Predicting Graduation Rates at 4-year Broad Access Institutions Using a Bayesian Modeling Approach
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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.
KeywordsBroad access institutions Selectivity Graduation rates Minority students Low-income students
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