Department of Psychology, Washington State University, Pullman, WA, USA.
Utah State University, Logan, UT, 84322, USA.
J Abnorm Child Psychol. 2020 Jul;48(7):917-922. doi: 10.1007/s10802-020-00656-1.
The commentaries by Burke and Johnston (this issue), Eid (this issue), Junghänel et al. (this issue), and Willoughby (this issue) on Burns et al. (this issue) provide useful context for comparing three latent variable modeling approaches to understanding psychopathology-the correlated first-order syndrome-specific factors model, the bifactor S - 1 model, and the symmetrical bifactor model. The correlated first-order syndrome-specific factors model has proven useful in constructing explanatory models of psychopathology. The bifactor S - 1 model is also useful for examining the latent structure of psychopathology, especially in contexts with clear theoretical predictions. Joint use of correlated first-order syndrome-specific model and bifactor S - 1 model provides leverage for explaining psychopathology, and both models can also guide individual clinical assessment. In this reply, we further clarify reasons why the symmetrical bifactor model should not be used to study the latent structure of psychopathology and also discuss a restricted bifactor S - 1 model that is equivalent to the first-order syndrome-specific factors model.
伯克和约翰斯顿（本期）、艾德（本期）、容格内尔等人（本期）和威洛比（本期）对伯恩斯等人（本期）的评论为比较三种潜在变量建模方法理解精神病理学提供了有用的背景信息，这三种方法是相关的一阶综合征特异性因素模型、双因素 S-1 模型和对称双因素模型。相关的一阶综合征特异性因素模型已被证明在构建精神病理学的解释模型方面非常有用。双因素 S-1 模型也可用于检查精神病理学的潜在结构，尤其是在具有明确理论预测的情况下。相关的一阶综合征特异性模型和双因素 S-1 模型的联合使用为解释精神病理学提供了优势，并且这两种模型也可以指导个体临床评估。在本回复中，我们进一步澄清了不应使用对称双因素模型来研究精神病理学潜在结构的原因，并讨论了等效于一阶综合征特异性因素模型的受限双因素 S-1 模型。
