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赋予G一个意义:双因素 -(S - 1)方法在实现更以症状为导向的贝克抑郁量表第二版建模中的应用。

Giving G a Meaning: An Application of the Bifactor-(S-1) Approach to Realize a More Symptom-Oriented Modeling of the Beck Depression Inventory-II.

作者信息

Heinrich Manuel, Zagorscak Pavle, Eid Michael, Knaevelsrud Christine

机构信息

Freie Universität Berlin, Berlin, Germany.

出版信息

Assessment. 2020 Oct;27(7):1429-1447. doi: 10.1177/1073191118803738. Epub 2018 Oct 6.

DOI:10.1177/1073191118803738
PMID:30293444
Abstract

The Beck Depression Inventory-II is one of the most frequently used scales to assess depressive burden. Despite many psychometric evaluations, its factor structure is still a topic of debate. An increasing number of articles using fully symmetrical bifactor models have been published recently. However, they all produce anomalous results, which lead to psychometric and interpretational difficulties. To avoid anomalous results, the bifactor-(S-1) approach has recently been proposed as alternative for fitting bifactor structures. The current article compares the applicability of fully symmetrical bifactor models and symptom-oriented bifactor-(S-1) and first-order confirmatory factor analysis models in a large clinical sample ( 3,279) of adults. The results suggest that bifactor-(S-1) models are preferable when bifactor structures are of interest, since they reduce problematic results observed in fully symmetrical bifactor models and give the G factor an unambiguous meaning. Otherwise, symptom-oriented first-order confirmatory factor analysis models present a reasonable alternative.

摘要

贝克抑郁量表第二版是评估抑郁负担最常用的量表之一。尽管进行了许多心理测量学评估,但其因素结构仍是一个有争议的话题。最近发表了越来越多使用完全对称双因素模型的文章。然而,它们都产生了异常结果,这导致了心理测量学和解释方面的困难。为了避免异常结果,双因素 -(S - 1)方法最近被提出作为拟合双因素结构的替代方法。本文比较了完全对称双因素模型、症状导向双因素 -(S - 1)模型和一阶验证性因素分析模型在一个大型成人临床样本(3279例)中的适用性。结果表明,当对双因素结构感兴趣时,双因素 -(S - 1)模型更可取,因为它们减少了在完全对称双因素模型中观察到的问题结果,并赋予G因素明确的含义。否则,症状导向的一阶验证性因素分析模型是一个合理的替代选择。

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