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Improving Institutional Evaluation Methods: Comparing Three Evaluations Using PSM, Exact and Coarsened Exact Matching

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  • Bob Blankenberger

    (University of Illinois at Springfield)

  • Sophia Gehlhausen Anderson

    (Illinois Board of Higher Education
    University of Illinois at Springfield)

  • Eric Lichtenberger

    (Illinois Board of Higher Education)

Abstract

Policymakers and institutional leaders in higher education too often make decisions based on descriptive data analyses or even anecdote when better analysis options could produce more nuanced and more valuable results. Employing the setting of higher education program evaluation at a midwestern regional public university, for this study we compared analysis approaches using basic descriptive analyses, regression, standard propensity score matching (PSM), and a mixture of PSM with continuous variables, coarsened exact matching, and exact matching on categorical variables. We used three examples of program evaluations: a freshman seminar, an upper division general education program intended to improve cultural awareness and respect for diverse groups, and multiple living learning communities. We describe how these evaluations were conducted, compare the different results for each type of method employed, and discuss the strengths and weaknesses of each in the context of program evaluation.

Suggested Citation

  • Bob Blankenberger & Sophia Gehlhausen Anderson & Eric Lichtenberger, 2021. "Improving Institutional Evaluation Methods: Comparing Three Evaluations Using PSM, Exact and Coarsened Exact Matching," Research in Higher Education, Springer;Association for Institutional Research, vol. 62(8), pages 1248-1275, December.
  • Handle: RePEc:spr:reihed:v:62:y:2021:i:8:d:10.1007_s11162-021-09632-0
    DOI: 10.1007/s11162-021-09632-0
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    References listed on IDEAS

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    1. Kosuke Imai & Gary King & Elizabeth A. Stuart, 2008. "Misunderstandings between experimentalists and observationalists about causal inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(2), pages 481-502, April.
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