsecondary Students Longitudinal Study (BPS:12/14) interview data. NCES recognizes the great value added to the BPS:12/14 data file with the addition of data from specific administrative data sources. Certain data (for example, specific financial aid amounts and associated dates) can only be accurately obtained from sources other than the student or parent. Through the experience of collecting data for many NCES postsecondary studies, including previous BPS studies, Baccalaureate and Beyond (B&B), and National Postsecondary Study Aid Study (NPSAS), a considerable knowledge has been gained in performing file merges with many existing sources of valuable data, including Department of Education’s (ED) Central Processing System (CPS) for Free Application for Federal Student Aid (FAFSA) data, the National Student Loan Data System (NSLDS), and ACT. For this study, we plan to perform file merges with the CPS and NSLDS datasets: CPS, NSLDS.

The Family Educational Rights and Privacy Act (FERPA; 34 CFR Part 99) allows the disclosure of information without prior consent for the purposes of BPS:12/14 according to the following excerpts: 99.31 asks “Under what conditions is prior consent not required to disclose information?” and explains in 99.31 (a) “an educational agency or institution may disclose personally identifiable information from an education record of a student without the consent required by 99.30 if the disclosure meets one or more specific conditions. BPS:12/14 collection falls under:

Sec. 99.31 (a)( 3). The disclosure is, subject to the requirements of Sec. 99.35, to authorized representatives of--

(i) The Comptroller General of the United States;

(ii) The Attorney General of the United States;

(iii) The Secretary; or

(iv) State and local educational authorities.

BPS:12/14 is collecting data under the Secretary’s authority. The personally identifiable information is collected from student record systems with adherence to the security protocol detailed in 99.35: “What conditions apply to disclosure of information for Federal or State program purposes?”

(a)(1) Authorized representatives of the officials or agencies headed by officials listed in Sec. 99.31(a)(3) may have access to education records in connection with an audit or evaluation of Federal or State supported education programs, or for the enforcement of or

compliance with Federal legal requirements that relate to those programs.

(2) Authority for an agency or official listed in Sec. 99.31(a)(3) to conduct an audit, evaluation, or compliance or enforcement activity is not conferred by the Act or this part and must be established under other Federal, State, or local authority.

(b) Information that is collected under paragraph (a) of this section must:

(1) Be protected in a manner that does not permit personal identification of individuals by anyone other than the officials or agencies headed by officials referred to in paragraph (a) of this section, except that those officials and agencies may make further disclosures of personally identifiable information from education records on behalf of the educational agency or institution in accordance with the requirements of Sec. 99.33(b); and

(2) Be destroyed when no longer needed for the purposes listed in paragraph (a) of this section.

(c) Paragraph (b) of this section does not apply if:

(1) The parent or eligible student has given written consent for the

disclosure under Sec. 99.30; or

(2) The collection of personally identifiable information is

specifically authorized by Federal law.

A.2 File Merge with ED Central Processing System (CPS)

We propose to perform file merges with the CPS data containing federal student aid application information. The merge with CPS can occur at any time for any number of cases, provided that the case has an apparently valid SSN associated with it. BPS contractor, RTI, will send a file to CPS and receive in return a large data file containing all students who applied for federal aid. The programs and procedures are already in place to prepare and submit files according to rigorous CPS standards. Similarly, programs and procedures to receive and process data obtained from CPS have also been developed.

RTI will electronically upload a file on the FAFSA secure web-site for matching. The file contains SSN and the first 2 letters of the sample member’s last name, but no other information. Access to the site for the upload is restricted to authorized users who are registered and provide identification/authentication information to the FAFSA data site. The file is retrieved by the Central Processing System or CPS (the FAFSA contractor data system) for linkage. The linked file, containing student aid applications for matched records, is then made available to RTI only through a secure connection (EdConnect) which requires username and password. All CPS files will be processed, edited, and documented for inclusion on the analytic data files. The CPS data will cover academic years beginning with 2012–2013. All CPS files will be processed, edited, and documented for inclusion in the Electronic Codebook (ECB).

A.3 File Merge with National Student Loan Data System Disbursement

RTI will also conduct a file merge with the NSLDS to collect federal loan and Pell grant data for the 2012-13 award year. The resulting file will contain cumulative amounts for each student’s entire postsecondary education enrollment. Files are transmitted using a secure connection (EdConnect) which requires username and password. Programs to create the files for the merge and also programs to read the received data already exist. All matching processes are initiated by RTI staff providing a file with one record per sample member to be merged.

Appendix B
Data Security Language for Vendor Contracts

Data Security Requirements

Contractor shall use data supplied to them by Company for the specific purpose included in the corresponding Statements of Work only.
Contractor will protect all data supplied to them by Company as specifically stated in Exhibit C, attached.
Unless otherwise agreed to, Contractor will promptly and properly destroy data supplied to them by Company upon the Statement of Work completion date.

EXHIBIT C

COMPANY INFORMATION SECURITY REQUIREMENTS

Definitions.

“Business Contact Information” is defined as name, job title, department name, company name, business telephone, business fax number, and business email address.

“COMPANY Confidential Information” as defined in the Agreement.

“Information Processing System(s)” is defined as the individual and collective electronic, mechanical, or software components of CONTRACTOR operations that store and/or process COMPANY Confidential Information.

“Information Security Event” is defined as any situation where COMPANY Confidential Information is lost; is subject to unauthorized or inappropriate access, use, or misuse; the security, confidentiality, or integrity of the information is compromised; or the availability of CONTRACTOR Information Processing Systems is compromised by external attack.

“Security Breach” is defined as an unauthorized access to CONTRACTOR’s facilities, Information Processing Systems or networks used to service, store, or access COMPANY Confidential Information, provided such unauthorized access exposes COMPANY Confidential Information or provided CONTRACTOR is required to report such unauthorized access to appropriate legal or regulatory agencies or affected COMPANY members.

“Industry best practice” is defined by the information security guidelines prepared by the PCI Security Standards Council and documented in the PCI DSS requirements as well as standards and guidelines prepared by the Federal Financial Institutions Examination Council (FFIEC)

Security and Confidentiality.

Before receiving, or continuing to receive, COMPANY Confidential Information, CONTRACTOR will implement and maintain an information security program that ensures: 1) COMPANY’s Confidential Information and CONTRACTOR’s Information Processing Systems are protected from internal and external security threats; and 2) that COMPANY Confidential Information is protected from unauthorized disclosure.

