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MplusLGM

1.0.0

Automate Latent Growth Mixture Modelling in 'Mplus'

0packages depend
2Kdownloads / year
test coverage
13/13checks pass

Overview

About
Maintained by Olivier Percie du SertFirst published 2025-02-031 releasesCRAN page ↗GitHub ↗

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.

Install

Health

CRAN checks
13OK
Slowest check: 2.0 min · r-oldrel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
11
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 751 wordsVignettesNopkgdown siteNoNEWSYes · 67% structuredCode of conductNoContributing guideNo
Examples that run
22%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Downloads

2K
CRAN downloads in the past year
Rank #21,764 · ~5/day · ~165/mo
Daily download trend is not available in this view yet.
13930 days
52190 days
2K1 year
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Repository

Repository
6Stars
0Forks
0Open issues
0Open PRs
3Releases
266Commits
3Contributors
mplusmplusautomation
License GPL-3.0 · 266 commits · Last activity 2025-07-22

Repository practices

Upstream repositoryBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/olivierpds/mpluslgm on 2026-08-23.

Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
10 external dependencies (excludes base and recommended)
Depends (1)
R >= 4.1.0
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (2)
Maintainer (1)
Author, Maintainer, Copyright holder
Authors (2)
Author, Maintainer, Copyright holder
Copyright holders (1)
Author, Maintainer, Copyright holder
Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.0Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-02-03
Total releases
1 / 1 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 4.1.0
Bundled data
2.7 KB / 1 file
Download size
29 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("MplusLGM")
Percie du Sert, O., & Unrau, J. (2025). MplusLGM: Automate Latent Growth Mixture Modelling in 'Mplus' (Version 1.0.0) [Computer software]. https://doi.org/10.32614/CRAN.package.MplusLGM

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for MplusLGM version 1.0.0 [Data set]. HJJB, LLC. Data release v2026-08-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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