Liu Xiao, Zhang Zhiyong, Wang Lijuan
Department of Educational Psychology, University of Texas at Austin.
Department of Psychology, University of Notre Dame.
Psychol Methods. 2024 May 23. doi: 10.1037/met0000670.
Testing the presence of mediation effects is important in social science research. Recently, Bayesian hypothesis testing with Bayes factors (BFs) has become increasingly popular. However, the use of BFs for testing mediation effects is still under-studied, despite the growing literature on Bayesian mediation analysis. In this study, we systematically examine the performance of the BF for testing the presence versus absence of a mediation effect. Our results showed that the false and/or true positive rates of detecting mediation with the BF can be impacted by the prior specification, including the prior odds of the presence of each path (treatment-mediator path or mediator-outcome path) used in the design stage for data generation and in the analysis stage for calculating the BF of the mediation effect. Based on our examination, we developed an R function and a web application to determine sample sizes for testing mediation effects with the BF. Our study provides insights on the performance of the BF for testing mediation effects and adds to researchers' toolbox of sample size determination for mediation studies. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
检验中介效应的存在在社会科学研究中很重要。最近，使用贝叶斯因子（BFs）的贝叶斯假设检验越来越受欢迎。然而，尽管关于贝叶斯中介分析的文献不断增加，但使用BFs检验中介效应仍未得到充分研究。在本研究中，我们系统地考察了BF在检验中介效应存在与否时的表现。我们的结果表明，使用BF检测中介效应的假阳性率和/或真阳性率可能会受到先验设定的影响，包括在数据生成的设计阶段以及在分析阶段计算中介效应的BF时所使用的每条路径（处理-中介路径或中介-结果路径）存在的先验概率。基于我们的考察，我们开发了一个R函数和一个网络应用程序，用于确定使用BF检验中介效应时的样本量。我们的研究为使用BF检验中介效应的表现提供了见解，并为中介研究的样本量确定增添了研究人员的工具库。（PsycInfo数据库记录（c）2024美国心理学会，保留所有权利）
