统计
估计员
同质性(统计学)
置信区间
数学
相关性
蒙特卡罗方法
荟萃分析
皮尔逊积矩相关系数
复制(统计)
计量经济学
费希尔变换
医学
几何学
内科学
作者
Adam R. Hafdahl,Michelle A. Williams
摘要
In 2 Monte Carlo studies of fixed- and random-effects meta-analysis for correlations, A. P. Field (2001) ostensibly evaluated Hedges-Olkin-Vevea Fisher-z and Schmidt-Hunter Pearson-r estimators and tests in 120 conditions. Some authors have cited those results as evidence not to meta-analyze Fisher-z correlations, especially with heterogeneous correlation parameters. The present attempt to replicate Field's simulations included comparisons with analytic values as well as results for efficiency and confidence-interval coverage. Field's results under homogeneity were mostly replicable, but those under heterogeneity were not: The latter exhibited up to over .17 more bias than ours and, for tests of the mean correlation and homogeneity, respectively, nonnull rejection rates up to .60 lower and .65 higher. Changes to Field's observations and conclusions are recommended, and practical guidance is offered regarding simulation evidence and choices among methods. Most cautions about poor performance of Fisher-z methods are largely unfounded, especially with a more appropriate z-to-r transformation. The Appendix gives a computer program for obtaining Pearson-r moments from a normal Fisher-z distribution, which is used to demonstrate distortion due to direct z-to-r transformation of a mean Fisher-z correlation.
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