DESCRIPTION

Package: MplusLGM
Type: Package
Title: Automate Latent Growth Mixture Modelling in 'Mplus'
Version: 1.0.0.9000
Authors@R: c(
	person("Olivier", "Percie du Sert", email = "olivier.perciedusert@mail.mcgill.ca", role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0002-6283-2529")),
	person("Joshua", "Unrau", email = "Joshua.unrau@mail.mcgill.ca", role = "aut"))
Description: 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), Latent Class Growth Analysis (LCGA) and Growth Mixture Model (GMM). 
  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>. 
Depends: R (>= 4.1.0),
License: GPL (>= 3)
Imports:
    MplusAutomation,
    magrittr,
    tibble,
    dplyr,
    tidyr,
    tidyselect,
    stringr,
    purrr,
    ggplot2,
    glue,
    parallel
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
URL: https://github.com/OlivierPDS/MplusLGM
BugReports: https://github.com/OlivierPDS/MplusLGM/issues
LazyData: true