Using informative priors for handling missing data problem in Cox regression

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dc.authoridalkan, nesrin/0000-0003-1452-4780
dc.contributor.authorAlkan, Nesrin
dc.contributor.authorTerzi, Yuksel
dc.contributor.authorCengiz, M. Ali
dc.date.accessioned2025-03-23T19:35:16Z
dc.date.available2025-03-23T19:35:16Z
dc.date.issued2017
dc.departmentSinop Üniversitesi
dc.description.abstractThe aim of this study is to determine the effect of informative priors for variables with missing value and to compare Bayesian Cox regression and Cox regression analysis. For this purpose, firstly simulated data sets with different sample size within different missing rate were generated and each of data sets were analysed by Cox regression and Bayesian Cox regression with informative prior. Secondly lung cancer data set as real data set was used foranalysis. Consequently, using informative priors for variables with missing value solved the missing data problem.
dc.identifier.doi10.1080/03610918.2016.1248568
dc.identifier.endpage7623
dc.identifier.issn0361-0918
dc.identifier.issn1532-4141
dc.identifier.issue10
dc.identifier.scopus2-s2.0-85018306732
dc.identifier.scopusqualityQ2
dc.identifier.startpage7614
dc.identifier.urihttps://doi.org/10.1080/03610918.2016.1248568
dc.identifier.urihttps://hdl.handle.net/11486/5828
dc.identifier.volume46
dc.identifier.wosWOS:000422900600006
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherTaylor & Francis Inc
dc.relation.ispartofCommunications in Statistics-Simulation and Computation
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250323
dc.subjectBayesian Cox regression
dc.subjectCox regression
dc.subjectMissing at random
dc.subjectMissing value
dc.titleUsing informative priors for handling missing data problem in Cox regression
dc.typeArticle

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