Security Policy.
1. Formal Security Policy. Consistent with the requirement of this Attachment, CONTRACTOR will create an information security policy that is approved by CONTRACTOR’s management, published and communicated to all CONTRACTOR’s employees. Such information security policy may be reviewed by COMPANY at CONTRACTOR’s place of business pursuant to confidentiality obligations.
2. Security Policy Review. CONTRACTOR will review the information security policy at planned intervals or if significant changes occur to ensure its continuing suitability, adequacy, and effectiveness.
Asset Management.
1. Asset Inventory. CONTRACTOR shall have the ability to identify the location of all CONTRACTOR Information Processing Systems and media containing COMPANY Confidential Information.
2. Acceptable Use. CONTRACTOR will implement rules for the acceptable use of information and assets which is no less restrictive than industry best practice and consistent with the requirements of this Attachment.
3. Equipment Use While on COMPANY Premises. While on COMPANY’s premises, CONTRACTOR will not connect hardware (physically or via a wireless connection) to COMPANY systems unless necessary for CONTRACTOR to perform Services under this Agreement. This hardware must be inspected / scanned by COMPANY before use.
4. Portable Devices. COMPANY Confidential Information, with the exception of Business Contact Information, may not be stored on portable devices including, but not limited to, laptops, external hard drives, Personal Digital Assistants, MP3 devices, and USB devices.
5. Personally-owned Equipment. COMPANY Confidential Information, with the exception of Business Contact Information, may not be stored on personally‑owned equipment.
Human Resources Security.
1. Security Awareness Training. Prior to CONTRACTOR employees receiving access to COMPANY Confidential Information, they will receive security awareness training appropriate to their job function. CONTRACTOR will also ensure that recurring security awareness training is performed.
2. Removal of access Rights. The access rights of all CONTRACTOR employees to CONTRACTOR Information Processing Systems or media containing COMPANY Confidential Information will be removed immediately upon termination of their employment, contract or agreement, or adjusted upon change.
Physical and Environmental Security.
1. Secure Areas. CONTRACTOR will secure all areas, including loading docks, holding areas, telecommunications areas, cabling areas and off-site areas that contain Information Processing Systems or media containing COMPANY Confidential Information by the use of appropriate security controls in order to ensure that only authorized personnel are allowed access and to prevent damage and interference. The following controls will be implemented:
  1. Access will be controlled and restricted by use of a defined security perimeter, appropriate security barriers, entry controls and authentication controls. A record of all accesses will be securely maintained.
  2. All personnel will be required to wear some form of visible identification to identify them as employees, contractors, visitors, et cetera.
  3. Visitors to secure areas will be supervised, or cleared for non-escorted accessed via an appropriate background check. Their date and time of entry and departure will be recorded.
2. Environmental Security. CONTRACTOR will protect equipment from power failures and other disruptions caused by failures in supporting utilities.
Communications and Operations Management.
1. Protections Against Malicious Code. CONTRACTOR will implement detection, prevention, and recovery controls to protect against malicious software, which is no less than current industry best practice and perform appropriate employee training on the prevention and detection of malicious software.
2. Back-ups. CONTRACTOR will perform appropriate back-ups of CONTRACTOR Information Processing Systems and media containing COMPANY Confidential Information as required in order to ensure services and service levels described in this Statement of Work.
3. Media and Information Handling. CONTRACTOR will protect against unauthorized access or misuse of COMPANY Confidential Information contained on media by use of a media control management program and provide a copy of the program to COMPANY.
  1. COMPANY input and result code data can be stored as Audit Data in a SQLServer table. All Audit Data on this SQLServer table can only be accessed for up to 180 days. After 180 days the Audit Data in the SQLServer table is automatically destroyed.
4. Media and Information Disposal. CONTRACTOR will securely and safely dispose of COMPANY Confidential Information that resides on media (including but not limited to hard copies, disks, CDs, DVDs, optical disks, USB devices, hard drives) upon the Statement of Work completion date using establishment of procedures to include, but not be limited to:
  1. Disposing of COMPANY Confidential Information on media so that it is rendered unreadable or undecipherable, such as by burning, shredding, pulverizing or overwriting in compliance with DoD Standard 5220.22-M.
  2. Maintaining a secured disposal log that provides an audit trail of disposal activities.
  3. Purging COMPANY Confidential Information from all CONTRACTOR’s physical storage mediums (filing cabinets, drawers, et cetera.) and from all Information Processing Systems, including back-up systems, within thirty (30) days of the latest occurrence of following: upon termination of this agreement; or as soon as the COMPANY Confidential Information is no longer required to perform services under this Statement of Work.
  4. Providing a Certificate of Destruction to COMPANY certifying that all COMPANY Confidential Information was purged. The certificate will be provided to COMPANY within ten (10) business days after the information was purged.
5. Exchange of Information. To protect confidentiality and integrity of COMPANY Confidential Information in transit, CONTRACTOR will:
  1. Perform an inventory, analysis and risk assessment of all data exchange channels (including but not limited to FTP, HTTP, HTTPS, SMTP, modem, and fax) to identify and mitigate risks to COMPANY Confidential Information from these channels.
  2. Monitor and inspect all data exchange channels to detect unauthorized information releases.
  3. Ensure that appropriate security controls using approved data exchange channels are employed when exchanging COMPANY Confidential Information.
  4. If COMPANY Confidential Information can only be sent to CONTRACTOR electronically, then CONTRACTOR must employ industry standard encryption security measures (minimum standard of NIST’s FIPS 140-2) to encrypt COMPANY Confidential Information prior to transmitting via the Internet. Otherwise, COMPANY Confidential Information can only be sent to CONTRACTOR using an encrypted (minimum standard NIST’s FIPS 140-2) CD-ROM sent via courier service with a tracking number.
  5. Ensure that information (including persistent cookies) about COMPANY customers, members or employees is not harvested by CONTRACTOR web pages except for purposes of this Agreement.
6. Monitoring. To protect against unauthorized access or misuse of COMPANY Confidential Information residing on CONTRACTOR Information Processing Systems, CONTRACTOR will:
  1. Employ current industry best practice security controls and tools to monitor Information Processing Systems and log user activities, exceptions, unauthorized information processing activities, suspicious activities and information security events. Logging facilities and log information will be protected against tampering and unauthorized access. Logs will be kept for at least 90 days.
  2. Perform frequent reviews of logs and take necessary actions to protect against unauthorized access or misuse of COMPANY Confidential Information.
  3. At COMPANY’s request, make logs available to COMPANY to assist in investigations of security breaches.
  4. Comply with all relevant legal requirements applicable to monitoring and logging activities.
  5. Ensure that the clocks of all relevant information processing systems are synchronized using a national or international time source.
Access Control.
1. User access Management. To protect against unauthorized access or misuse of COMPANY Confidential Information residing on CONTRACTOR Information Processing Systems, CONTRACTOR will:
  1. Employ a formal user registration and de-registration procedure for granting and revoking access and access rights to all CONTRACTOR Information Processing Systems.
  2. Employ a formal password management process.
  3. Perform recurring reviews of users’ access and access rights to ensure that they are appropriate for the users’ role.
2. User Responsibilities. To protect against unauthorized access or misuse of COMPANY Confidential Information residing on CONTRACTOR Information Processing Systems, CONTRACTOR will:
  1. Ensure that CONTRACTOR Information Processing Systems users follow current security practices in the selection and use of strong passwords.
  2. Ensure that unattended equipment has appropriate protection to prohibit access and use by unauthorized individuals.
  3. Ensure that COMPANY Confidential Information contained at workstations, including but not limited to paper and on display screens is protected from unauthorized access.
3. Network access Control. access to internal, external, and public network services that allow access to CONTRACTOR Information Processing Systems shall be controlled. CONTRACTOR will:
  1. Ensure that current industry best practice standard authentication mechanisms for network users and equipment are in place and updated as necessary.
  2. Ensure electronic perimeter controls are in place to protect CONTRACTOR Information Processing Systems from unauthorized access.
  3. Ensure authentication methods are used to control access by remote users.
  4. Ensure physical and logical access to diagnostic and configuration ports is controlled.
4. Operating System access Control. To protect against unauthorized access or misuse of COMPANY Confidential Information residing on CONTRACTOR Information Processing Systems, CONTRACTOR will:
  1. Ensure that access to operating systems is controlled by a secure log-on procedure.
  2. Ensure that CONTRACTOR Information Processing System users have a unique identifier (user ID).
  3. Ensure that the use of utility programs that are capable of overriding system and application controls are highly restricted and tightly controlled.
  4. Ensure that inactive sessions are shut down when technically possible after a defined period of inactivity.
  5. Employ restrictions on connection times when technically possible to provide additional security for high risk applications.
5. Mobile Computing and Remote Working. To protect COMPANY Confidential Information residing on CONTRACTOR Information Processing Systems from the risks inherent in mobile computing and remote working, CONTRACTOR will:
  1. Perform a risk assessment to identify and mitigate risks to COMPANY Confidential Information from residing on mobile computing and remote access systems.
  2. Develop a policy, operational plans and procedures for managing mobile computing and remote access systems to ensure that COMPANY Confidential Information does not reside on or are used on these systems.
Information Systems Acquisition, Development and Maintenance.
1. Security of System Files. To protect CONTRACTOR Information Processing Systems and system files containing COMPANY Confidential Information, CONTRACTOR will ensure that access to source code is restricted to authorized users who have a direct need to know.
2. Security in Development and Support Processes. To protect CONTRACTOR Information Processing Systems and system files containing COMPANY Confidential Information, CONTRACTOR will:
  1. Ensure that the implementation of changes is controlled by the use of formal change control procedures.
  2. Employ industry best practice security controls to minimize information leakage.
  3. Employ oversight quality controls and security management of outsourced software development.
Information Security Incident Management.

Reporting Information Security Events and Weaknesses. To protect CONTRACTOR Information Processing Systems and system files containing COMPANY Confidential Information, CONTRACTOR will, in the event that Contractor becomes aware of (or reasonably suspects) that any information and data obtained pursuant to the Services has been compromised in any manner, immediately notify Company via email or telephone call and follow-up on the incident in writing and provide all requested information about the event. For purposes of this obligation, “compromise” includes suspected or known incidents without limitation: (i) any unauthorized access to information and data obtained pursuant to the Services, (ii) any inadvertent disclosure of information and data obtained pursuant to the Services to any third party, (iii) any known or suspected misuse of information and data obtained pursuant to the Services by any person (even if such person was authorized to access such information or data), (iv) any suspected use of information and data obtained pursuant to the Services by any person outside of the scope of that person’s authority, and (v) any known or suspected alteration of information and data obtained pursuant to the Services other than as required or permitted by this Agreement.

Information Security Events and Security Breaches: Contractor shall
1. Implement a process to ensure that Information Security Events and Security Breaches are reported through appropriate management channels as quickly as possible.
2. Train all employees of information systems and services how to report any observed or suspected Information Security Events and Security Breaches.
3. Notify COMPANY by email (JDavismailto:@RTI.org or by phone (800-334‑8571) immediately of all suspected Information Security Events and Security Breaches. Following any such event or breach, CONTRACTOR will promptly notify COMPANY as to the COMPANY Confidential Information affected and the details of the event or breach.

