The Small Sample Performance of Four Tests of the Difference Between Pairs of Meta-Analytically Derived Effect Sizes
通过蒙特卡洛模拟比较了四种检验方法在元分析中比较效应量差异时的小样本表现，发现基于效应量差异的z检验在控制第一类错误和统计功效上最准确，而修正的置信区间方法在图形化检验调节变量方面有潜力。
Four tests for the difference between pooled estimators of effect size from separate meta-analyses are discussed, and small sample performance compared via Monte Carlo simulation. In terms of Type I error and power, a z-test based on the difference between pooled estimators appears most accurate, while a confidence interval approach modified to permit testing between two mean effect sizes and Hedges and Olkin’s (1985) chi-square test with one degree of freedom appear roughly equivalent, and each of these is superior to a z-test based on an r-transformation. The modified confidence interval approach has particular promise for graphical examination of presumed moderators in meta-analyses.