Department of Psychiatry, University of Pennsylvania.
Department of Psychology, Vanderbilt University.
J Abnorm Psychol. 2020 Oct;129(7):677-688. doi: 10.1037/abn0000601. Epub 2020 Jul 16.
[Correction Notice: An Erratum for this article was reported in Vol 129(7) of (see record 2020-72912-001). In the article (http://dx.doi.org/10.1037/abn0000601), an acknowledgment is missing from the author note. The missing acknowledgement is included in the erratum.] Psychopathology can be viewed as a hierarchy of correlated dimensions. Many studies have supported this conceptualization, but they have used alternative statistical models with differing interpretations. In bifactor models, every symptom loads on both the general factor and 1 specific factor (e.g., internalizing), which partitions the total explained variance in each symptom between these orthogonal factors. In second-order models, symptoms load on one of several correlated lower-order factors. These lower-order factors load on a second-order general factor, which is defined by the variance shared by the lower-order factors. Thus, the factors in second-order models are not orthogonal. Choosing between these valid statistical models depends on the hypothesis being tested. Because bifactor models define orthogonal phenotypes with distinct sources of variance, they are optimal for studies of shared and unique associations of the dimensions of psychopathology with external variables putatively relevant to etiology and mechanisms. Concerns have been raised, however, about the reliability of the orthogonal specific factors in bifactor models. We evaluated this concern using parent symptom ratings of 9-10 year olds in the ABCD Study. Psychometric indices indicated that all factors in both bifactor and second-order models exhibited at least adequate construct reliability and estimated replicability. The factors defined in bifactor and second-order models were highly to moderately correlated across models, but have different interpretations. All factors in both models demonstrated significant associations with external criterion variables of theoretical and clinical importance, but the interpretation of such associations in second-order models was ambiguous due to shared variance among factors. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
[勘误通知:本文的勘误报告在 (请参见记录 2020-72912-001)的 129(7)卷中报告。在文章(http://dx.doi.org/10.1037/abn0000601)中,作者注释中缺少一个致谢。缺失的致谢包含在勘误中。] 可以将精神病理学视为相关维度的层次结构。许多研究都支持这种概念化,但它们使用了具有不同解释的替代统计模型。在双因素模型中,每个症状都同时加载在一般因素和 1 个特定因素(例如,内部因素)上,这将每个症状的总可解释方差在这两个正交因素之间进行划分。在二阶模型中,症状加载在几个相关的低阶因素之一上。这些低阶因素加载在二阶一般因素上,该因素由低阶因素之间的共享方差定义。因此,二阶模型中的因素不是正交的。在这些有效统计模型之间进行选择取决于正在测试的假设。由于双因素模型定义了具有不同方差来源的正交表型,因此它们最适合研究精神病理学的维度与假定与病因和机制相关的外部变量之间的共享和独特关联。然而,人们对双因素模型中正交特定因素的可靠性提出了担忧。我们使用 ABCD 研究中 9-10 岁儿童的父母症状评分来评估这种担忧。心理测量学指标表明,双因素和二阶模型中的所有因素都表现出至少足够的结构可靠性和估计可重复性。两种模型中定义的因素在模型之间高度相关,但具有不同的解释。两种模型中的所有因素都与理论和临床重要的外部标准变量显著相关,但由于因素之间的共享方差,二阶模型中的这种关联的解释是模糊的。(PsycInfo 数据库记录(c)2020 APA,保留所有权利)。