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Multidimensional Factor-Analysis-Based Procedures for Assessing Scalability in Personality Measurement

机译：基于多维因素分析的人格评估过程

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摘要

Most personality tests are made up of Likert-type items and analyzed by means of factor analysis (FA). In this type of application, the fit of the model at the level of individual respondents is almost never assessed. This article proposes procedures for assessing individual fit (scalability). The procedures are intended for the analysis of multitrait personality questionnaires, and based on the multiple FA model. A general assessment procedure is described, and 2 multidimensional scalability indexes that use the chi-square and normal distribution are proposed. These indexes are derived both as residual measures and as likelihood-based person-fit measures, and their relations with some item-response, theory-based measures is discussed. The indexes are proposed mainly as first-step exploratory devices, and procedures for obtaining further information about the possible causes of misfit are also discussed. The behavior of the indexes is assessed in simulation studies, and the general procedure is illustrated by means of an empirical example.
机译：大多数人格测验是由李克特类型的项目组成，并通过因素分析（FA）进行分析。在这种类型的应用程序中，几乎从未评估过模型是否适合各个受访者。本文提出了评估个人适合度（可伸缩性）的过程。该程序旨在分析多特征人格问卷，并基于多重FA模型。描述了一种通用的评估程序，并提出了使用卡方和正态分布的2个多维可伸缩性指标。这些指标既可以作为残差测度，也可以作为基于似然度的人身测度来导出，并讨论它们与一些基于项目反应，基于理论的测度之间的关系。这些索引主要是作为第一步探索性设备提出的，并且还讨论了获取有关不当可能原因的更多信息的过程。在模拟研究中评估了指标的行为，并通过一个经验示例说明了一般过程。

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