Year: 2025
Type: article
Abstract: 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. This article introduces the R package SLCARE, which implements a robust and flexible algorithm to carry out Zhao, Peng, and Hanfelt (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 and $p$ values. 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.
Source: The R Journal
DOI: 10.32614/rj-2024-030
Authors: Qi Yu, Limin Peng
Institution: Emory University
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4411432887