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).

中文翻译：

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使用贝叶斯因子检测中介效应：性能评估和样本量确定工具。


测试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（BF）进行贝叶斯假设检验变得越来越流行。然而，尽管关于贝叶斯中介分析的文献越来越多，但使用 BF 来测试中介效应的研究仍然不足。在这项研究中，我们系统地检查了 BF 的性能，以测试是否存在中介效应。我们的结果表明，检测 BF 中介的假阳性率和/或真阳性率可能会受到先前规范的影响，包括在 BF 中使用的每条路径（治疗-中介路径或中介-结果路径）存在的先验几率。设计阶段用于数据生成，分析阶段用于计算中介效应的BF。根据我们的检查，我们开发了一个 R 函数和一个 Web 应用程序来确定用于测试 BF 中介效应的样本大小。我们的研究提供了关于 BF 在测试中介效应方面的性能的见解，并增加了研究人员用于中介研究的样本量确定工具箱。 （PsycInfo 数据库记录 (c) 2024 APA，保留所有权利）。