Back to Search
Start Over
Accounting for Time-Varying Inter-Individual Differences in Trajectories when Assessing Cross-Lagged Models
- Source :
- Structural Equation Modeling: A Multidisciplinary Journal. 28:365-375
- Publication Year :
- 2020
- Publisher :
- Informa UK Limited, 2020.
-
Abstract
- This paper explores relationships amongst cross-lagged models allowing trajectories to be freely estimated, some accounting for time-varying differences amongst individuals (Autoregressive Latent Trajectory (ALT), General Cross-lagged Model (GCLM), and Latent Growth Curve Model with Structured Residuals and Unspecified Growth Trajectory (LGCM-SR-UGT)) and some not (Cross-lagged Panel Model (CLPM), Random Intercept Cross-lagged Panel Model (RI-CLPM), and Mean Stationary GCLM). An applied example using LSAY data demonstrates these models. Simulations examine (1) fit indices assessing “good” fit and Bayes Factor for model selection; (2) consequences of ignoring variability in trajectories on cross-lagged estimates. Findings were (1) RMSEA discerned “good” fit and Bayes Factor tended to select models closely related to true model over less related models; (2) various patterns of bias in path estimates and standard errors are found, in particular, causal dominance in conjunction with time-variant between-person variance and covariance were notably influential on bias in path estimates.
- Subjects :
- Sociology and Political Science
Computer science
business.industry
05 social sciences
050401 social sciences methods
General Decision Sciences
Accounting
0504 sociology
Autoregressive model
Modeling and Simulation
Cross lagged
0502 economics and business
business
General Economics, Econometrics and Finance
050203 business & management
Subjects
Details
- ISSN :
- 15328007 and 10705511
- Volume :
- 28
- Database :
- OpenAIRE
- Journal :
- Structural Equation Modeling: A Multidisciplinary Journal
- Accession number :
- edsair.doi.dedup.....8163c1c8df6407663c55429e5f22fcf5