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Cited by 35Higher Education Research StudiesMedical Education and AdmissionsSchool Choice and Performance

Assessing Differential Prediction of College Grades by Race/Ethnicity with a Multilevel Model

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Culpepper, Steven A., Davenport, Ernest C.·2009·Journal of Educational Measurement
DOI 10.1111/j.1745-3984.2009.00079.x
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Abstract

Previous research notes the importance of understanding racial/ethnic differential prediction of college grades across multiple institutions. Institutional variation in selection indices is especially important given some states’ laws governing public institutions’ admissions decisions. This paper employed multilevel moderated multiple regression to study the variation of selection indices across 30 institutions and the accuracy of selection indices in predicting college grades for students of different racial/ethnic backgrounds. Several benefits of multilevel models for cross‐institutional differential prediction studies were described and include: controlling for institutional differences in range restriction, providing reliability estimates of least squares estimates, and adjusting criterion scores for differences in coursework difficulty. The findings from this study provide evidence of institutional variation in selection indices, which challenges current laws aimed at standardizing them. Specifically, there was evidence that the predictor slope coefficients varied across institutions, in addition to the estimates that measured intercept differences for African and Asian American students. Across universities, the results mirrored previous findings: high school grade point average (GPA) differentially predicted grades for African Americans, SAT verbal scores differentially predict grades for Asian Americans, and SAT math scores were better predictors of Asian Americans’ grades.

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  • Most research does not support the claim that test scores and grades are biased against minority individuals.

    “Apart from findings of underprediction for women (Fischer et al., 2013;Keiser et al., 2016), most research does not support the claim that test scores and grades are biased against minority individuals (Culpepper & Davenport, 2009;Mattern & Patterson, 2013).”

    From An Omitted Variables Approach to Disentangling Differential Prediction in College Admissions (2026) · cites this paper as Culpepper & Davenport, 2009

    The Literature Review (page unavailable) reports that prior studies often found minority students’ college grades were overpredicted rather than underpredicted, supporting the narrower point that these predictors did not generally disadvantage minority students in that setting. But the claim extends beyond prediction of college grades to test scores and grades generally; the Discussion (page unavailable) also reports differential prediction for African American students, so the paper does not establish the broader absence of bias. (LLM, conf=0.83)

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Research works printed but not linked: 37

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Cited by

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Authors
Culpepper, S. A., & Davenport, E. C.
Affiliations
  • University of Colorado Boulder (US)
  • University of Minnesota (US)
ORCID
Venue
Journal of Educational Measurement
Publisher
Wiley
Published
2009-06
Volume
46
Issue
2
Pages
220-242
ISSN
  • 0022-0655 (ISSN-L)
  • 1745-3984
DOI
10.1111/j.1745-3984.2009.00079.x
OpenAlex
W1996960755
Cited by
35
References
1
Citations by year
2026: 2 · 2020: 2 · 2019: 4 · 2017: 4 · 2016: 3 · 2014: 5 · 2013: 2 · 2012: 5
FWCI
18.38
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
Journal of Educational Measurement (publishedVersion)
Funders
University of Michigan
Topics
  • Social Sciences › Education › Higher Education Research Studies
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Medical Education and Admissions
  • Social Sciences › Education › School Choice and Performance
Keywords
racial and ethnic differences, selection index, institutional variation, range restriction, standardized testing, SAT scores, grade point average, African American students, Asian American students, university admission

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