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元分析中效应量差异的方法，发现基于效应量差异的z检验在I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.