A Bayesian Long-term Survival Model Parametrized in the Cured Fraction

dc.creatorCASTRO, Mario de
dc.creatorCANCHO, Vicente G.
dc.creatorRODRIGUES, Josemar
dc.date.accessioned2012-10-20T03:34:56Z
dc.date.accessioned2018-07-04T15:38:43Z
dc.date.available2012-10-20T03:34:56Z
dc.date.available2018-07-04T15:38:43Z
dc.date.created2012-10-20T03:34:56Z
dc.date.issued2009
dc.identifierBIOMETRICAL JOURNAL, v.51, n.3, p.443-455, 2009
dc.identifier0323-3847
dc.identifierhttp://producao.usp.br/handle/BDPI/28949
dc.identifier10.1002/bimj.200800199
dc.identifierhttp://dx.doi.org/10.1002/bimj.200800199
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1625591
dc.description.abstractThe main goal of this paper is to investigate a cure rate model that comprehends some well-known proposals found in the literature. In our work the number of competing causes of the event of interest follows the negative binomial distribution. The model is conveniently reparametrized through the cured fraction, which is then linked to covariates by means of the logistic link. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis in the proposed model. The procedure is illustrated with a numerical example.
dc.languageeng
dc.publisherWILEY-V C H VERLAG GMBH
dc.relationBiometrical Journal
dc.rightsCopyright WILEY-V C H VERLAG GMBH
dc.rightsrestrictedAccess
dc.subjectBayesian inference
dc.subjectCure rate models
dc.subjectLong-term survival models
dc.subjectNegative binomial distribution
dc.subjectSurvival analysis
dc.titleA Bayesian Long-term Survival Model Parametrized in the Cured Fraction
dc.typeArtículos de revistas


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