Mediation Analyses of Intensive Longitudinal Data with Dynamic Structural Equation Modeling
Jie Fang, Zhonglin Wen, Kit‐Tai Hau
Guangdong University Of Finances and Economics University of Finance and Economics Guangdong University of Finance South China Normal University
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摘要与影响
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 timetj 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.
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计算机 / AIPsychometric Methodologies and Testing
Mental Health Research Topics · Advanced Statistical Modeling Techniques
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