The R package LSJM for fitting location-scale joint models for a longitudinal marker and complex survival data

Abstract

The LSJM R package provides a series of functions to estimate models based on location-scale linear mixed model and location-scale joint model theory. For longitudinal data, it includes the estimation of location-scale mixed models with subject-specific residual variance that can be time-dependent or distinguish within-visit and between-visits variability. When survival data is considered, implemented joint models handle competing risks as well as semi-competing risks possibly with interval-censored data through the use of a illness-death sub-model. They incorporate flexible dependence structure between the longitudinal marker and the times-to-events through the current value, the slope and/or the residual variability of the marker. Maximum likelihood estimators are obtained using the Marquardt-Levenberg algorithm with stringent convergence criteria. The package also provides several post-fit functions including goodness-of-fit analyses and individual dynamic predictions. Some examples on real data allows to illustrates the use of this package.