Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa 52242, USA; email:
Annu Rev Clin Psychol. 2019 May 7;15:51-69. doi: 10.1146/annurev-clinpsy-050718-095522. Epub 2019 Jan 16.
Bifactor and other hierarchical models have become central to representing and explaining observations in psychopathology, health, and other areas of clinical science, as well as in the behavioral sciences more broadly. This prominence comes after a relatively rapid period of rediscovery, however, and certain features remain poorly understood. Here, hierarchical models are compared and contrasted with other models of superordinate structure, with a focus on implications for model comparisons and interpretation. Issues pertaining to the specification and estimation of bifactor and other hierarchical models are reviewed in exploratory as well as confirmatory modeling scenarios, as are emerging findings about model fit and selection. Bifactor and other hierarchical models provide a powerful mechanism for parsing shared and unique components of variance, but care is required in specifying and making inferences about them.
双因子和其他层级模型已经成为在精神病理学、健康和临床科学的其他领域，以及更广泛的行为科学中表示和解释观察结果的核心方法。这种突出地位是在经历了相对快速的重新发现之后出现的，然而，某些特征仍然理解得不够透彻。在这里，层级模型与其他高级结构模型进行了比较和对比，重点是对模型比较和解释的影响。在探索性和验证性建模场景中，对双因子和其他层级模型的规范和估计问题进行了回顾，以及关于模型拟合和选择的新发现。双因子和其他层级模型为解析方差的共享和独特成分提供了一个强大的机制，但在规范和进行推断时需要谨慎。