Business Continuity Management.
1. Business Continuity Management Program. In order to ensure services and service levels described in this agreement, CONTRACTOR will:
  1. Develop and maintain a process for business continuity throughout the organization that addresses the information security requirements needed for the CONTRACTOR’s business continuity so that the provision of products and/or services provided under the Agreement to COMPANY is uninterrupted.
  2. Identify events that can cause interruptions to business processes, along with the probability and impact of such interruptions and their consequences for information security.
  3. Develop and implement plans to maintain or restore operations and ensure availability of information at the required level and in the required time scales following interruption to, or failure of, critical business processes and provide COMPANY a copy of the same.
  4. Test and update Business Continuity Plans regularly to ensure that they are up‑to-date and effective.
Security Assessments.
1. Initial and Recurring Security Assessments. CONTRACTOR will permit COMPANY representatives to perform an on-site physical and logical Security Assessment of CONTRACTOR’s data processing and business facilities prior to the release of COMPANY Confidential Information and each year thereafter. Security Assessments will be performed during regular business hours, at a date and time agreed to by both parties, and will not require online access to CONTRACTOR’s Information Processing Systems.
2. Security Assessments Following Information Security Events and Security Breaches. Following the occurrence of an Information Security Event or Security Breach, CONTRACTOR will permit COMPANY representatives to perform an on-site physical and logical Security Assessment of CONTRACTOR’s data processing and business facilities to assess the impact of the event or breach even if a Security Assessment has been completed within the year.
3. Security Assessment Findings. Upon completion of a Security Assessment, COMPANY will provide CONTRACTOR with a Security Assessment completion letter that summarizes COMPANY’s Security Assessment findings. These findings may identify critical security deficiencies identified as “Mandatory” that require immediate correction before COMPANY can release, or continue to release, COMPANY Confidential Information to CONTRACTOR. CONTRACTOR will implement and continue to maintain all mutually agreed upon “Mandatory” security findings. If mutual agreement to “Mandatory” security findings cannot be reached, then these issues may be escalated using the dispute resolution provisions within this Agreement

Appendix C
Full-scale Sampling Specifications

Introduction

For the NPSAS:12 sample design and selection, the following 5-step cost/variance optimization process was used:

Establish precision requirements for key estimates.
Develop institution and student sampling strata to support the key estimates.
Develop a cost model.
Develop a relative variance model.
Determine the optimum sample allocation.

Precision Requirements

The precision goal for NPSAS:12 was to achieve relative standard errors (RSEs) of 10 percent or less and comparable to or less than NPSAS:08 for key national estimates for the full population, undergraduate students, and graduate students. The key estimates are based on acquired knowledge of the NPSAS data, how the data will be used for analysis, and what data are most important. An additional precision goal for NPSAS:12 was to achieve RSEs of 10 percent or less and comparable to or less than NPSAS:04 for key national estimates for first-time beginners (FTBs). The appropriate outcomes and domains, for which precision constraints will be developed for FTBs, were determined from field test results testing new FTB items.

3. Institution Frame and Sample Selection

To be eligible for NPSAS:12 an institution was 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 were excluded. U.S. Service Academies were also excluded because of their unique funding/tuition base.

The NPSAS:12 full-scale institution sampling frame was constructed during the field test from the IPEDS:2008–09 header, Institutional Characteristics (IC), 12-Month and Fall Enrollment, and Completions files. In order to guarantee complete data for the frame, data were imputed using the latest IPEDS imputation procedures for the small number of institutions with missing enrollment information.

As discussed earlier in the supporting materials for the forms clearance package, the NPSAS:12 field test institution sample was selected statistically, rather than purposively as had been done in past NPSAS cycles. A statistical sample would provide more control to ensure that the field test and the full-scale institution samples have similar characteristics, and would 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 comprised the full-scale sample. Figure 1 displays the flow of institution sampling activities.

Figure 1. NPSAS:12 institution sample flow

Institutions for the initial sample were selected 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 has been 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 and Fall Enrollment Components. Using composite measure of size sampling ensured that target sample sizes would be achieved within institution and student sampling strata while also achieving approximately equal student weights across institutions.

The institution sample was freshened in order to add newly eligible institutions to the sample and produce a sample that is representative of institutions eligible in the 2011-2012 academic year. To do this, the IPEDS:200910 header, Institutional Characteristics (IC), 12-Month and Fall Enrollment, and Completions files were used to create an updated sampling frame of currently NPSAS-eligible institutions. This frame was then compared with the original frame, and 387 new or newly eligible institutions were identified. These 387 institutions make up the freshening sampling frame. The freshening sample size was then determined such that the freshened institutions would have similar probabilities of selection to the originally selected institutions within sector (stratum) in order to minimize unequal weights and subsequently variances; 21 freshened institutions were selected.

The 10 institutional strata used for NPSAS:12 were based on institutional level, control, and highest level of offering:¹

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 nonprofit less-than-4-year

6. private nonprofit 4-year non-doctorate-granting

7. private nonprofit 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, for NPSAS:12 the two were split into separate strata to reflect the recent growth in enrollment in for-profit 4-year institutions.

When data collection is complete, an overall 99 percent eligibility rate among sampled institutions should be reached. 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 institution sample sizes and estimated sample yield by the ten institutional strata are presented in table 1.

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 (HBCU) indicator; (2) Hispanic-serving institutions (HSI) indicator² (3) Carnegie classifications of postsecondary institutions;³ (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 1. NPSAS:12 full-scale institution sample sizes and estimated yield

Institutional sector	Frame count¹	Number sampled	Number eligible	List respondents
Total	7,052	1,692	1,672	1,416

Public
Less-than 2-year	271	22	19	14
2-year	1,108	381	381	335
4-year non-doctorate-granting	356	130	130	117
4-year doctorate-granting	309	230	230	200

Private
Nonprofit less-than-4-year	263	20	20	17
Nonprofit 4-year non-doctorate-granting	1,031	260	260	218
Nonprofit 4-year doctorate-granting	555	221	221	183
For-profit less-than-2-year	1,513	55	52	41
For-profit 2-year	1,028	115	111	90
For-profit 4-year	618	258	248	201

¹Institution counts based on IPEDS:2008-09 and IPEDS:2009-10 header files.

Table 2. NPSAS:12 preliminary student sample sizes and yield

Institutional sector	Sample students				Eligible students				Interview Respondents				Responding students per responding institution
Institutional sector	Total	FTBs	Other undergraduate Students	Graduate students	Total	FTBs	Other undergraduate students	Graduate students	Total	FTBs	Other undergraduate students	Graduate students	Responding students per responding institution
Total	124,644	45,413	63,497	15,735	118,748	43,068	60,396	15,283	83,124	31,045	41,746	10,333	59

Public
Less-than 2-year	1,279	717	563	0	1,036	580	456	0	623	366	257	0	45
2-year	41,304	14,822	26,483	0	38,693	13,885	24,808	0	26,235	10,013	16,223	0	78
4-year non-doctorate-granting	8,288	1,954	4,962	1,372	8,115	1,913	4,858	1,344	6,095	1,553	3,809	733	52
4-year doctorate-granting	20,057	3,864	11,182	5,012	19,728	3,800	10,998	4,930	15,226	3,155	8,585	3,486	76

Private nonprofit
Less-than-4-year	1,646	937	709	0	1,484	844	639	0	811	486	325	0	48
4-year non-doctorate-granting	8,311	2,250	3,458	2,604	8,116	2,195	3,378	2,543	6,334	1,906	2,732	1,696	29
4-year doctorate-granting	8,770	2,100	1,733	4,937	8,509	2,080	1,692	4,736	6,451	1,703	1,410	3,338	35

Private for-profit
Less-than-2-year	5,472	3,074	2,398	0	4,720	2,651	2,068	0	2,407	1,430	977	0	59
2 year	10,849	5,971	4,878	0	10,408	5,728	4,680	0	7,004	4,028	2,976	0	78
4 year	18,668	9,726	7,131	1,810	17,938	9,391	6,817	1,730	11,938	6,406	4,452	1,080	59

NOTE: FTB = first time beginner. Detail may not sum to totals due to rounding.

4. Student Sample Design and Selection

The students eligible for inclusion in the sample were 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 were:

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.

The following section describes the student sample design, including plans for sampling students from enrollment lists.

Based on past experience, a minimum of a 95 percent student eligibility rate and an overall 70 percent student interview response rate are expected. The preliminary sample sizes and sample yield are presented in table 2. As indicated in the table, the sample was designed to include about 117,000 students. The distribution of the sample by institution and student strata will be finalized after completion of the sample optimization process.

Several student subgroups were intentionally sampled at rates different than their natural occurrence within the population due to specific analytic objectives. Two groups were oversampled to better understand their unique experiences within postsecondary education. Specifically:

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
FTB 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 a sufficient starting sample is identified.

Similarly, two students groups were undersampled: graduate students in business and graduate students in 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 were oversampled.

Potential FTBs will be identified 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 were adjusted based on field test interview and pre-sampling matching results (see below), as well as on results from both NPSAS:04 and BPS:04/06, to yield appropriate sample sizes after accounting for expected false positive and false negative rates by sector

The eleven student sampling strata are:

first-time beginning undergraduate students enrolled in sub-baccalaureate programs
other first-time beginning undergraduate students
other undergraduate students
master’s degree students in STEM programs
master’s degree students in education and business programs
master’s degree students in other programs
doctoral-research/scholarship/other students in STEM programs
doctoral-research/scholarship/other students in education and business programs
doctoral-research/scholarship/other students in other programs
doctoral-professional practice students⁴
other graduate students⁵

As part of the cost/variance optimization process, it was determined that there is sufficient sample for the graduate student strata.⁶ The sample size for graduate students was increased to help offset the increased design effect and variance for analyses of all graduate students.

