lcmm (version 1.4-1)

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

Description

This function provides informations about the posterior classification stemmed from a hlme, lcmm or Jointlcmm object.

Usage

postprob(x,...)
postprob.hlme(x,...)
postprob.lcmm(x,...)
postprob.Jointlcmm(x,...)

Arguments

x

an object inheriting from classes hlme, lcmm or Jointlcmm representing respectively a fitted latent class linear mixed-effects model, a more general latent class mixed model or a joint latent class model.

...

further arguments to be passed to or from other methods. They are ignored in this function.

Details

This function provides the number of subjects classified a posteriori in each latent class, and the classification table that contains the mean of the posterior probability of belonging to each latent class over the subjects classified in each of the latent classes. This table aims at evaluating the quality of the posterior classification. For hlme, lcmm objects, the posterior classification and the classification table are derived from the posterior class-membership probabilities given the vector of repeated measures that are contained in pprob output matrix. For a Jointlcmm object, the first posterior classification and the classification table are derived from the posterior class-membership probabilities given the vector of repeated measures and the time-to-event information (that are contained in columns probYT1, probYT2, etc in pprob output matrix). The second posterior classification is derived from the posterior class-membership probabilities given only the vector of repeated measures (that are contained in columns probY1, probY2, etc in pprob output matrix).

See Also

Jointlcmm, lcmm, hlme,plot.postprob

Examples

data(data_hlme)
m<-lcmm(Y~Time+X1+X1_time,mixture=~Time,random=~Time,classmb=~X2+X3,
subject='ID',ng=2,data=data_hlme)
postprob(m)