Package: lcmm 2.1.0

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 class mixed models, mixed models for curvilinear outcomes, mixed models for multivariate longitudinal outcomes using a maximum likelihood estimation method (Proust-Lima, Philipps, Liquet (2017) <doi:10.18637/jss.v078.i02>).

Authors:Cecile Proust-Lima [aut, cre], Viviane Philipps [aut], Amadou Diakite [ctb], Benoit Liquet [ctb]

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lcmm.pdf |lcmm.html
lcmm/json (API)
NEWS

# Install 'lcmm' in R:
install.packages('lcmm', repos = c('https://cecileproust-lima.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/cecileproust-lima/lcmm/issues

Uses libs:
  • fortran– Runtime library for GNU Fortran applications
Datasets:
  • data_hlme - Simulated dataset for hlme function
  • data_lcmm - Simulated dataset for lcmm and Jointlcmm functions
  • paquid - Longitudinal data on cognitive and physical aging in the elderly
  • simdataHADS - Simulated dataset simdataHADS

On CRAN:

10.98 score 55 stars 7 packages 210 scripts 2.2k downloads 46 mentions 38 exports 13 dependencies

Last updated 1 months agofrom:4bde57c713. Checks:OK: 4 NOTE: 5. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-win-x86_64NOTEOct 31 2024
R-4.5-linux-x86_64NOTEOct 31 2024
R-4.4-win-x86_64NOTEOct 31 2024
R-4.4-mac-x86_64NOTEOct 31 2024
R-4.4-mac-aarch64NOTEOct 31 2024
R-4.3-win-x86_64OKOct 31 2024
R-4.3-mac-x86_64OKOct 31 2024
R-4.3-mac-aarch64OKOct 31 2024

Exports:BrandomcumincDiffepocedynpredepoceestimatesexternVarfitYgridsearchhlmeItemInfojlcmmJointlcmmlcmmloglikhlmeloglikJointlcmmlogliklcmmloglikmpjlcmmloglikmultlcmmmlcmmmpjlcmmmultlcmmpermutpostprobpredictClasspredictLpredictlinkpredictREpredictYpredictYbackpredictYcondsummaryplotsummarytableVarCovVarCovREVarExplWaldMultxclass

Dependencies:codetoolsdoParallelforeachiteratorslatticemarqLevAlgMatrixmvtnormnlmenumDerivrandtoolboxrngWELLsurvival

Description of lcmm package

Rendered fromlcmm.Rmdusingknitr::rmarkdownon Oct 31 2024.