As was done in past rounds of NPSAS, the eleven student strata were 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.

A variable-based (rather than source-based) definition of a study member will be used, like that used in NPSAS:04 and NPSAS:08, updated by changes to the interview. 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;
first-time beginner (FTB) status;
months enrolled;
tuition;
received federal aid;
received non-federal aid;
student budget;
race; and
parent education.

The rate of study membership is expected to be about 90 percent.⁷

Creating student sampling frames. Sample institutions were asked to provide an electronic student enrollment list. The following data items were 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)
First-time beginner (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)

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

The FTB indicator, student level, class level, and date of birth were 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 the feasibility of this request was tested in the field test. About 80 percent 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 not FTBs and 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 STEM majors who were not SMART grant recipients. For NPSAS:12, in order to appropriately undersample business and education graduate students and oversample graduate students in STEM fields, CIP code and major were collected on lists. Schools were also asked to provide degree program for use in identifying FTBs in sub-baccalaureate programs, as described above.

The field test included 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, was not requested in the full-scale study.

Obtaining student enrollment lists. To ensure the secure transmission of sensitive information on the enrollment lists, the following options were provided 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, few institutions were expected to ask to provide a paper list. However, in the event that an institution was unable to transmit data via the secure electronic methods of transmission outlined above, faxes sent to a secure electronic fax machine could be accepted.

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.

Several steps were taken early in the NPSAS:12 listing and sampling processes to improve the rate at which FTBs would be correctly classified for sampling. First, in addition to an FTB indicator, enrollment lists provided by institutions and institution systems were to 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, were not 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 were also not eligible for sampling. If the FTB indicator was not provided for a student on the list, but the student was 18 years old or younger and did not appear to be dually enrolled, the student was classified as an FTB for sampling. Otherwise, if the FTB indicator was not provided for a student on the list and the student was over the age of 18, then the student was sampled as an “other undergraduate,” but will be added to the BPS cohort if identified during the interview as an FTB.

Second, prior to sampling, all students listed as potential FTBs were matched 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, 2011). Since NSLDS maintains current records of all Title IV grant and loan funding, any students with data showing disbursements from prior years could 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. All potential FTBs were sent to NSLDS because ten percent of students aged 18 and younger, sampled as FTBs, and interviewed in the field test were not FTBs (false positives). 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 RTI in one day.

Third, simultaneously with NSLDS matching, all potential FTBs were matched to the Central Processing System (CPS) to identify students who on their FAFSA indicated that they had attended college previously. In the field test, this process for identifying potential FTBs from a subset of 94 institutions, mainly public and private nonprofit institutions, was evaluated and an additional 2.4 percent of false positives was found from the initial pool of potential FTBs who were not identified as such by NSLDS and NSC. CPS has an automated, free process for matching that has been 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.

Fourth, after NSLDS and CPS matching, a subset of the remaining potential FTBs was matched to the National Student Clearinghouse (NSC) for further narrowing of FTBs based on the presence of evidence of earlier enrollment. In the field test, matching to NSC identified about 14 percent of the remaining potential FTBs, after NSLDS matching, as false positives. NSC worked with RTI to set up a process that can handle a large number of potential FTBs and return FTB lists to RTI within two or three days. There is a “charge per case matched” for NSC matching, so an approach targeting potential FTBs over the age of 18 in the public 2-year and for-profit sectors was used. These sectors tended to have high false-positive rates in the field test and in NPSAS:04, and have large full-scale sample sizes.

Fifth, the FTB selection rates set took into account error rates observed in the NPSAS:12 field test, in NPSAS:04, and in BPS:04/06, and the expected pre-sampling matching results, within each sector, as described above. As shown in table 3, some NPSAS:04 institution sectors were better able to accurately identify their students as FTBs. While the sample selection rates took into account false positive rates, the NSLDS, CPS, and NSC record matches should result in improved accuracy. Table 4 shows the field test false positive identification from NSLDS, NSC, CPS, and overall matching, as well as from the interview, by sector.

Table 3. 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 nonprofit
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 4. Unweighted false positive rate observed in FTB identification from NSLDS, NSC, CPS, and overall matching and from the interview, by sector: NPSAS:12 field test

Sector in NPSAS:12	False positive rate (unweighted)
Sector in NPSAS:12	NSLDS	NSC	CPS	Overall matching	Interview

All institutions	19.2	14.1	10.2	32.1	18.2
Public
Less-than 2-year	29.8	29.1	0	50.2	53.8
2-year	22.0	13.7	14.9	34.9	18.1
4-year non-doctorate-granting	6.7	7.0	9.5	15.6	8.4
4-year doctorate-granting	4.2	13.0	6.4	18.2	6.4

Private nonprofit
Less-than-4-year	8.7	16.3	14.0	26.3	24.1
4-year non-doctorate-granting	20.1	12.3	6.0	31.2	10.4
4-year doctorate-granting	13.0	14.1	8.4	26.3	7.9

Private for-profit
Less-than-2-year	33.6	25.4	0	50.4	18.8
2 year	25.5	20.8	0	41.0	44.4
4-year	48.4	22.7	9.1	60.2	28.6

FTB = first time beginner.

Quality control checks for lists. Several checks on the quality and completeness of student lists were implemented before the sample students were selected. For example, the lists failed quality control checks if student level and/or the FTB indicator were not included on the list. Additionally, the unduplicated total of students at the undergraduate and graduate levels on each institution’s student list was checked against the latest IPEDS unduplicated enrollment data from the 12-Month Enrollment Component. The unduplicated count of FTBs on each institution’s student list was checked against IPEDS enrollment data from the Fall Enrollment Component adjusted to estimate full year enrollment. Contact information was checked carefully for each enrollment list as well as for each student sampled. If an institution did not provide high school graduation date, but included many students who were less than 18, the list failed quality control checks because it could erroneously contain high school students.

Institutions failing quality control checks were re-contacted to resolve the discrepancy and verify that the institution coordinator who prepared the student list(s) clearly understood the request being made and provided a list of the appropriate students. When it was determined that the initial list provided by an institution was not satisfactory, a replacement list was requested. Sample students were selected once it was either confirmed that the list received was correct or a corrected list was received. If the list was incorrect, but the institution would not or could not correct it, a determination was made as to whether or not sample selection could proceed depending on the severity of the problem.

Selection of sample students. Students were sampled on a flow basis, as student lists were received, using a stratified systematic sampling procedure. Sample yield was monitored by institution and student sampling strata, and the sampling rates were adjusted, as necessary, to achieve the desired sample yield.

Quality control checks for sampling. RTI has developed technical operating procedures (TOPs) that describe how to properly implement statistical procedures and QC checks. A checklist is available to all NPSAS:12 statisticians to ensure that appropriate QC checks were performed.

Some specific sampling QC checks will include 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.

5. Cost/Variance Optimization

A cost/variance optimization procedure developed by Chromy⁸ was used to determine the sample size distribution across institution and student strata that minimized data collection costs and the variance of estimates of key outcomes. The first step was to set the precision constraints to be the levels of precision achieved in NPSAS:08 (and NPSAS:04 for BPS estimates) for each domain and outcome that drives the sample design. This produced sample sizes that were comparable to those achieved in past studies. A 10 percent level of precision was imposed for some domains where historical levels of precision were higher than 10 percent. The sample sizes and yield presented in table 2 are based on the preliminary optimal allocation that did not yet include domains and outcomes for FTBs.

Appendix D
Bibliography of Publications Using BPS Data

Bibliography of Publications Using BPS Data
Arranged alphabetically by year

National Center for Education Statistics (NCES) publication numbers are indicated in brackets. Publications with an NCES number may be accessed from http://nces.ed.gov.

2012

Mamiseishvili, K. (2012). Academic and Social Integration and Persistence of International Students at U.S. Two-Year Institutions. Community College Journal of Research and Practice, 36(1), 15-27.

2011

Alon, S. (2011). Who Benefits Most from Financial Aid? The Heterogeneous Effect of Need-Based Grants on Students’ College Persistence. Social Science Quarterly, 92(3), 807-829.

Alon, S. & Gelbgiser, D. (2011). The Female Advantage in College Academic Achievements and Horizontal Sex Segregation. Social Science Research. 40(1). 107-119.

Attewell, P., Heil, S, & Reisel, L. Competing Explanations of Undergraduate Noncompletion. American Educational Research Journal, 48(3), 536-559.

Doyle, W. R. (2011). Effect of Increased Academic Momentum on Transfer Rates: An Application of the Generalized Propensity Score. Economics of Education Review, 30(1), 191-200.

Hinrichs, P. (2011). The Effects of Attending a Diverse College. Economics of Education Review, 30(2), 332-341.

