lcmm (version 1.2)

lcmm-package: Estimation of Latent Class Mixed Models and Joint Latent Class Mixed Models for quantitative, bounded quantitative, discrete and ordinal outcomes

Description

This package provides functions for the estimation of latent class mixed models (LCMM) and joint latent class mixed models using a maximum likelihood method.

Details

ll{ Package: lcmm Type: Package Version: 1.2 Date: 2011-02-17 License: GPL (>=2.0) LazyLoad: yes } The package includes for the moment only the estimation of latent class linear mixed models for Gaussian longitudinal outcomes using hlme function.

References

Verbeke G and Lesaffre E (1996). A linear mixed-effects model with heterogeneity in the random-effects population. Journal of the American Statistical Association 91, 217-21

Muthen B and Shedden K (1999). Finite mixture modeling with mixture outcomes using the EM algorithm. Biometrics 55, 463-9

Proust C and Jacqmin-Gadda H. Estimation of linear mixed models with a mixture of distribution for the random-effects. Comput Methods Programs Biomed 78:165-73

Examples

data(data_hlme)
m<-hlme(Y~Time+X1+X1_time,mixture=~Time,random=~Time,classmb=~X2+X3,subject=ID,ng=2,data=data_hlme,B=c(0,0,0,30,25,0,-1,0,0,5,0,1,1))
summary(m)
plot(m)
##posterior classification
postprob(m)
plot.postprob(m)
##class-specific predicted trajectories
newdata<-data.frame(intercept=rep(1,100),Time=seq(0,5,length=100),X1=rep(0,100),X1_time=rep(0,100),X2=rep(0,100),X3=rep(0,100))
plot.predict.hlme(m,newdata,"Time","right")