Mediation Analyses of Intensive Longitudinal Data with Dynamic Structural Equation Modeling

被引:3
|
作者
Fang, Jie [1 ]
Wen, Zhonglin [2 ,4 ]
Hau, Kit-Tai [3 ]
机构
[1] Guangdong Univ Finance & Econ, Guangzhou, Peoples R China
[2] South China Normal Univ, Guangzhou, Peoples R China
[3] Chinese Univ Hong Kong, Hong Kong, Peoples R China
[4] South China Normal Univ, Sch Psychol, Guangzhou 510631, Peoples R China
基金
中国国家自然科学基金;
关键词
Dynamic structural equation modeling; intensive longitudinal data; mediation effect; moderated mediation model; residual dynamic structural equation modeling; CROSS-SECTIONAL ANALYSES; TIME; BIAS;
D O I
10.1080/10705511.2023.2268293
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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.
引用
收藏
页码:728 / 741
页数:14
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