Ho, P. & Chang Wei, C. (2011). Trends in Attainment Among Student Populations at Increased Risk of Noncompletion: Selected Years, 1989–90 to 2008–09. (NCES 2012-254). Washington, DC: National Center for Education Statistics.

Horn, L. & Skomsvold, P. (2011). Community College Student Outcomes: 1994-2009. (NCES 2012-253). Washington, DC: National Center for Education Statistics.

Mamiseishvili, K. (2011, September 13). International student persistence in U.S. postsecondary institutions. Higher Education.

Mamiseishvili, K. & Koch, L.C. (2011). First-to-Second-Year Persistence of Students with Disabilities in Postsecondary Institutions in the United States. Rehabilitation Counseling Bulletin. 54(2): 93-105.

McKean, J.R. (2011). First-time Beginning Student Attainment: Examining the Role of Distance Education. Unpublished Ph.D. dissertation, Ohio University.

Radford, A.W. (2011). Military Service Members and Veterans: A Profile of Those Enrolled in Undergraduate and Graduate Education in 2007–08. (NCES 2011-163). Washington, DC: National Center for Education Statistics.

Settle, J.S. (2011). Variables that Encourage Students to Persist in Community Colleges. Community College Journal of Research and Practice, 35(4), 281-300.

Skomsvold, P., Radford, A.W., & Berkner, L. (2011). Web Tables—Six-Year Attainment, Persistence, Transfer, Retention, and Withdrawal Rates of Students Who Began Postsecondary Education in 2003-04. (NCES 2011-152). Washington, DC: National Center for Education Statistics

Soldner, M.E. (2011). Persistence and Attainment among Pell Grant Recipients: Results from the Beginning Postsecondary Students Longitudinal Study of 2004/09. (NCES 2011-275). Washington, DC: National Center for Education Statistics.

Staklis, S., Bersudskaya, V., & Horn, L. (2011). Students Attending For-Profit Postsecondary Institutions: Demographics, Enrollment Characteristics, and 6-Year Outcomes. (NCES 2012-173). Washington, DC: National Center for Education Statistics.

Wine, J., Janson, N., & Wheeless, S. (2011). 2004/09 Beginning Postsecondary Students Longitudinal Study (BPS:04/09) Methodology Report. (NCES 2012-246). Washington, DC: National Center for Education Statistics.

2010

Camp, A. G., Gilleland, D. S., Pearson, C., & Putten, J. V. (2010). Differentiating between Women in Hard and Soft Science and Engineering Disciplines. Journal of College Student Retention: Research, Theory & Practice, 11(3): 363-384.

Chen, R., & DesJardins, S. L. (2010). Investigating the Impact of Financial Aid on Student Dropout Risks: Racial and Ethnic Differences. Journal of Higher Education, 81(2): 179-208.

Crisp, G., and Nora, A. (2010). Hispanic Student Success: Factors Influencing the Persistence and Transfer Decisions of Latino Community College Students Enrolled in Developmental Education. Research in Higher Education, 51(2): 175-194.

Griffith, J. (2010). Community Service Among a Panel of Beginning College Students: Its Prevalence and Relationship to Having Been Required and to Supporting “Capital.” Nonprofit and Voluntary Sector Quarterly, 39(5): 884-900.

Hornak, A.M, Farrell, P.L., and Jackson, N.L. Making It (or Not) on a Dime in College: Implications for Practice. (2010). Journal of College Student Development, 51(5): 481-495.

Li, D. (2010). They Need Help: Transfer Students from Four-Year to Four-Year Institutions. The Review of Higher Education, 33(2): 207-238.

Mamiseishvili, K. (2010). Effects of Employment on Persistence of Low-income, First-Generation College Students. College Student Affairs Journal, 29(1), 65-74, 93.

Museus, S. D. (2010). Understanding Racial Differences in the Effects of Loans on Degree Attainment: A Path Analysis. Journal of College Student Retention: Research, Theory & Practice, 11(4), 499-527.

Radford, A., Berkner, L., Wheeless, S. C., & Shepherd, B. (2010). Persistence and Attainment of 2003-04 Beginning Postsecondary Students: After 6 Years. First Look (NCES 2011-151). Washington, DC: National Center for Education Statistics.

Settle, J. S. (2011). Variables that Encourage Students to Persist in Community Colleges. Community College Journal of Research and Practice, 35(4), 281-300.

2009

Camp, A., Gilleland, D., Pearson, C., and Putten, J.V. (2009). Women's path into science and engineering majors: a structural equation model. Educational Research & Evaluation, 15(1): 63-77.

Camp, A.G., Gilleland, D.S., Pearson, C., and Putten, J.V. (2009). Differentiating between Women in Hard and Soft Science and Engineering Disciplines. Journal of College Student Retention, 11(3): 363-384.

Chen, X. (2009). Students Who Study Science, Technology, Engineering, and Mathematics (STEM) in Postsecondary Education (2009-161). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Choy, S.P., Berkner, L., Lee, J., and Topper, A. (2009). Academic Competitiveness and SMART Grant Programs: First-Year Lessons Learned. Washington, DC: U.S. Department of Education

Cragg, K.M. (2009). Influencing the Probability for Graduation at Four-Year Institutions: A Multi-Model Analysis. Research in Higher Education, 50(4): 394-413.

Doyle, W. (2009). The effect of community college enrollment on bachelor's degree completion. Economics of Education Review, 28(2): 199-206.

Horn, L. (2009). On Track to Complete? A Taxonomy of Beginning Community College Students and Their Outcomes 3 Years After Enrolling: 2003-04 through 2006 (NCES 2009-152). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Radford, A. (2009, July). Military Service Members and Veterans in Higher Education: What the New GI Bill May Mean for Postsecondary Institutions. Washington, DC: American Council on Education.

Radford, A., and Tasoff, S. (2009, July). Web Tables: Choosing a Postsecondary Institution: Considerations Reported by Students (NCES 2009-186). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Radford, A., and Wun, J. (2009, April). Issue Tables: A Profile of Military Service members and Veterans Enrolled in Postsecondary Education in 2007-08 (NCES 2009-182). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Snyder, T.D., Dillow, S.A., and Hoffman, C.M. (2009, March). Digest of Education Statistics, 2008 (NCES 2009-020). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Wine, J., Cominole, M., and Caves, L. (2009, June). 2004/09 Beginning Postsecondary Students Longitudinal Study (BPS:04/09) Field Test (NCES 2009-01). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

2008

Berkner, L., and Choy, S. (2008). Descriptive Summary of 2003-04 Beginning Postsecondary Students: Three Years Later (NCES 2008-174). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.’

Provasnik, S., and Planty, M. (2008, August). Community Colleges: Special Supplement to The 2008 Condition of Education (NCES 2008-033). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Stratton, L.S., O’Toole, D.M., and Wetzel, J.N. (2008, June). A Multinomial Logit Model of College Stopout and Dropout Behavior. Economics of Education Review, 27(3): 319-331.

2007

Berkner, L., He, S., Mason, M., and Wheeless, S. (2007). Persistence and Attainment of 2003-04 Beginning Postsecondary Students: After Three Years (NCES 2007-169). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Chen, X. (2007). Part-Time Undergraduates in Postsecondary Education: 2003–04 (NCES 2007-165). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Cominole, M., Wheeless, S., Dudley, K., Franklin, J., and Wine, J. (2007). 2004/06 Beginning Postsecondary Students Longitudinal Study (BPS:04/06) Methodology Report (NCES 2008-184). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Dongbin, K. (2007). The Effect of Loans on Students' Degree Attainment: Differences by Student and Institutional Characteristics. Harvard Educational Review, 77(1): 64-100.

Goan, S.K., and Cunningham, A.F. (2007). Differential Characteristics of 2-Year Postsecondary Institutions (NCES 2007-164rev). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Hudson, L., Kienzl, G., and Diehl, J. (2007). Students Entering and Leaving Postsecondary Occupational Education: 1995-2001. (NCES 2007-041). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Hunt-White, T. (2007). 2004/06 Beginning Postsecondary Students Longitudinal Study Data Analysis System (NCES 2007-185). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

2006

Anderson, G. (2006). Effectiveness of Statewide Articulation Agreements on the Probability of Transfer: A Preliminary Policy Analysis. The Review of Higher Education, 29(3): 261-291.

Blecher, L. (2006). Persistence toward Bachelor Degree Completion of Students in Family and Consumer Sciences. College Student Journal, 40(3):469-484.

Dougherty, K.J., and Kienzl, G.S. (2006). It's Not Enough to Get Through the Open Door: Inequalities by Social Background in Transfer from Community Colleges to Four-Year Colleges. Teachers College Record, 108(3): 452-487.

Dowd, A. and Coury, T. (2006). The Effect of Loans on the Persistence and Attainment of Community College Students. Research in Higher Education, 47(1): 33-62.

Flowers, L.A. (2006). Effects of Attending a 2-Year Institution on African American Males’ Academic and Social Integration in the First Year of College. Teachers College Record, 108(2): 267-286. [EJ733278]

Horn, L. (2006). Placing College Graduation Rates in Context: How 4-Year College Graduation Rates Vary With Selectivity and the Size of Low-Income Enrollment (NCES 2007-161). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Murphy, K. (2006). Factors Affecting the Retention, Persistence, and Attainment of Undergraduate Students at Public Urban Four Year Higher Education Institutions. Washington, DC: AIR.

