MplusLGM: Automate Latent Growth Mixture Modelling in 'Mplus'

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. “MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus.” Structural Equation Modeling, 25(4), 621–638. <doi:10.1080/10705511.2017.1402334> The workflow implemented in this package follows the recommendations outlined in Van Der Nest et al. (2020). “An Overview of Mixture Modeling for Latent Evolutions in Longitudinal Data: Modeling Approaches, Fit Statistics, and Software.” Advances in Life Course Research, 43, Article 100323. <doi:10.1016/j.alcr.2019.100323>.

Getting started

Package details

AuthorOlivier Percie du Sert [aut, cre, cph] (<https://orcid.org/0000-0002-6283-2529>), Joshua Unrau [aut]
MaintainerOlivier Percie du Sert <olivier.perciedusert@mail.mcgill.ca>
LicenseGPL (>= 3)
Version1.0.0
URL https://github.com/OlivierPDS/MplusLGM
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("MplusLGM")

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MplusLGM documentation built on April 3, 2025, 10:49 p.m.