Meta-analysis of correlation coefficients: A Monte Carlo comparison of fixed- and random-effects methods
Meta-analysis of correlation coefficients: A Monte Carlo comparison of fixed- and random-effects methods
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DOI：
10.1037//1082-989x.6.2.161
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发表时间：
2001-06-01
影响因子：
7
通讯作者：
Field, AP
中科院分区：
文献类型：
--
作者：
Field, AP
Hedges及其同事、Rosenthal-Rubin和Hunter-Schmidt组合相关系数的方法的有效性在群体效应量既固定又可变的情况下进行了检验。在简要介绍了这些荟萃分析方法之后，作者介绍了两种Monte Carlo模拟，这些模拟比较了荟萃分析中研究数量和研究平均样本量变化的情况。在固定的情况下，这些方法产生了平均效应量的可比估计值;然而，Hunter-Schmidt方法未能控制相关显著性检验的I型错误率。在变量情况下，对于Hedges及其同事和Hunter-Schmidt方法，对于包括15项或更少研究的荟萃分析，I型错误率未得到控制，并且检测到小效应的概率小于。对荟萃分析的使用提出了一些实用的建议。
The efficacy of the Hedges and colleagues, Rosenthal-Rubin, and Hunter-Schmidt methods for combining correlation coefficients was tested for cases in which population effect sizes were both fixed and variable. After a brief tutorial on these meta-analytic methods, the author presents two Monte Carlo simulations that compare these methods for cases in which the number of studies in the meta-analysis and the average sample size of studies were varied. In the fixed case the methods produced comparable estimates of the average effect size; however, the Hunter-Schmidt method failed to control the Type I error rate for the associated significance tests. In the variable case, for both the Hedges and colleagues and Hunter-Schmidt methods, Type I error rates were not controlled for meta-analyses including 15 or fewer studies and the probability of detecting small effects was less than.3. Some practical recommendations are made about the use of meta-analysis.