Person, A., and Rosenbaum, J. (2006). Educational Outcomes of Labor-Market Linking and Job Placement for Students at Public and Private 2-Year Colleges. Economics of Education Review, 25(4): 412-429.

Titus, M.A. (2006). No College Student Left Behind: The Influence of Financial Aspects of a State's Higher Education Policy on College Completion. The Review of Higher Education, 29(3): 293-317.

Titus, M.A. (2006). Understanding the Influence of the Financial Context of Institutions on Student Persistence at Four-Year Colleges and Universities. The Journal of Higher Education, 77(2): 353-375.

Wine, J., Cominole, M., Wheeless, S., Bryant, A., Gilligan, T., Dudley, K., and Franklin, J. (2006). 2004/06 Beginning Postsecondary Students Longitudinal Study (BPS:04/06) Field Test Methodology Report (NCES 2006-01). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington.

2005

Adelman, C. (2005). Moving into Town--and Moving On: The Community College in the Lives of Traditional-Age Students. Office of Vocational and Adult Education. Washington, DC.

Alfonso, M., Bailey, T.R., and Scott, M. (2005). The Educational Outcomes of Occupational Sub-Baccalaureate Students: Evidence from the 1990s. Economics of Education Review, 24(2): 197-212.

Bailey, T., Jenkins, D., and Leinbach, T. (2005). What We Know about Community College Low-Income and Minority Student Outcomes: Descriptive Statistics from National Surveys. New York, NY: Community College Research Center.

Glenn, D. (2005, September 2). Sociologists Debate Degrees, Dropouts, and Faculty Beliefs. Chronicle of Higher Education, p. A24–A25.

Horn, L., Cataldi, E., and Sikora, A. (2005). Waiting to Attend College: Undergraduates Who Delay Their Postsecondary Enrollment (NCES 2005-152). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Leppel, K. (2005). College Persistence and Student Attitudes Toward Financial Success. College Student Journal, 39(2): 223–241.

Lohfink, M.M., and Paulsen, M.B. (2005). Comparing the Determinants of Persistence for First-Generation and Continuing-Generation Students. Journal of College Student Development, 46(4): 409–428.

Peter, K., and Cataldi, E. (2005). The Road Less Traveled? Students Who Enroll in Multiple Institutions (NCES 2005-157). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Peter, K., and Horn, L. (2005). Gender Differences in Participation and Completion of Undergraduate Education and How They Have Changed Over Time (NCES 2005-169). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Schuetz, P. (2005). UCLA community college review: campus environment: a missing link in studies of community college attrition. Community College Review, 32(4): 60–80.

2004

Bauer, C.J. (2004). The nexus between community college choice and student persistence. Unpublished Ph.D. dissertation, University of Missouri, Saint Louis

Borden, V.M.H. (2004). Accommodating student swirl: when traditional students are no longer the tradition. Change, 36(2): 10–17. [EJ701873]

Boswell, K. (2004). Bridges or barriers? Public Policy and the community college transfer function. Change, 36(6): 22–29. [EJ708608]

Brothen, T., and Wambach, C.A. (2004). Refocusing Developmental Education. Journal of Developmental Education, 28(2): 16–33.

Duggan, M.B. (2004). E-Mail as Social Capital and Its Impact on First-Year Persistence of 4-Year College Students. Journal of College Student Retention Research Theory and Practice, 6(2): 169–189. [EJ683627]

Ferris, E., Finster, M., McDonald, D. (2004). Academic Fit of Student-Athletes: An Analysis of NCAA Division I-A Graduation Rates. Research in Higher Education, 45(6): 555–575.

Hahs-Vaughn, D. (2004). The Impact of Parents' Education Level on College Students: An Analysis Using the Beginning Postsecondary Students Longitudinal Study 1990-92/94. Journal of College Student Development, 45(5): 483-500.

Horn, L., and Berger, R. (2004). College Persistence on the Rise? Changes in 5-Year Degree Completion and Postsecondary Persistence Rates Between 1994 and 2000 (NCES 2005-156). National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. Washington, DC.

Kane, M.A., Beals, C., Valeau, E.J., Johnson, M.J. (2004). Fostering Success Among Traditionally Underrepresented Student Groups: Hartnell College’s Approach to Implementation of the Math, Engineering, and Science Achievement (MESA) Program. Community College Journal of Research and Practice, 28(1): 17–26.

Kim, M.H. (2004). The determinants of institutional financial aid and its effect on degree completion: the difference between students at public and private four-year institutions. Ph.D. dissertation Columbia University.

Long, A.C. (2004). Community college attrition of GED certificate holders and regular high school graduates: A comparative study using national BPS data. Unpublished Ph.D. dissertation, Oregon State University

Pascarella, E.T. (2004). First-Generation College Students: Additional Evidence on College Experiences and Outcomes. The Journal of Higher Education, 75(3): 249-284.

Pascarella, E.T. (2004). The Role of Race in the Development of Plans for a Graduate Degree"
The Review of Higher Education, 27(3): 299-320.

Persell, C.H., and Wenglinsky, H. (2004). For-profit post-secondary education and civic engagement. Higher education, 47(2): 337–360.

Saunders, K.P. (2004). Degree attainment of low-socioeconomic status students: Structural equation modeling test of an elaborated theory of socialization. Unpublished Ph.D. dissertation, Iowa State University

Wassmer, R., Moore, C., and Shulock, N. (2004). Effect of Racial/Ethnic Composition on Transfer Rates in Community Colleges: Implications for Policy and Practice. Research in Higher Education, 45(6): 651–672.

2003

Alfonso, M., Bailey, T.R., and Scott, M. (2003, April). The Educational Outcomes of Occupational Sub-Baccalaureate Students: Evidence from the 1990s. Paper presented at the annual meeting of the American Educational Research Association, Chicago, IL. [ED481031]

Ashby, C. M. College completion: Additional efforts could help education with its completion goals. General Accounting Office (GAO-03-568). Washington, DC.

Below, D.L. “The first-to-second-year persistence of public, four-year college students by ethnicity.” (Ph.D. dissertation, University of Missouri, Saint Louis, 2003).

Berkner, L., He, S., and Cataldi, E. F. Descriptive summary of 1995-96 beginning postsecondary students: Six years later. Education Statistics Quarterly, 5(1): 62–67.

Freeman, T.L.(2003). Theoretical model for studying year-to-year persistence of two-year college students by ethnicity using the Beginning Postsecondary Students Longitudinal Study, 1996—1998. Ph.D. dissertation, University of Missouri, Saint Louis.

Hahs, D. L. (2003). The utilization of sample weights in structural equation modeling: An application using the beginning postsecondary students longitudinal study 1990/92/94. Ph.D. dissertation, University of Alabama.

Hoachlander, G., Sikora, A. C., and Horn, L. (2003). Community college students: Goals, academic preparation, and outcomes. (NCES 2003-164) U.S. Department of Education. Washington, DC: National Center for Education Statistics. Postsecondary education descriptive analysis reports, Statistical Analysis Report.

Horn, L., and Berker, A. (2004). Work First, Study Second: Adult Undergraduates Who Combine Employment and Postsecondary Enrollment. Education Statistics Quarterly, 5(3): 59–66.

Horn, L., and Peter, K. (2003). What colleges contribute: Institutional aid to full-time undergraduates attending 4-year colleges and universities. (NCES 2003–157) U.S. Department of Education. Washington, DC: National Center for Education Statistics. Postsecondary education descriptive analysis reports, Statistical Analysis Report.

Kim, D. (2003). Multilevel analysis of the effect of loans on degree attainment: differences by race, SES, and college characteristics. Ph.D. dissertation, University of California, Los Angeles.

O'Toole, D.M., Stratton, L.S., and Wetzel, J.N. (2003). A longitudinal analysis of the frequency of part-time enrollment and the persistence of students who enroll part time. Research in Higher Education, 44(5): 519–537.

Perez, N.M. (2003). Factors associated with the college success of Hispanic women: A mixed methods investigation. Ed.D. Dissertation, Texas A&M University, Corpus Christi.

Rosenfield, E.D. (2003). A demographic profile of single-mother college students and an examination of factors that influence their persistence. Ed.D. Dissertation, University of Rochester.

Titus, M.A. (2003). An examination of the influence of institutional context on persistence at four-year colleges and universities: A multilevel approach. Ph.D. dissertation, University of Maryland, College Park.

Yang, P. (2003, March 30). Do Institutional Characteristics Matter in Two- to Four-Year Transfer? Paper presented at Annual Meeting of the Council for the Study of Community Colleges 45th, Dallas, TX.

