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dc.contributor.authorAzarang, L.
dc.contributor.authorOviedo de la Fuente, M.
dc.description.abstractThe progressive illness-death model is frequently used in medical applications. For example, the model may be used to describe the disease process in cancer studies. We have developed a new R package called idmTPreg to estimate regression coefficients in datasets that can be described by the progressive illness-death model. The motivation for the development of the package is a recent contribution that enables the estimation of possibly time-varying covariate effects on the transition probabilities for a progressive illness-death data. The main feature of the package is that it befits both non-Markov and Markov progressive illness-death data. The package implements the introduced estimators obtained using a direct binomial regression approach. Also, variance estimates and confidence bands are implemented in the package. This article presents guidelines for the use of the package.en_US
dc.description.sponsorshipBERC 2014-2017 SEV-2013-0323 MTM2016-76969-P FP7/2011: Marie Curie Initial Training Network MEDIASRESen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.titleidmTPreg: Regression Model for Progressive Illness Death Dataen_US
dc.journal.titleThe R Journalen_US

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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España