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Generalizability Versus Situational Specificity in Adverse Impact Analysis: Issues in Data Aggregation

Published online by Cambridge University Press:  30 August 2017

Elizabeth Howard ,
Scott B. Morris  and
Eric Dunleavy
Elizabeth Howard*
Affiliation:
Illinois Institute of Technology
Scott B. Morris
Affiliation:
Illinois Institute of Technology
Eric Dunleavy
Affiliation:
DCI Consulting Group
*
Correspondence concerning this article should be addressed to Elizabeth Howard, Illinois Institute of Technology, 3105 S. Dearborn, Chicago, IL 60616. E-mail: [email protected]
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Extract

Tett, Hundley, and Christiansen (2017) argue that the concept of validity generalization in meta-analysis is a myth, as the variability of the effect size appears to decrease with increasing moderator specificity such that the level of precision needed to deem an estimate “generalizable” is actually reached at levels of situational specificity that are so high as to (paradoxically) refute an inference of generalizability. This notion highlights the need to move away from claiming that effects are either “generalizable” or “situationally specific” and instead look more critically and less dichotomously at degrees of generalizability, or effect size variability.

Type
Commentaries
Information
Industrial and Organizational Psychology , Volume 10 , Issue 3 , September 2017 , pp. 495 - 501
Copyright
Copyright © Society for Industrial and Organizational Psychology 2017 

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