Predictions of the random-effects

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

Sasha Cuau, Viviane Philipps, Cecile Proust-Lima

Examples

# \dontrun{
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,])
#>   ID  intercept     age65 I(age65^2)
#> 1  1 -12.085190  7.525836  -1.955429
#> 6  2  -9.207263 -6.126612   1.325377
# }