Recurrent event data frequently arise in biomedical follow-upstudies. The concept of latent classes enables researchers tocharacterize complex population heterogeneity in a plausible andparsimonious way. SLCARE implements a robust and flexible algorithm tocarry out Zhao et al.(2022)’s latent class analysis method for recurrentevent data, where semiparametric multiplicative intensity modeling isadopted. SLCARE returns estimates for non-functional model parametersalong with the associated variance estimates. Visualization tools areprovided to depict the estimated functional model parameters and relatedfunctional quantities of interest. SLCARE also delivers a model checkingplot to help assess the adequacy of the fitted model.
You can install the development version of SLCARE like so:
if (!require("pak",quietly =TRUE))install.packages("pak")pak::pak("qyxxx/SLCARE")Or install SLCARE from CRAN with:
install.packages("SLCARE")