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
Authors: Agnieszka Król, Philippe Saint-Pierre
Title: SemiMarkov: An R Package for Parametric Estimation in Multi-State Semi-Markov Models
Abstract: Multi-state models provide a relevant tool for studying the observations of a continuoustime process at arbitrary times. Markov models are often considered even if semi-Markov are better adapted in various situations. Such models are still not frequently applied mainly due to lack of available software. We have developed the R package SemiMarkov to fit homogeneous semi-Markov models to longitudinal data. The package performs maximum likelihood estimation in a parametric framework where the distributions of the sojourn times can be chosen between exponential, Weibull or exponentiated Weibull. The package computes and displays the hazard rates of sojourn times and the hazard rates of the semi-Markov process. The effects of covariates can be studied with a Cox proportional hazards model for the sojourn times distributions. The number of covariates and the distribution of sojourn times can be specified for each possible transition providing a great flexibility in a model’s definition. This article presents parametric semi-Markov models and gives a detailed description of the package together with an application to asthma control.

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Paper: SemiMarkov: An R Package for Parametric Estimation in Multi-State Semi-Markov Models     Download PDF (Downloads: 4900)
SemiMarkov_1.4.2.tar.gz: R source package Download (Downloads: 265; 44KB)
v66i06.R: R example code from the paper Download (Downloads: 366; 2KB)

DOI: 10.18637/jss.v066.i06

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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.