ABSTRACT

Bayesian mediation analysis using the method of covariances requires specifying a prior for the covariance matrix of the independent variable, mediator, and outcome. Using a conjugate inverse-Wishart prior has been the norm, even though this choice assumes equal levels of informativeness for all elements in the covariance matrix. This paper describes separation strategy priors for the single mediator model, develops a Prior Predictive Check (PrPC) for inverse-Wishart and separation strategy priors, and implements the PrPC in a Shiny app. An empirical example illustrates the possibilities in the app. Guidelines are provided for selecting the optimal prior specification for the prior knowledge researchers wish to encode.

摘要

使用协方差方法的贝叶斯中介分析需要指定自变量、中介和结果的协方差矩阵的先验。使用共轭逆维夏特先验一直是常态，尽管这种选择假设协方差矩阵中所有元素的信息量相同。本文描述了单中介模型的分离策略先验，开发了一种用于逆Wishart 和分离策略先验的先验预测检查 (PrPC)，并在 Shiny 应用程序中实现了 PrPC。一个经验示例说明了应用程序中的可能性。为研究人员希望编码的先验知识选择最佳先验规范提供了指南。