Ryu Ehri, Cheong Jeewon
Psychology, Boston CollegeChestnut Hill, MA, USA.
Health Education and Behavior, University of FloridaGainesville, FL, USA.
Front Psychol. 2017 May 11;8:747. doi: 10.3389/fpsyg.2017.00747. eCollection 2017.
In this article, we evaluated the performance of statistical methods in single-group and multi-group analysis approaches for testing group difference in indirect effects and for testing simple indirect effects in each group. We also investigated whether the performance of the methods in the single-group approach was affected when the assumption of equal variance was not satisfied. The assumption was critical for the performance of the two methods in the single-group analysis: the method using a product term for testing the group difference in a single path coefficient, and the Wald test for testing the group difference in the indirect effect. Bootstrap confidence intervals in the single-group approach and all methods in the multi-group approach were not affected by the violation of the assumption. We compared the performance of the methods and provided recommendations.
在本文中,我们评估了统计方法在单组和多组分析方法中的性能,用于检验间接效应中的组间差异以及检验每组中的简单间接效应。我们还研究了在不满足方差齐性假设时,单组方法中这些方法的性能是否会受到影响。该假设对于单组分析中两种方法的性能至关重要:一种是使用乘积项检验单一路径系数中的组间差异的方法,另一种是检验间接效应中组间差异的 Wald 检验。单组方法中的 Bootstrap 置信区间以及多组方法中的所有方法均不受该假设违背的影响。我们比较了这些方法的性能并给出了建议。