2002

Berkner, L., He, S., and Cataldi, E. F. (2003). Descriptive Summary of 1995-96 Beginning Postsecondary Students: Six Years Later. (NCES 2003–151) U.S. Department of Education. Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Blecher, L., Michael, W.B., and Hagedorn, L.S. (2002, April). Factors Related to the "System"

Persistence of Students Seeking the Bachelor's Degree at Four-Year Institutions. Paper presented at the annual meeting of the North East Association for Institutional Research, New Orleans, LA. [ED465345]

Bradburn, E. (2002). Short-Term Enrollment in Postsecondary Education: Student Background and Institutional Differences in Reasons for Early Departure, 1996–98. (NCES 2003–153) U.S. Department of Education. Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Choy, S.P. (2002). Access & Persistence: Findings from 10 Years of Longitudinal Research on Students. Washington, DC: Center for Policy Analysis. American Council on Education.

Choy, S. (2002). Nontraditional Undergraduates: Findings From the Condition of Education, 2002. (NCES 2002–012) U.S. Department of Education. Washington, DC: National Center for Education Statistics.

Duggan, M.B. (2002). The effect of social capital on the first-year persistence of first generation college students. Ph.D. dissertation, University of Massachusetts, Boston.

Hudson, L., and Hurst, D. 2002. The Persistence of Employees Who Pursue College Study. (NCES 2002–118) Washington, DC: National Center for Educational Statistics. Stats in Brief.

Hudson, L., and Hurst, D. (2002). The persistence of employees who pursue postsecondary study. Education Statistics Quarterly, 4(1): 33–36.

King, J.E. (2002). Crucial choices: How students' financial decisions affect their academic success. American Council on Education, Washington, DC. Center for Policy Analysis.

Pearson, A. F. (2002). Gendered organizations: Academic and social integration of females in engineering and science programs. Paper presented at the Southern Sociological Society.

Sherlin, J.H., Jr. (2002). Understanding the system persistence of first-generation students through path modeling.(Ph.D. dissertation, University of Maryland, College Park.

Wei, C.C., and Horn, L. (2002). Persistence and Attainment of Beginning Students with Pell Grants. (NCES 2002–169) U.S. Department of Education. Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Wei, C. C., and Horn, L. (2002). Persistence and attainment of beginning students with Pell grants. Education Statistics Quarterly, 4(2): 91–96.

Wine, J.S., Heuer, R.E., Wheeless, S.C., Francis, T.L., and Dudley, K.M. (2002). Beginning Postsecondary Students Longitudinal Study: 1996–2001 (BPS:1996/2001) Methodology Report. (NCES 2002–171) Washington, DC: National Center for Education Statistics. Methodology Report.

Wine, J. S., Heuer, R. E., Wheeless, S. C., Francis, T. L., Franklin, J. W., and Dudley, K. M. (2002). Beginning Postsecondary Students Longitudinal Study: 1996–2001 (BPS:1996/2001) Methodology Report. Education Statistics Quarterly, 4(3): 147–149.

2001

Choy, S.P. (2001). Findings from the Condition of Education 2001: Students Whose Parents Did Not Go to College. (NCES 2001–126, ED460660) Washington DC: National Center for Education Statistics.

Bradburn, E.M., Hurst, D.G., and Peng, S. (2001). Community College Transfer Rates to 4-Year Institutions Using Alternative Definitions of Transfer. (NCES 2001–197, ED454301) Research and Development Report. Washington DC: National Center for Education Statistics.

Duggan, M. (2001, November). Factors Influencing the First-Year Persistence of First Generation College Students. Paper presented at the Annual Meeting of the North East Association for Institutional Research, Cambridge, MA. [ED459673]

Horn, L., and Kojaku, L.K. (2001). High School Academic Curriculum and the Persistence Path Through College. (NCES 2001–163, ED456694) Washington DC: National Center for Education Statistics. Descriptive Analysis Report.

Leppel, K., Williams, M.L., and Waldauer, C. (2001). The impact of parental occupation and socioeconomic status on choice of college major. Journal of Family & Economic Issues, 22(4): 373–394.

Stratton, L.S., O'Toole, D.M., and, Wetzel, J.N. (2001, June). Factors Affecting Part-Time College Enrollment within the First Year. AIR 2001 Annual Forum Paper. Paper presented at the Annual Meeting of the Association for Institutional Research, Long Beach, CA. [ED456791]

Teng, L.Y., Morgan, G.A., and Anderson, S.K. (2001). Career development among ethnic and age groups of community college students. Journal of Career Development, 28(2): 115–127.

Warburton, E.C., Bugarin, R., and Nuñez, A. (2001). Bridging the Gap: Academic Preparation and Postsecondary Success of First-Generation Students. (NCES 2001–153, ED456168) Descriptive Analysis Report. Washington DC: National Center for Education Statistics.

Wine, J.S., Heuer, R.E., Link, M.W., Whitmore, R.W., and Francis, T.L. (2001). Beginning Postsecondary Students Longitudinal Study:1996–2001 (BPS:1996/2001) Field Test Methodology Report. (NCES 2001–04) Washington DC: National Center for Education Statistics. Technical Report.

2000

Ariguzo, G.C. “An examination of the effects of the federal College Work-Study program on minority students' persistence, academic performance, and graduation rates: Based on the NCES 1990/94 Beginning Postsecondary Students Longitudinal Study” (Ph.D. dissertation, University of Massachusetts, Boston, 2000).

Berkner, L., Horn, L. and Clune, M. (2000). Descriptive Summary of 1995–96 Beginning Postsecondary Students: Three Years Later, With an Essay on Students Who Started at Less-Than-4-Year Institutions. (NCES 2000–154) Washington DC: National Center for Education Statistics.

Boyles, L.W. (2000). Exploration of a Retention Model for Community College Students. (Ph.D. dissertation, The University of North Carolina at Greensboro.

Byun, K. (2000). A Study on the Applicability of Bean and Metzner’s Nontraditional Student Attrition Model for Older Students Using Four Different Measures of Persistence. Ph.D. dissertation, University of Oregon.

Chae, J. (2000). Student departure from United States community colleges: A competing risks survival analysis. Ph.D. dissertation, Harvard University.

Choy, S.P. (2000). Low-Income Students: Who They Are and How They Pay for Their Education. (NCES 2000–169) Washington DC: National Center for Education Statistics. Statistical Analysis Report.

Huang, G., Taddese, N., and Walter, E. (2000). Entry and Persistence of Women and Minorities in College Science and Engineering Education. (NCES 2000–161) Washington, DC: National Center for Educational Statistics. Research and Development Report.

Hurst, D., Ed., and Smerdon, B., Ed. (2000). Postsecondary Students with Disabilities: Enrollment, Services, and Persistence. (NCES 2000–092, ED444329) Washington, DC: National Center for Educational Statistics. Stats in Brief.

Ishitani, T.T. (2000). An application of event history modeling to assessing student dropout behavior: A national data approach. Ph.D. dissertation, The University of Iowa.

Levesque, K., Lauen, D., Teitelbaum, P., Alt, M., and Librera, S. (2000). Vocational Education in the United States: Toward the Year 2000. (NCES 2000–029) Washington DC: National Center for Education Statistics. Statistical Analysis Report.

U.S. Department of Education, National Center for Education Statistics. (2000). The Condition of Education 2000 (NCES 2000–062). Indicator 35, “Postsecondary Persistence and Progress: Persistence Toward a Bachelor's Degree.” Washington, DC: U.S. Government Printing Office.

U.S. Department of Education, National Center for Education Statistics. (2000). The Condition of Education 2000 (NCES 2000–062). Indicator 51, “Learning Opportunities: Student Satisfaction with Instruction.” Washington, DC: U.S. Government Printing Office.

Wine, J.S., Whitmore, R.W., Heuer, R.E., Biber, M., and Pratt, D.J. (2000). Beginning Postsecondary Students Longitudinal Study First Follow-up 1996–98 (BPS:96/98) Methodology Report. (NCES 2000–157) Washington DC: National Center for Education Statistics. Technical Report.

1999

Choy, S.P. (1999). College Access and Affordability. (NCES 1999–108) Washington, DC: National Center for Education Statistics.

Contento, J.M. (1999).Impacts of Financial Aid on Persistence: A Longitudinal Analysis of Beginning Undergraduate Students. Ph.D. Dissertation, Arizona State University.

Horn, L.J. (1999). Students with Disabilities in Postsecondary Education: A Profile of Preparation, Participation, and Outcomes. (NCES 1999–187) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Kaufman, P., and Chen, X. (1999). Projected Postsecondary Outcomes of 1992 High School Graduates. (NCES 1999–15) Washington, DC: National Center for Education Statistics. Working Paper.

LeBard, C. (1999). The Relationship between American Community Colleges’ Curricular and Extracurricular Programs and Students’ Perceptions of Their Leadership Abilities. [ED429625]

Salvucci, S., Wenck, S., and Tyson, J. (1999). Development of a Prototype System for Accessing Linked NCES data. (NCES 9815) Washington, DC: National Center for Education Statistics. Working Paper.

Shafer, L.L. (1999). Data Sources on Lifelong Learning. (ED431892) Washington, D.C.: National Center for Education Statistics. Working Paper.

