lcmm: Extended Mixed Models Using Latent Classes and Latent Processes

Estimation of various extensions of the mixed models including latent class mixed models, joint latent latent class mixed models, mixed models for curvilinear outcomes or mixed models for multivariate longitudinal outcomes using a maximum likelihood estimation method (Proust-Lima, Philipps, Liquet (2017) <doi:10.18637/jss.v078.i02>).

Version: 1.9.5
Depends: R (≥ 3.5.0), survival (≥ 2.37-2), parallel, mvtnorm, randtoolbox
Imports: nlme
Suggests: knitr, rmarkdown, lattice, NormPsy, ggplot2, ggpubr, dplyr, splines, gridExtra
Published: 2022-01-31
Author: Cecile Proust-Lima, Viviane Philipps, Amadou Diakite and Benoit Liquet
Maintainer: Cecile Proust-Lima <cecile.proust-lima at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
NeedsCompilation: yes
Citation: lcmm citation info
Materials: NEWS
In views: Cluster
CRAN checks: lcmm results


Reference manual: lcmm.pdf
Vignettes: Longitudinal IRT with multlcmm
Latent class model with hlme
Latent process model with lcmm
Latent process model with multlcmm
Usual problems


Package source: lcmm_1.9.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): lcmm_1.9.5.tgz, r-release (x86_64): lcmm_1.9.5.tgz, r-oldrel: lcmm_1.9.5.tgz
Old sources: lcmm archive

Reverse dependencies:

Reverse imports: NormPsy, pencal, SlaPMEG
Reverse suggests: JLPM, latrend


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