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

Frontiers in Psychology

article

Fred A. Hintz¹  Christian Geiser¹  G. Leonard Burns²  Mateu Servera³ 

[1] Department of Psychology, Utah State University, United States;Department of Psychology, Washington State University, United States;Department of Psychology, University of the Balearic Islands

关键词: structural equation modeling;    multiple rater;    multitrait-multimethod (MTMM) analysis;    latent moderated structural equations;    latent difference model;    latent means model;   

DOI  :  10.3389/fpsyg.2019.00353

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 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 ( Pohl et al., 2008 ; Pohl and Steyer, 2010 ). 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.

【 授权许可】

CC BY