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Correction to Moore et al. (2020).
Journal of Psychopathology and Clinical Science ( IF 4.6 ) Pub Date : 2020-10-01 , DOI: 10.1037/abn0000646
Tyler M. Moore , Antonia N. Kaczkurkin , E. Leighton Durham , Hee Jung Jeong , Malerie G. McDowell , Randolph M. Dupont , Brooks Applegate , Jennifer L. Tackett , Carlos Cardenas-Iniguez , Omid Kardan , Gaby N. Akcelik , Andrew J. Stier , Monica D. Rosenberg , Donald Hedeker , Marc G. Berman , Benjamin B. Lahey

Reports an error in "Criterion validity and relationships between alternative hierarchical dimensional models of general and specific psychopathology" by Tyler M. Moore, Antonia N. Kaczkurkin, E. Leighton Durham, Hee Jung Jeong, Malerie G. McDowell, Randolph M. Dupont, Brooks Applegate, Jennifer L. Tackett, Carlos Cardenas-Iniguez, Omid Kardan, Gaby N. Akcelik, Andrew J. Stier, Monica D. Rosenberg, Donald Hedeker, Marc G. Berman and Benjamin B. Lahey (Journal of Abnormal Psychology, Advanced Online Publication, Jul 16, 2020, np). 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. (The following abstract of the original article appeared in record 2020-50590-001.) 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:

对摩尔等人的更正。(2020)。

在Tyler M. Moore,Antonia N. Kaczkurkin,E。Leighton Durham,Hee Jung Jeong,Malerie G.McDowell,Randolph M. Dupont, Brooks Applegate,Jennifer L.Tackett,Carlos Cardenas-Iniguez,Omid Kardan,Gaby N.Akcelik,Andrew J.Stier,Monica D.Rosenberg,Donald Hedeker,Marc G.Berman和Benjamin B.Lahey(《异常心理学杂志》在线出版物,2020年7月16日,np)。在文章(http://dx.doi.org/10.1037/abn0000601)中,作者注释中缺少确认。丢失的确认包含在勘误中。(原始文章的以下摘要出现在记录2020-50590-001中。)精神病理学可以看作是相关维度的层次结构。许多研究都支持这种概念化,但是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,每个症状都会在一般因素和1个特定因素(例如,内在化)上加重,从而在这些正交因素之间划分每种症状的总解释方差。在二阶模型中,症状加重在几个相关的低阶因素之一上。这些低阶因子加在二阶通用因子上,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检验的假设。因为双因素模型定义了具有不同变异来源的正交表型,所以它们是研究精神病理学维度与可能与病因和机制相关的外部变量的共享且唯一关联的最佳选择。然而,人们对双因素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岁父母的症状分级来评估这种担忧。心理测验指标表明,双因素模型和二阶模型中的所有因素均至少表现出足够的构建可靠性和估计的可复制性。在双因素模型和二阶模型中定义的因素在各个模型中具有高度至中度相关性,但具有不同的解释。两种模型中的所有因素均显示出与具有理论和临床重要性的外部标准变量之间的显着关联,但由于因素之间存在共同的差异,因此在二阶模型中此类关联的解释不明确。(PsycInfo数据库记录(c)2020 APA,保留所有权利)。
更新日期:2020-10-01
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