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Article: Bayesian cure rate model accommodating multiplicative and additive covariates

TitleBayesian cure rate model accommodating multiplicative and additive covariates
Authors
KeywordsAdditive hazards model
cure rate model
markov gamma process
mixture prior
proportional hazards model
Issue Date2009
PublisherInternational Press. The Journal's web site is located at http://www.intlpress.com/SII
Citation
Statistics And Its Interface, 2009, v. 2 n. 4, p. 513-521 How to Cite?
AbstractWe propose a class of Bayesian cure rate models by incorporating a baseline density function as well as multiplicative and additive covariate structures. Our model naturally accommodates zero and non-zero cure rates, which provides an objective way to examine the existence of a survival fraction in the failure time data. An inherent parameter constraint needs to be incorporated into the model formulation due to the additive covariates. Within the Bayesian paradigm, we take a Markov gamma process prior to model the baseline hazard rate, and mixture prior distributions for the parameters in the additive component of the model. We implement a Markov chain Monte Carlo computational scheme to sample from the full conditional distributions of the posterior. We conduct simulation studies to assess the estimation and inference properties of the proposed model, and illustrate it with data from a bone marrow transplant study.
Persistent Identifierhttp://hdl.handle.net/10722/125403
ISSN
2015 Impact Factor: 1.546
2015 SCImago Journal Rankings: 0.481

 

DC FieldValueLanguage
dc.contributor.authorYin, Gen_HK
dc.contributor.authorNieto-Barajas, LEen_HK
dc.date.accessioned2010-10-31T11:29:26Z-
dc.date.available2010-10-31T11:29:26Z-
dc.date.issued2009en_HK
dc.identifier.citationStatistics And Its Interface, 2009, v. 2 n. 4, p. 513-521en_HK
dc.identifier.issn1938-7989en_HK
dc.identifier.urihttp://hdl.handle.net/10722/125403-
dc.description.abstractWe propose a class of Bayesian cure rate models by incorporating a baseline density function as well as multiplicative and additive covariate structures. Our model naturally accommodates zero and non-zero cure rates, which provides an objective way to examine the existence of a survival fraction in the failure time data. An inherent parameter constraint needs to be incorporated into the model formulation due to the additive covariates. Within the Bayesian paradigm, we take a Markov gamma process prior to model the baseline hazard rate, and mixture prior distributions for the parameters in the additive component of the model. We implement a Markov chain Monte Carlo computational scheme to sample from the full conditional distributions of the posterior. We conduct simulation studies to assess the estimation and inference properties of the proposed model, and illustrate it with data from a bone marrow transplant study.-
dc.languageengen_HK
dc.publisherInternational Press. The Journal's web site is located at http://www.intlpress.com/SIIen_HK
dc.relation.ispartofStatistics And Its Interfaceen_HK
dc.rightsStatistics And Its Interface. Copyright © International Press.en_HK
dc.subjectAdditive hazards model-
dc.subjectcure rate model-
dc.subjectmarkov gamma process-
dc.subjectmixture prior-
dc.subjectproportional hazards model-
dc.titleBayesian cure rate model accommodating multiplicative and additive covariatesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1938-7989&volume=2&issue=4&spage=513&epage=521&date=2009&atitle=Bayesian+cure+rate+model+accommodating+multiplicative+and+additive+covariatesen_HK
dc.identifier.emailYin, G: gyin@hku.hken_HK
dc.identifier.authorityYin, G=rp00831en_HK
dc.identifier.hkuros180260en_HK
dc.identifier.volume2en_HK
dc.identifier.issue4-
dc.identifier.spage513en_HK
dc.identifier.epage521en_HK

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