Aguinis, HermanSturman, Michael C.Pierce, Charles A.2020-09-122020-09-122008-01-014854345https://hdl.handle.net/1813/72298The 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).en-USRequired Publisher Statement: © SAGE. Aguinis, H., Sturman, M. C., & Pierce, C. A. (2008). Final version published as: Comparison of three meta-analytic procedures for estimating moderating effects of categorical variables. Organizational Research Methods, 11(1), 9-34. doi: 10.1177/1094428106292896. Reprinted with permission. All rights reserved.meta-analysismoderator variablemoderating effectcategorical variablearticle