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Research in Higher Education

, Volume 59, Issue 2, pp 133–155 | Cite as

Predicting Graduation Rates at 4-year Broad Access Institutions Using a Bayesian Modeling Approach

  • Gloria CrispEmail author
  • Erin Doran
  • Nicole A. Salis Reyes
Article

Abstract

This study models graduation rates at 4-year broad access institutions (BAIs). We examine the student body, structural-demographic, and financial characteristics that best predict 6-year graduation rates across two time periods (2008–2009 and 2014–2015). A Bayesian model averaging approach is utilized to account for uncertainty in variable selection in modeling graduation rates. Evidence suggests that graduation rates can be predicted by religious affiliation, proportion of students enrolled full-time, socioeconomic status of the student body, enrollment size and institutional revenue and expenditures. Findings also demonstrate that relatively fewer variables predict institutional graduation rates for Latina/o and African American students at 4-year BAIs. We conclude with implications for policy and key recommendations for research focused on 4-year BAIs.

Keywords

Broad access institutions Selectivity Graduation rates Minority students Low-income students 

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Gloria Crisp
    • 1
    Email author
  • Erin Doran
    • 2
  • Nicole A. Salis Reyes
    • 3
  1. 1.Oregon State UniversityCorvallisUSA
  2. 2.Iowa State UniversityAmesUSA
  3. 3.University of Hawai‘i at MānoaHonoluluUSA

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