Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
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Authors: Luís Filipe Meira Machado, Javier Roca-Pardiñas
Title: p3state.msm: Analyzing Survival Data from an Illness-Death Model
Abstract: In longitudinal studies of disease, patients can experience several events across a followup 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 nonMarkov 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.

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Paper: p3state.msm: Analyzing Survival Data from an Illness-Death Model     Download PDF (Downloads: 9080)
p3state.msm_1.2.tar.gz: R source package Download (Downloads: 1264; 13KB)
v38i03.R: R example code from the paper Download (Downloads: 1398; 598B)

DOI: 10.18637/jss.v038.i03

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.