drizopoulos/JM: Joint Models for Longitudinal Survival Data

the current value of thelongitudinal outcomes， the Weibull hazard and a completelyunspecified function (i.e.， a discrete function with point masses at the unique eventtimes). The user has now the option to define custom transformation functions for the terms ofthe longitudinal submodel that enter into the linear predictor of the survival submodel(arguments derivForm， a piecewise-constant function， using argument InterFact interactions terms can beconsidered. Dynamic predictions Function survfitJM() computes dynamic survival probabilities. Function predict() computes dynamic predictions for the longitudinal outcome. Function aucJM() calculates time-dependent AUCs for joint models， when focusis on the survival outcome and we wish to account for the effect of an endogenous(aka internal) time-dependent covariates measured with error. Second， parameterization). For example， JM: Joint Models for Longitudinal and Survival Data using Maximum Likelihood Description This repository contains the source files for the R package JM .This package fits joint models for longitudinal and time-to-event data using maximumlikelihood. These models are applicable in mainly two settings. First， and functionrocJM() calculates the corresponding time-dependent sensitivities and specifies. Function prederrJM() calculates prediction errors for joint models. ， the velocity of the longitudinal outcome (slope)， when focus is on thelongitudinal outcome and we wish to correct for nonrandom dropout. The basic joint-model-fitting function of the package is jointModel(). This accepts asmain arguments a linear mixed model fitted by function lme() from the nlme package and a Cox model fitted usingfunction coxph() from the survival package. Basic Features It can fit joint models for a single continuous longitudinal outcome and a time-to-eventoutcome. For the survival outcome a relative risk models is assumed. The method argument ofjointModel() can be used to define the type of baseline hazard function. Options are aB-spline approximation， the area underthe longitudinal profile. From the aforementioned options， in each model up to two termscan be included. In addition，。