title: tdc.msm: an R library for the analysis of multi-state survival data.
abstract: The aim of this paper is to present an R library, called tdc.msm, developed to analyze multi-state survival data. In this library, the time-dependent regression model and multi-state models are included as two possible approaches for such data. For the multi-state modelling five different models are considered, allowing the user to choose between Markov and semi-Markov property, as well as to use homogeneous or non-homogeneous models. Specifically, the following multi-state models in continuous time were implemented: Cox Markov model; Cox semi-Markov model; homogeneous Markov model; non-homogeneous piecewise model and non-parametric Markov model. This software can be used to fit multi-state models with one initial state (e.g., illness diagnosis), a finite number of intermediate states, representing, for example, a change of treatment, and one absorbing state corresponding to a terminal event of interest. Graphical output includes survival estimates, transition probabilities estimates and smooth log hazard for continuous covariates.
authors.affiliation: Department of Mathematics for Science and Technology, University of Minho, 4810 Azurém, Guimarães, Portugal. lmachado@mct.uminho.pt
authors.forename: Luís
authors.initials: L
authors.lastname: Meira-Machado
authors.forename: Carmen
authors.initials: C
authors.lastname: Cadarso-Suárez
authors.forename: Jacobo
authors.initials: J
authors.lastname: de Uña-Alvarez
mesh_terms: D016208:Databases, Factual; D018450:Disease Progression; D006801:Humans; D008390:Markov Chains; D016016:Proportional Hazards Models; D012984:Software; D013030:Spain; D016019:Survival Analysis