A comparison of methods to test mediation and other intervening variable effects
A comparison of methods to test mediation and other intervening variable effects
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DOI：
10.1037/1082-989x.7.1.83
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发表时间：
2002-03-01
影响因子：
7
通讯作者：
Sheets, V
中科院分区：
文献类型：
--
作者：
MacKinnon, DP;Lockwood, CM;Sheets, V
一项蒙特卡罗研究比较了14种方法来检验干预变量效应的统计学显著性。中介变量将自变量的影响传递给因变量。常用的R. M. Baron和D. A. Kenny（1986）方法的统计功效较低。基于乘积分布的两种方法和两种系数差方法具有最准确的I型错误率和最大的统计功效，除了在I型错误率太高的重要情况下。所有情况下I类错误和统计功效的最佳平衡是对包括干预变量效应的两个效应的联合显著性进行检验。
A Monte Carlo study compared 14 methods to test the statistical significance of the intervening variable effect. An intervening variable (mediator) transmits the effect of an independent variable to a dependent variable. The commonly used R. M. Baron and D. A. Kenny (1986) approach has low statistical power. Two methods based on the distribution of the product and 2 difference-in-coefficients methods have the most accurate Type I error rates and greatest statistical power except in I important case in which Type I error rates are too high. The best balance of Type I error and statistical power across all cases is the test of the joint significance of the two effects comprising the intervening variable effect.