Posterior classification and class-membership probabilities

This function provides the posterior classification and posterior individual class-membership probabilities for external data.

Usage

predictClass(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 outcome(s) and the grouping structure. Names should match exactly.

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 with 2+ng columns: the grouping structure, the predicted class and the ng posterior class-membership probabilities.

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))
predictClass(m2b, newdata=paquid[1:6,])
#>   ID class     prob1     prob2
#> 1  1     1 0.8412575 0.1587425
#> 2  2     1 0.8913364 0.1086636
# }