Joint Latent Process Models

Estimation of extended joint models with shared random effects. Longitudinal data are handled in latent process models for continuous (Gaussian or curvilinear) and ordinal outcomes while proportional hazard models are used for the survival part. We propose a frequentist approach using maximum likelihood estimation. See Saulnier et al, 2022 .

Installation

To install the CRAN version, use :

install.packages("JLPM")

To get the most recent update, install it from github :

remotes::install_github("VivianePhilipps/JLPM")

Documentation

Some vignettes are available on the JLPM website https://VivianePhilipps.github.io/JLPM/.