ABSTRACT

This Teacher’s Corner paper introduces Bayesian evaluation of informative hypotheses for structural equation models, using the free open-source R packages bain, for Bayesian informative hypothesis testing, and lavaan, a widely used SEM package. The introduction provides a brief non-technical explanation of informative hypotheses, the statistical underpinnings of Bayesian hypothesis evaluation, and the bain algorithm. Three tutorial examples demonstrate informative hypothesis evaluation in the context of common types of structural equation models: 1) confirmatory factor analysis, 2) latent variable regression, and 3) multiple group analysis. We discuss hypothesis formulation, the interpretation of Bayes factors and posterior model probabilities, and sensitivity analysis.

摘要

该教师角论文介绍了结构方程模型的信息假设的贝叶斯评估，使用了免费的开源R包贝恩（用于贝叶斯信息假设测试）和lavaan（一种广泛使用的SEM包）。简介对信息假设，贝叶斯假设评估的统计基础以及贝恩算法进行了简短的非技术性解释。三个教程示例在结构方程模型的常见类型的背景下演示了信息丰富的假设评估：1）验证性因子分析，2）潜变量回归和3）多组分析。我们讨论了假设公式，贝叶斯因素和后验模型概率的解释以及敏感性分析。