p3state.msm: Analyzing survival data from an illness-death model

In longitudinal studies of disease,patients can experience several events across a follow-up period. analysis of such studies can be successfully performed by multi-state models. in the multi-state framework,issues of interest include the study of the relationship between covariates and disease evolution,estimation of transition probabilities,and survival rates. this paper introduces p3state.msm,a software application for r which performs inference in an illness-death model. it describes the capabilities of the program for estimating semi-parametric regression models and for implementing nonparametric estimators for several quantities. the main feature of the package is its ability for obtaining non-markov estimates for the transition probabilities. moreover,the methods can also be used in progressive three-state models. in such a model,estimators for other quantities,such as the bivariate distribution function (for sequentially ordered events),are also given. the software is illustrated using data from the stanford heart transplant study.