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Not Seeing Clearly With Cleary: What Test Bias Analyses Do and Do Not Tell Us

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  • Meade, Adam W.
  • Tonidandel, Scott

Abstract

In recent decades, the Cleary (1968) approach for testing for differences in regression lines among demographic groups has been codified as a central approach to evaluate a test for bias. However, this approach is fraught with numerous shortcomings, a preponderance of implicit assumptions, and outcomes that are not sufficient to conclude that there is a problem with a test. We believe these shortcomings are poorly understood by many industrial–organizational (I–O) psychologists, that this method for evaluating test bias is overrelied on by our profession, and that it is interpreted improperly by those wishing to evaluate tests for bias in applied settings. Moreover, eliminating differential prediction may be impossible in some cases, undesirable in others, and places an undue burden on organizational researchers.

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  • Meade, Adam W. & Tonidandel, Scott, 2010. "Not Seeing Clearly With Cleary: What Test Bias Analyses Do and Do Not Tell Us," Industrial and Organizational Psychology, Cambridge University Press, vol. 3(2), pages 192-205, June.
    • Handle: RePEc:cup:inorps:v:3:y:2010:i:02:p:192-205_00
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    Cited by:

    1. Rüdiger Mutz & Lutz Bornmann & Hans-Dieter Daniel, 2015. "Testing for the fairness and predictive validity of research funding decisions: A multilevel multiple imputation for missing data approach using ex-ante and ex-post peer evaluation data from the Austr," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(11), pages 2321-2339, November.

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