p3state.msm: Analyzing Survival Data from an Illness-Death Model

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 evo...

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Bibliographic Details
Main Authors: Luís Filipe Meira Machado, Javier Roca-Pardiñas
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2011-01-01
Series:Journal of Statistical Software
Subjects:
Online Access:http://www.jstatsoft.org/v38/i03/paper
Description
Summary: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.
ISSN:1548-7660