Multilevel Factor Analysis and Structural Equation Modeling of Daily Diary Coping Data: Modeling Trait and State Variation

结构方程建模 多级模型 特质 变化(天文学) 应对(心理学) 心理学 计量经济学 统计 计算机科学 数学 临床心理学 天体物理学 物理 程序设计语言
作者
Scott C. Roesch,Arianna A. Aldridge,Stephanie N. Stocking,Feion Villodas,Queenie K. Leung,Carrie E. Bartley,L. J. Black
出处
期刊:Multivariate Behavioral Research [Taylor & Francis]
卷期号:45 (5): 767-789 被引量:81
标识
DOI:10.1080/00273171.2010.519276
摘要

The current study used multilevel modeling of daily diary data to model within-person (state) and between-person (trait) components of coping variables. This application included the introduction of multilevel factor analysis (MFA) and a comparison of the predictive ability of these trait/state factors. Daily diary data was collected on a large (n = 366) multiethnic sample over the course of five days. Intraclass correlation coefficient for the derived factors suggested approximately equal amounts of variability in coping usage at the state and trait levels. MFAs showed that Problem-Focused Coping and Social Support emerged as stable factors at both the within-person and between-person levels. Other factors (Minimization, Emotional Rumination, Avoidance, Distraction) were specific to the within-person or between-person levels, but not both. Multilevel structural equation modeling (MSEM) showed that the prediction of daily positive and negative affect differed as a function of outcome and level of coping factor. The Discussion section focuses primarily on a conceptual and methodological understanding of modeling state and trait coping using daily diary data with MFA and MSEM to examine covariation among coping variables and predicting outcomes of interest.

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