Function reference • lcmm

Presentation

lcmm-package: Estimation of extended mixed models using latent classes and latent processes.

Data

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

Estimation

hlme(): Estimation of latent class linear mixed models

lcmm(): Estimation of mixed-effect models and latent class mixed-effect models for different types of outcomes (continuous Gaussian, continuous non-Gaussian or ordinal)

multlcmm() mlcmm(): 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.

Jointlcmm() jlcmm(): Estimation of joint latent class models for longitudinal and time-to-event data

mpjlcmm(): Estimation of multivariate joint latent class mixed models

externVar(): Estimation of secondary regression models after the estimation of a primary latent class model

gridsearch(): Automatic grid search

loglikhlme() logliklcmm() loglikmultlcmm() loglikJointlcmm() loglikmpjlcmm(): Wrapper to the Fortran subroutines computing the log-likelihood

permut(): Permutation of the latent classes

Extract outputs

estimates(): Maximum likelihood estimates

print(<lcmm>): Brief summary of a hlme, lcmm, Jointlcmm,multlcmm, epoce or Diffepoce objects

postprob(): Posterior classification stemmed from a hlme, lcmm, multlcmm or Jointlcmm estimation

coef(<hlme>): Standard methods for estimated models

summary(<lcmm>): Summary of a hlme, lcmm, Jointlcmm, multlcmm, mpjlcmm, externSurv, externX epoce or Diffepoce objects

summarytable(): Summary of models

update(<mpjlcmm>): Update the longitudinal submodels

VarCov(): Variance-covariance of the estimates

xclass(): Cross classifications

Predictions and computations

cuminc(): Predicted cumulative incidence of event according to a profile of covariates

Diffepoce(): Difference of expected prognostic cross-entropy (EPOCE) estimators and its 95% tracking interval between two joint latent class models estimated with Jointlcmm

dynpred(): Individual dynamic predictions from a joint latent class model

epoce(): Estimators of the Expected Prognostic Observed Cross-Entropy (EPOCE) for evaluating predictive accuracy of joint latent class models estimated using Jointlcmm

ItemInfo(): Conditional probabilities and item information given specified latent process values for lcmm or multlcmm object with ordinal outcomes.

predictClass(): Posterior classification and class-membership probabilities

predictlink(): Confidence intervals for the estimated link functions from lcmm, Jointlcmm and multlcmm

predictL(): Class-specific marginal predictions in the latent process scale for lcmm, Jointlcmm and multlcmm objects

predictRE(): Predictions of the random-effects

predictY(): 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).

predictYcond(): Conditional predictions of a lcmm, multlcmm or Jointlcmm object in the natural scale of the longitudinal outcome(s) for specified latent process values.

predictYback(): Marginal predictions in the natural scale of a pre-trandormed outcome

Plots

plot(<hlme>) plot(<lcmm>) plot(<multlcmm>) plot(<Jointlcmm>) plot(<mpjlcmm>) plot(<externSurv>) plot(<externX>): Plot of a fitted model

plot(<cuminc>): Plot of predicted cumulative incidences according to a profile of covariates

plot(<dynpred>): Plot of individual dynamic predictions

plot(<Diffepoce>) plot(<epoce>): Plots

plot(<ItemInfo>): Plot of information functions

plot(<predictL>) plot(<predictY>) plot(<predictYcond>): Plot of predicted trajectories and link functions

summaryplot(): Summary of models

Evaluation and tests

fitY(): Marginal predictions of the longitudinal outcome(s) in their natural scale from lcmm, Jointlcmm or multlcmm objects

VarExpl(): Percentage of variance explained by the (latent class) linear mixed model regression

VarCovRE(): Estimates, standard errors and Wald test for the parameters of the variance-covariance matrix of the random effects.

WaldMult(): Multivariate Wald Test

Simulation

simulate(<lcmm>): Data simulation according to models from lcmm package

Internal functions

ForInternalUse mixture factor.names .Ordlcmm .Contlcmm risq_spl risqcum_spl .plotresid .plotpostprob .plotfit .plotlinkfuntion .plotlinkfunctionmult .plotbaselinerisk .plotsurvival C_hetmixlin C_hetmixcont C_hetmixord C_hetmixcontmult C_jointhet C_predictcont C_predictmult C_postprob2 C_cvpl C_calculustransfo Brandom: For internal use only ...