Comparison of Three Meta-Analytic Procedures for Estimating Moderating Effects of Categorical Variables
通过蒙特卡洛模拟比较了三种元分析方法在估计分类变量调节效应时的点估计准确性和错误率，为研究者根据理论和研究设计选择方法提供指南。
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).