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Empirical Benchmarks for Interpreting Effect Size Variability in Meta-Analysis

Published online by Cambridge University Press:  30 August 2017

Brenton M. Wiernik*
Department of Developmental, Personality and Social Psychology, Ghent University
Jack W. Kostal
Department of Psychology, University of Minnesota
Michael P. Wilmot
Department of Psychology, University of Minnesota
Stephan Dilchert
Narendra Paul Loomba Department of Management, Baruch College, CUNY
Deniz S. Ones
Department of Psychology, University of Minnesota
Correspondence concerning this article should be addressed to Brenton M. Wiernik, Department of Developmental, Personality and Social Psychology, Ghent University, Henri Dunantlaan 2, 9000 Gent, Belgium. Email:


Generalization in meta-analyses is not a dichotomous decision (typically encountered in papers using the Q test for homogeneity, the 75% rule, or null hypothesis tests). Inattention to effect size variability in meta-analyses may stem from a lack of guidelines for interpreting credibility intervals. In this commentary, we describe two methods for making practical interpretations and determining whether a particular SDρ represents a meaningful level of variability.

Copyright © Society for Industrial and Organizational Psychology 2017 

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