Three Extensions of the Random Intercept Cross-Lagged Panel Model. Issue 4 (4th July 2021)

• Record Type: Journal Article
• Authors: Mulder, Jeroen D.; Hamaker, Ellen L.
• Is Part Of: Structural equation modeling. Volume 28:Issue 4(2021)
• Page Start: 638
• Page End: 648
• Publication Date: 2021-07-04
• Subjects: Random-Intercept Cross-Lagged Panel Model -- panel data -- within-person dynamics -- longitudinal modeling; Multivariate analysis -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 519.535
• DOI: 10.1080/10705511.2020.1784738
• Languages: English
• ISSNs: 1070-5511

Abstract

ABSTRACT: The random intercept cross-lagged panel model (RI-CLPM) is rapidly gaining popularity in psychology and related fields as a structural equation modeling (SEM) approach to longitudinal data. It decomposes observed scores into within-unit dynamics and stable, between-unit differences. This paper discusses three extensions of the RI-CLPM that researchers may be interested in, but are unsure of how to accomplish: (a) including stable, person-level characteristics as predictors and/or outcomes; (b) specifying a multiple-group version; and (c) including multiple indicators. For each extension, we discuss which models need to be run in order to investigate underlying assumptions, and we demonstrate the various modeling options using a motivating example. We provide fully annotated code for lavaan (R-package) and Mplus on an accompanying website.