多维潜变量建模的发展:层次性和交叉性的双视角

doi:10.16187/j.cnki.issn1001-4918.2025.05.15

摘要/Abstract

摘要： 在心理、教育、管理等社科领域,经常涉及多维潜变量。多维潜变量建模方法经历了从简单到精确、贝叶斯统计与频率统计并行的发展过程。本文首先回顾和评介了多维潜变量的传统建模方法,其次概述了基于层次性和交叉性双视角的双因子探索性结构方程模型(bifactor-ESEM)和双因子贝叶斯结构方程模型(bifactor-BSEM)两种新近建模方法的特点以及在心理学等社科研究中的应用,然后总结出一个兼顾简洁性和精确性的多维潜变量建模流程。最后通过一个实例对多维潜变量的各种建模方法进行了演示。

关键词: 双因子模型, 探索性结构方程模型, 贝叶斯结构方程模型, 双因子探索性结构方程模型, 双因子贝叶斯结构方程模型

Abstract: Empirical psychological, educational, and managemental researches are frequently confronted with multidimensional latent variables (e.g., emotional intelligence, job burnout). The measurement model of multidimensional latent variables is established through confirmatory factor analysis (CFA), bifactor models, exploratory structural equation models (ESEM), bayesian structural equation models (BSEM), bifactor exploratory structural equation models (bifactor-ESEM), and bifactor Bayesian structural equation models (bifactor-BSEM). BSEM and bifactor-BSEM models are developed within the Bayesian statistical framework, while other models are proposed on the base of frequency statistics. Although domestic scholars are familiar with CFA and have a certain understanding of bifactor model, ESEM and BSEM, they know little about bifactor-ESEM and bifactor-BSEM. The latter two models not only allow the coexistence of global and specific constructs (i.e., both general and specific factors in the models), but also incorporate the effects of non-target subdomains on items (i.e., cross-loadings between specific factors). First, this study reviews and comments on the traditional modeling methods of multidimensional latent variables. Second, we introduce the characteristics of bifactor-ESEM and bifactor-BSEM and their applications in social science research (e.g., psychology). Third, a flow chart of multidimensional latent variable modeling is presented, which balances the simplicity and the precision. Finally, an empirical example is illustrated to demonstrate the use of various modeling methods of multidimensional latent variables.

Key words: bifactor model, ESEM, BSEM, bifactor-ESEM, bifactor-BSEM

中图分类号:

B844

顾红磊, 温忠麟. 多维潜变量建模的发展:层次性和交叉性的双视角[J]. 心理发展与教育, 2025, 41(5): 750-760.

GU Honglei, WEN Zhonglin. The Development of Multidimensional Latent Variable Modeling: Dual Perspectives of Hierarchy and Overlapping[J]. Psychological Development and Education, 2025, 41(5): 750-760.

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