Semiparametric Latent Class Analysis of Recurrent Events.

SLCARE

Recurrent event data frequently arise in biomedical follow-up studies. The concept of latent classes enables researchers to characterize complex population heterogeneity in a plausible and parsimonious way. SLCARE implements a robust and flexible algorithm to carry out Zhao et al.(2022)’s latent class analysis method for recurrent event data, where semiparametric multiplicative intensity modeling is adopted. SLCARE returns estimates for non-functional model parameters along with the associated variance estimates. Visualization tools are provided to depict the estimated functional model parameters and related functional quantities of interest. SLCARE also delivers a model checking plot to help assess the adequacy of the fitted model.

Installation

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")