Mediation Analyses of Intensive Longitudinal Data with Dynamic Structural Equation Modeling

Currently, dynamic structural equation modeling (DSEM) and residual DSEM (RDSEM) are commonly used in testing intensive longitudinal data (ILD). Researchers are interested in ILD mediation models, but their analyses are challenging. The present paper mathematically derived, empirically compared, and...

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Bibliographic Details
Published in:Structural equation modeling 2024-07, Vol.31 (4), p.728-741
Main Authors: Fang, Jie, Wen, Zhonglin, Hau, Kit-Tai
Format: Article
Language:English
Subjects:
Bayesian analysis
Discriminant analysis
Dynamic structural equation modeling
Generalized linear models
intensive longitudinal data
Mediation
mediation effect
moderated mediation model
Parameter estimation
Predictive control
residual dynamic structural equation modeling
Simulation
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Summary:Currently, dynamic structural equation modeling (DSEM) and residual DSEM (RDSEM) are commonly used in testing intensive longitudinal data (ILD). Researchers are interested in ILD mediation models, but their analyses are challenging. The present paper mathematically derived, empirically compared, and step-by-step demonstrated three types (i.e., 1-1-1, 2-1-1, and 2-2-1) of intensive longitudinal mediation (ILM) analyses based on DSEM and RDSEM models. Specifically, each ILM model was demonstrated with a simulated example and illustrated with the corresponding annotated Mplus codes. We compared two types of detrending methods in mediation analyses and showed that RDSEM was superior to DSEM because the latter included the time tj variable as a Level 1 predictor. Lastly, we extended ILM analyses based on DSEM and RDSEM to multilevel autoregressive mediation models, cross-classified DSEM, and intensive longitudinal moderated mediation models.
ISSN:1070-5511
1532-8007
DOI:10.1080/10705511.2023.2268293