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Examining Quadratic Relationships Between Traits and Methods in Two Multitrait-Multimethod Models

机译:检查两个多特征多方法模型中特征与方法之间的二次关系

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摘要

Multitrait-multimethod (MTMM) analysis is one of the most frequently employed methods to examine the validity of psychological measures. Confirmatory factor analysis (CFA) is a commonly used analytic tool for examining MTMM data through the specification of trait and method latent variables. Most contemporary CFA-MTMM models either do not allow estimating correlations between the trait and method factors or they are restricted to linear trait-method relationships. There is no theoretical reason why trait and method relationships should always be linear, and quadratic relationships are frequently proposed in the social sciences. In this article, we present two approaches for examining quadratic relations between traits and methods through extended latent difference and latent means CFA-MTMM models (; ). An application of the new approaches to a multi-rater study of the nine inattention symptoms of attention-deficit/hyperactivity disorder in children (N = 752) and the results of a Monte Carlo study to test the applicability of the models under a variety of data conditions are described.
机译:多特征多方法(MTMM)分析是检查心理测度有效性的最常用方法之一。验证性因子分析(CFA)是用于通过特征和方法潜在变量的规范检查MTMM数据的常用分析工具。大多数当代的CFA-MTMM模型要么不允许估计特征与方法因素之间的相关性,要么它们仅限于线性特征与方法的关系。特征和方法之间的关系应该始终是线性的,没有任何理论上的理由,而在社会科学中经常提出二次关系。在本文中,我们提出了两种通过扩展的潜在差异和潜在均值CFA-MTMM模型来检查特征与方法之间的二次关系的方法。新方法在儿童注意力缺乏/多动障碍的九种注意力不集中症状的多评估研究中的应用(N = 752),并通过蒙特卡罗研究的结果测试了该模型在各种情况下的适用性描述了数据条件。

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