Provide a suite of functions for conducting and automating Latent Growth Modeling (LGM) in 'Mplus', including Growth Curve Model (GCM), Growth-Based Trajectory Model (GBTM) and Latent Class Growth Analysis (LCGA). The package builds upon the capabilities of the 'MplusAutomation' package (Hallquist & Wiley, 2018) to streamline large-scale latent variable analyses. âMplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus.â Structural Equation Modeling, 25(4), 621â638. <doi:10.1080/10705511.2017.1402334> The workflow implemented in this package follows the recommendations outlined in Van Der Nest et al. (2020). âAn Overview of Mixture Modeling for Latent Evolutions in Longitudinal Data: Modeling Approaches, Fit Statistics, and Software.â Advances in Life Course Research, 43, Article 100323. <doi:10.1016/j.alcr.2019.100323>.
Version: 1.0.0 Depends: R (≥ 4.1.0) Imports: MplusAutomation, magrittr, tibble, dplyr, tidyr, tidyselect, stringr, purrr, ggplot2, glue, parallel Published: 2025-02-03 DOI: 10.32614/CRAN.package.MplusLGM Author: Olivier Percie du Sert [aut, cre, cph], Joshua Unrau [aut] Maintainer: Olivier Percie du Sert <olivier.perciedusert at mail.mcgill.ca> BugReports: https://github.com/OlivierPDS/MplusLGM/issues License: GPL (≥ 3) URL: https://github.com/OlivierPDS/MplusLGM NeedsCompilation: no Materials: README NEWS CRAN checks: MplusLGM results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=MplusLGM to link to this page.
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