Comparison of Weights for Meta-Analysis of r and d Under Realistic Conditions
通过蒙特卡洛模拟比较了单位权重、样本量权重和逆方差权重在随机效应元分析中估计总体均值和随机效应方差成分的表现，发现对于r样本量权重最佳，对于d逆方差权重最佳。
We compared unit, sample size, and inverse variance weighting procedures for estimating the overall mean and random-effects variance component (REVC) in random-effects meta-analysis under realistic conditions for both r and d. Root mean square error and average absolute error of estimation were used to compare weighting schemes via Monte-Carlo simulation. For r, unit weights worked surprisingly well, and sample size weights worked best overall. For d, unit weights worked poorly, and inverse variance weights worked best overall. Discussion focuses on the meta-analyst’s choice of weights, possible explanations for the differences across types of effect size, and implications for meta-analytic inferences in organizational research.