Last update: 2023-02-17
Started: 2023-02-17

Readme and manuals

Help Manual

Help pageTopics
Estimation of extended mixed models using latent classes and latent processes.lcmm-package
Predicted cumulative incidence of event according to a profile of covariatescuminc
Simulated dataset for hlme functiondata_hlme
Simulated dataset for lcmm and Jointlcmm functionsdata_lcmm
Difference of expected prognostic cross-entropy (EPOCE) estimators and its 95% tracking interval between two joint latent class models estimated with 'Jointlcmm'Diffepoce
Individual dynamic predictions from a joint latent class modeldynpred
Estimators of the Expected Prognostic Observed Cross-Entropy (EPOCE) for evaluating predictive accuracy of joint latent class models estimated using 'Jointlcmm'epoce
Maximum likelihood estimatesestimates estimates.externSurv estimates.externX estimates.hlme estimates.Jointlcmm estimates.lcmm estimates.mpjlcmm estimates.multlcmm
Estimation of a secondary regression model after the estimation of a primary latent class modelexternVar
Marginal predictions of the longitudinal outcome(s) in their natural scale from 'lcmm', 'Jointlcmm' or 'multlcmm' objectsfitY fitY.Jointlcmm fitY.lcmm fitY.multlcmm
For internal use only ....Contlcmm .Ordlcmm .plotbaselinerisk .plotfit .plotlinkfunctionmult .plotlinkfuntion .plotpostprob .plotresid .plotsurvival Brandom C_calculustransfo C_cvpl C_hetmixcont C_hetmixcontmult C_hetmixlin C_hetmixord C_jointhet C_postprob2 C_predictcont C_predictmult factor.names ForInternalUse mixture risqcum_spl risq_spl
Automatic grid searchgridsearch
Estimation of latent class linear mixed modelshlme
Conditional probabilities and item information given specified latent process values for 'lcmm' or 'multlcmm' object with ordinal outcomes.ItemInfo
Estimation of joint latent class models for longitudinal and time-to-event datajlcmm Jointlcmm
Estimation of mixed-effect models and latent class mixed-effect models for different types of outcomes (continuous Gaussian, continuous non-Gaussian or ordinal)lcmm
Wrapper to the Fortran subroutines computing the log-likelihoodloglik loglikhlme loglikJointlcmm logliklcmm loglikmpjlcmm loglikmultlcmm
Estimation of multivariate joint latent class mixed modelsmpjlcmm
Estimation of multivariate mixed-effect models and multivariate latent class mixed-effect models for multivariate longitudinal outcomes of possibly multiple types (continuous Gaussian, continuous non-Gaussian/curvilinear, ordinal) that measure the same underlying latent process.mlcmm multlcmm
Longitudinal data on cognitive and physical aging in the elderlypaquid
Permutation of the latent classespermut
Plot of a fitted modelplot plot.externSurv plot.externX plot.hlme plot.Jointlcmm plot.lcmm plot.mpjlcmm plot.multlcmm
Plot of predicted cumulative incidences according to a profile of covariatesplot.cuminc
Plotsplot.Diffepoce plot.epoce plot.pred.accuracy
Plot of individual dynamic predictionsplot.dynpred
Plot of information functionsplot.ItemInfo
Plot of predicted trajectories and link functionsplot.predict plot.predictL plot.predictL.Jointlcmm plot.predictL.lcmm plot.predictL.multlcmm plot.predictlink plot.predictlink.Jointlcmm plot.predictlink.lcmm plot.predictlink.multlcmm plot.predictY plot.predictY.hlme plot.predictY.Jointlcmm plot.predictY.lcmm plot.predictY.multlcmm plot.predictYcond
Posterior classification stemmed from a 'hlme', 'lcmm', 'multlcmm' or 'Jointlcmm' estimationpostprob postprob.externSurv postprob.externX postprob.hlme postprob.Jointlcmm postprob.lcmm postprob.mpjlcmm postprob.multlcmm
Posterior classification and class-membership probabilitiespredictClass
Class-specific marginal predictions in the latent process scale for 'lcmm', 'Jointlcmm' and 'multlcmm' objectspredictL predictL.Jointlcmm predictL.lcmm predictL.multlcmm
Confidence intervals for the estimated link functions from 'lcmm', 'Jointlcmm' and 'multlcmm'predictlink predictlink.Jointlcmm predictlink.lcmm predictlink.multlcmm
Predictions of the random-effectspredictRE
Predictions (marginal and possibly subject-specific in some cases) of a 'hlme', 'lcmm', 'multlcmm' or 'Jointlcmm' object in the natural scale of the longitudinal outcome(s) computed from a profile of covariates (marginal) or individual data (subject specific in case of 'hlme').predictY predictY.hlme predictY.Jointlcmm predictY.lcmm predictY.multlcmm
Marginal predictions in the natural scale of a pre-transformed outcomepredictYback
Conditional predictions of a 'lcmm', 'multlcmm' or 'Jointlcmm' object in the natural scale of the longitudinal outcome(s) for specified latent process values.predictYcond
Brief summary of a 'hlme', 'lcmm', 'Jointlcmm','multlcmm', 'epoce' or 'Diffepoce' objectsprint.Diffepoce print.epoce print.externSurv print.externX print.hlme print.Jointlcmm print.lcmm print.mpjlcmm print.multlcmm
Simulated dataset simdataHADSsimdataHADS
Data simulation according to models from lcmm packagesimulate.lcmm
Standard methods for estimated modelscoef.externSurv coef.externX coef.hlme coef.Jointlcmm coef.lcmm coef.mpjlcmm coef.multlcmm fitted.hlme fitted.Jointlcmm fitted.lcmm fitted.multlcmm fixef.hlme fixef.Jointlcmm fixef.lcmm fixef.multlcmm ranef.hlme ranef.Jointlcmm ranef.lcmm ranef.multlcmm residuals.hlme residuals.Jointlcmm residuals.lcmm residuals.multlcmm StandardMethods vcov.externSurv vcov.externX vcov.hlme vcov.Jointlcmm vcov.lcmm vcov.mpjlcmm vcov.multlcmm
Summary of a 'hlme', 'lcmm', 'Jointlcmm', 'multlcmm', 'mpjlcmm', 'externSurv', 'externX' 'epoce' or 'Diffepoce' objectssummary.Diffepoce summary.epoce summary.externSurv summary.externX summary.hlme summary.Jointlcmm summary.lcmm summary.mpjlcmm summary.multlcmm
Summary of modelssummaryplot
Summary of modelssummarytable
Update the longitudinal submodelsupdate.mpjlcmm
Variance-covariance of the estimatesVarCov
Estimates, standard errors and Wald test for the parameters of the variance-covariance matrix of the random effects.VarCovRE VarCovRE.hlme VarCovRE.Jointlcmm VarCovRE.lcmm VarCovRE.multlcmm
Percentage of variance explained by the (latent class) linear mixed model regressionVarExpl VarExpl.hlme VarExpl.Jointlcmm VarExpl.lcmm VarExpl.multlcmm
Multivariate Wald TestWaldMult
Cross classificationsxclass