The Prowess and Pitfalls of Bayesian Structural Equation Modeling
评述了贝叶斯结构方程模型（BSEM）技术，指出其与验证性和探索性因子分析的关系及当前应用中的关键问题，并基于创业自我效能感数据提出改进方法和使用建议。
Muthén and Asparouhov introduced an approach for conducting Bayesian inference in the context of structural equation models that they termed Bayesian structural equation modeling (BSEM). In this article, we provide an overview of the BSEM technique, illustrate how this technique relates to confirmatory and exploratory factor analysis, and highlight several key problems with using the BSEM approach as it is currently advocated. Utilizing data from a large-scale study of entrepreneurial self-efficacy, we develop a modified approach for applying the BSEM technique in a manner that is more consistent with accepted principles of reflective measurement, factor analysis, and model selection. We devise a series of recommendations to guide future use of the BSEM technique to help ensure that mainstream use of this approach heralds the coming of a new day in measurement development rather than a false dawn.