1998

Choy, S.P., and Ottinger, C. (1998). Choosing a Postsecondary Institution. (NCES 98–080) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Cuccaro-Alamin, S., and Choy, S.P. (1998). Postsecondary Financing Strategies: How Undergraduates Combine Work, Borrowing, and Attendance. (NCES 98–088) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Horn, L.J. (1999). Stopouts or Stayouts? Undergraduates Who Leave College in Their First Year. (NCES 1999–087, ED425683) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Horn, L. J. (1998). Profile of Undergraduates in U.S. Postsecondary Education Institutions: 1995–96, With an Essay on Undergraduates Who Work. (NCES 98–084) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Kojaku, L.K. and Nunez, A. (1998). Descriptive Summary of 1995–96 Beginning Postsecondary Students, with Profiles of Students Entering 2- and 4-Year Institutions. National Postsecondary Student Aid Study: 1995–96. (NCES 1999–030; ED425684) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Nunez, A. (1998, November). First-Generation Students: A Longitudinal Analysis of Educational and Early Labor Market Outcomes. Paper presented at the Annual Meeting of the Association for the Study of Higher Education, Miami, FL. [ED427599]

Nunez, A., and Cuccaro-Alamin, S. (1998). First-Generation Students: Undergraduates Whose Parents Never Enrolled in Postsecondary Education. (NCES 98–082, ED420235) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Perna, L.W. (1998). The Contribution of Financial Aid to Undergraduate Persistence. Journal of Student Financial Aid, 28(3): 25–40. [EJ584135]

Perna, L.W. (1998). Does Financial Aid Help Students To Attend Higher Priced Colleges? Journal of Student Financial Aid, 28(1): 19–38. [EJ567587]

Pratt, D.J., Wine, J.S., Heuer, R.E., Whitmore, R.W., Kelly, J.E., Doherty, J.M., Simpson, J.B., and Marti, N. (1998). Beginning Postsecondary Students Longitudinal Study First Follow-up (BPS:96/98) Field Test Report. (ED434132, NCES 98–11) Washington, DC: U.S. Department of Education, Department of Educational Research and Improvement, National Center for Education. Working Paper.

Smith, T.M., et al. (1998). Employment and Postsecondary Persistence and Attainment. (NCES 98-008, ED419473. Extracted from The Condition of Education, 1997 see ED404766) Washington, DC: National Center for Education Statistics, January 1998. Indicator of the Month.

U.S. Department of Education, National Center for Education Statistics. (1998). Sub baccalaureate Persistence and Attainment. January 1998. Indicator of the Month. (NCES-98-001, ED411918. Extracted from The Condition of Education, 1997, see ED410681.) Washington, DC: U.S. Government Printing Office.

Teng, L.Y. (1998 ). The Institutional Experience and Career Development of Community College Students (Minority Students, Employment). Ph.D. Dissertation, Colorado State University.

1997

Arnold, C.L. (1997). Using National Data Sets To Create Comparable National Statistics for the Student Characteristics and Outcomes in Community Colleges. (ED421197) Washington, DC: National Center for Education Statistics and VA, Arlington: National Science Foundation, Association for Institutional Research.

Choy, S.P., and Geis, S. (1997). Early Labor Force Experiences and Debt Burden. (NCES 97–286, ED411746) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Hurtado, S., et.al. (1997). Differences in College Access in Choice among Racial/Ethnic Groups: Identifying Continuing Barriers. Research in Higher Education, 38(1): 43–75. [EJ539550]

McCormick, A.C. (1997). Transfer Behavior among Beginning Postsecondary Students: 1989–94. (NCES 97–266, ED408929) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Nettles, M.T., and Perna, L.W. (1997). The African American Education Data Book. Volume I: Higher and Adult Education. (ED406871) Fairfax, VA: College Fund/UNCF.

Riccobono, J.A., Whitmore, R.W., Gabel, T.J., Traccarella, M.A., Pratt, D.J., and Berkner, L.K. (1997).

National Postsecondary Student Aid Study, 1995-96 (NPSAS:96) Methodology Report (NCES 98–073) Washington, DC: National Center for Education Statistics. Technical Report.

1996

Berkner, L.K., et al. (1996). Descriptive Summary of 1989-90 Beginning Postsecondary Students: 5 Years Later, with an Essay on Postsecondary Persistence and Attainment. (NCES 96–155, ED396597) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Choy, S.P., and Premo, M.D. (1996). How Low Income Undergraduates Financed Postsecondary Education: 1992-93. (NCES 96–161, ED394473) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Horn, L.J. (1996). Nontraditional Undergraduates: Trends in Enrollment from 1986 to 1992 and Persistence and Attainment among 1989–90 Beginning Postsecondary Students. (NCES 97–578, ED402857) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Perna, L.W. (1996, October 31–November 1). The Contribution of Financial Aid to the Price of Four-Year Institution Attended by 1989/90 Freshmen. Paper presented at the Annual Meeting of the Association for the Study of Higher Education, Memphis, TN. [ED402820]

Pratt, D.J., Whitmore, R.W., Wine, J.S., Blackwell, K.M., Forsyth, B.H., Smith, T.K., Becker, E.A., Veith, K.J., Mitchell, M., and Borman, G.D. (1996). Beginning Postsecondary Students Longitudinal Study Second Follow-up (BPS: 90/94) Final Technical Report. (NCES 96–153) Washington, DC: National Center for Education Statistics.

1995

Choy, S.P. and Premo, M.K. (1995). Profile of Older Undergraduates: 1989–90. (NCES 95–167, ED382122) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Davis, C., Ed. 1995. Programs and Plans of the National Center for Education Statistics. 1995 Edition. (ED379357) Washington, DC: National Center for Education Statistics.

Horn, L.J. (1995). Minority Undergraduate Participation in Postsecondary Education. (NCES 95–166, ED383276) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

McCormick, A., and Geis, S. (1995). Profile of Part-Time Undergraduates in Postsecondary Education: 1989–90. (NCES 95–173) Washington, DC: National Center for Education Statistics.

McGrew, K. (1995). Disability Summary Analyses of Select National Data Collection Programs. Technical Report 11. (ED396477) Washington, DC: Special Education Programs ED/OSERS.

Perna, L.W. (1997, November 6–9). The Contribution of Financial Aid to Undergraduate Persistence. (ED415818) Paper presented at Annual Meeting of the Association for the Study of Higher Education, Albuquerque, NM.

1994

Burkheimer, G. J., Jr, et al. (1994). Beginning Postsecondary Students Longitudinal Study First Follow-up (BPS:90/92): Final Public Technical Report. (NCES 94–369) Washington, DC: National Center for Education Statistics.

Fitzgerald, R., et al. (1994). Descriptive Summary of 1989-90 Beginning Postsecondary Students: Two Years Later. (NCES 94–386, ED372691) Washington, DC: National Center for Education Statistics. Statistical Analysis Report.

Persistence and Attainment in Postsecondary Education for Beginning AY 1989-90 Students as of Spring 1992. Beginning Postsecondary Students Longitudinal Study 1992 Follow-up (BPS: 90/92). (NCES-94-477) Washington, DC: National Center for Education Statistics, November 1993. E.D. TABS.

Pratt, D.J., et al. (1994). Beginning Postsecondary Students Longitudinal Study. Second Follow-up Field Test Report; BPS:90/94. (NCES 94–370) Washington, DC: National Center for Education Statistics. Technical Report.

1993

Bobbitt, L.G., and Carroll, C.D. (1993). Coding Major Fields of Study. (ED363665) Washington, DC: National Center for Education Statistics.

1992

Burkheimer, G. J., Jr.; et al. (1992). Beginning Postsecondary Students Longitudinal Study Field Test Methodology Report: BPS 90/92. (NCES 92–160) Washington, DC: National Center for Education Statistics.

1991

Nelson, D.D., Ed. (1991). Programs and Plans of the National Center for Education Statistics, 1991 Edition. (NCES 91–694, ED339739) Washington, DC: National Center for Education Statistics.

Appendix E
BPS:12/14 Technical Review Panel Contact List

Teresita Bazan

Director, Student Assistance and Veterans

Austin Community College

5930 Middle Fiskville Road

Austin, TX 78752

Phone: (512)223-7550

^(Name⁾

^(Job Title)

^{(Date of Assignment to NPSAS:12 Project)}

^{(Organization, State, or Local Agency or Instrumentality)}

^(Address)

Dr. Jennifer Wine	Dr. Sarah Crissey
BPS Project Director (RTI)	BPS Project Officer (NCES)
877-225-8470	202- 502-7395
[email protected]	[email protected].

«fname» «mname» «lname» «suffix» «addr1» «addr2» «city», «state» «zip» «zip4» («area1») «phone1» «panelinfo»	Name:
	Address:

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	Work phone:	( )
	Cell phone:	( )

File Type	application/vnd.openxmlformats-officedocument.wordprocessingml.document
File Title	Chapter 2
Author	elyjak
File Modified	0000-00-00
File Created	2021-01-30

Primary e‑mail address:
Alternate e‑mail address:

BPS 2012-14 Field Test Appendixes A-G