Comparison of three meta-analytic procedures for estimating moderating effects of categorical variables

Aguinis, Herman, Sturman, M.C., & Pierce, C.A.
Organizational Research Methods Vol 11, Issue 1, 2008

We conducted Monte Carlo simulations to compare the Hedges-Olkin (1985), Hunter-Schmidt (1990, 2004), and a refinement of the Aguinis-Pierce (1998) meta-analytic approaches for estimating moderating effects of categorical variables. The simulation examined binary moderator variables (e.g., gender–male, female; ethnicity–majority, minority). We compared the three meta-analytic methods in terms of their point estimation accuracy as well as 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).