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).

中文翻译：

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标准有效性以及一般和特定精神病理学的替代层次维度模型之间的关系。

精神病理学可以被视为相关维度的层次结构。许多研究都支持这种概念化，但他们使用了具有不同解释的替代统计模型。在双因素模型中，每个症状都加载在一般因素和 1 个特定因素（例如，内化）上，这将每个症状的总解释方差划分在这些正交因素之间。在二阶模型中，症状加载在几个相关的低阶因素之一上。这些低阶因子加载到二阶一般因子上，该因子由低阶因子共享的方差定义。因此，二阶模型中的因子不是正交的。在这些有效的统计模型之间进行选择取决于所测试的假设。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维度与假定与病因和机制相关的外部变量的共享和独特关联。然而，人们对双因子模型中正交特定因子的可靠性提出了担忧。我们在 ABCD 研究中使用 9-10 岁儿童的家长症状评级来评估这一问题。心理测量指数表明，双因素和二阶模型中的所有因素都至少表现出足够的构造可靠性和估计的可复制性。双因素和二阶模型中定义的因素在模型之间高度至中度相关，但具有不同的解释。两个模型中的所有因素都表现出与理论和临床重要性的外部标准变量的显着关联，但由于因素之间存在共同的方差，二阶模型中这种关联的解释是不明确的。（PsycInfo 数据库记录 (c) 2020 APA，保留所有权利）。