Comparison of Three Meta-Analytic Procedures for Estimating Moderating Effects of Categorical Variables

Author:

Aguinis Herman1,Sturman Michael C.2,Pierce Charles A.3

Affiliation:

1. University of Colorado at Denver and Health Sciences Center,

2. Cornell University

3. University of Memphis

Abstract

The authors conducted Monte Carlo simulations to compare the Hedges and Olkin, the Hunter and Schmidt, and a refinement of the Aguinis and Pierce meta-analytic approaches for estimating moderating effects of categorical variables. The simulation examined binary moderator variables (e.g., gender—male, female; ethnicity—majority, minority). The authors compared the three meta-analytic methods in terms of their point estimation accuracy and Type I and Type II error rates. Results provide guidelines to help researchers choose among the three meta-analytic techniques based on theory (i.e., exploratory vs. confirmatory research) and research design considerations (i.e., degree of range restriction and measurement error).

Publisher

SAGE Publications

Subject

Management of Technology and Innovation,Strategy and Management,General Decision Sciences

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