predictRE: Predictions of the random-effects

In lcmm: Extended Mixed Models Using Latent Classes and Latent Processes

Description

The function computes the predicted values of the random effects given observed data provided in input. With multiple latent classes, these predictions are averaged over classes using the posterior class-membership probabilities.

Usage

predictRE(model, newdata, subject = NULL)

Arguments

model	an object inheriting from class hlme, lcmm, Jointlcmm or multlcmm representing a general latent class mixed model.
newdata	data frame containing the data from which predictions are to be computed. The data frame should include at least all the covariates listed in model$Xnames2, the marker(s) values and the grouping structure. Names should match exactly the names of the variables in the model.
subject	character specifying the name of the grouping structure. If NULL (the default), the same as in the model will be used.

Value

a matrix containing the grouping structure and the predicted random-effects.

Author(s)

Sasha Cuau, Viviane Philipps, Cecile Proust-Lima

Examples

## Not run: 
library(NormPsy)
paquid$normMMSE <- normMMSE(paquid$MMSE)
paquid$age65 <- (paquid$age - 65)/10
m2b <- hlme(normMMSE ~ age65+I(age65^2)+CEP, random =~ age65+I(age65^2), subject = 'ID',
data = paquid, ng = 2, mixture =~ age65+I(age65^2), B = c(0, 60, 40, 0, -4, 0, -10, 10,
212.869397, -216.421323,456.229910, 55.713775, -145.715516, 59.351000, 10.072221))
predictRE(m2b,newdata=paquid[1:6,])

## End(Not run)

lcmm documentation built on Jan. 31, 2022, 9:06 a.m.