Bayesian analysis of survival data with missing censoring indicators

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dc.contributor.authorBrownstein, Naomi C.
dc.contributor.authorBunn, Veronica
dc.contributor.authorCastro, Luis M.
dc.contributor.authorSinha, Debajyoti
dc.date.accessioned2024-01-10T13:09:59Z
dc.date.available2024-01-10T13:09:59Z
dc.date.issued2021
dc.description.abstractIn some large clinical studies, it may be impractical to perform the physical examination to every subject at his/her last monitoring time in order to diagnose the occurrence of the event of interest. This gives rise to survival data with missing censoring indicators where the probability of missing may depend on time of last monitoring and some covariates. We present a fully Bayesian semi-parametric method for such survival data to estimate regression parameters of the proportional hazards model of Cox. Theoretical investigation and simulation studies show that our method performs better than competing methods. We apply the proposed method to analyze the survival data with missing censoring indicators from the Orofacial Pain: Prospective Evaluation and Risk Assessment study.
dc.description.funderChilean government
dc.description.funderNational Cancer Institute
dc.description.funderGustavus and Louise Pfeiffer Research Foundation
dc.description.funderMillennium Science Initiative of the Ministry of Economy, Development, and Tourism
dc.fechaingreso.objetodigital2024-05-28
dc.format.extent11 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1111/biom.13280
dc.identifier.eissn1541-0420
dc.identifier.issn0006-341X
dc.identifier.pubmedidMEDLINE:32282929
dc.identifier.urihttps://doi.org/10.1111/biom.13280
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/77739
dc.identifier.wosidWOS:000530406300001
dc.information.autorucFacultad de Matemáticas; Castro Cepero, Luis Mauricio; S/I; 151425
dc.issue.numero1
dc.language.isoen
dc.nota.accesocontenido completo
dc.pagina.final315
dc.pagina.inicio305
dc.publisherWILEY
dc.revistaBIOMETRICS
dc.rightsacceso abierto
dc.subjectinterim event adjudication
dc.subjectmissing data
dc.subjectproportional hazards
dc.subjectsemiparametric Bayes
dc.subjecttime-to-event
dc.subjectMODELS
dc.subject.ods05 Gender Equality
dc.subject.odspa05 Igualdad de género
dc.titleBayesian analysis of survival data with missing censoring indicators
dc.typeartículo
dc.volumen77
sipa.codpersvinculados151425
sipa.indexWOS
sipa.indexPubmed
sipa.trazabilidadCarga SIPA;09-01-2024
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