Random effects in promotion time cure rate models

dc.contributor.authorCarvalho Lopes C.M.
dc.contributor.authorBolfarine H.
dc.date.accessioned2024-03-13T01:09:33Z
dc.date.available2024-03-13T01:09:33Z
dc.date.issued2012
dc.description.abstractIn this paper, a survival model with long-term survivors and random effects, based on the promotion time cure rate model formulation for models with a surviving fraction is investigated. We present Bayesian and classical estimation approaches. The Bayesian approach is implemented using a Markov chain Monte Carlo (MCMC) based on the Metropolis-Hastings algorithms. For the second one, we use restricted maximum likelihood (REML) estimators. A simulation study is performed to evaluate the accuracy of the applied techniques for the estimates and their standard deviations. An example on an oropharynx cancer study is used to illustrate the model and the estimation approaches considered in the study. © 2011 Elsevier B.V. All rights reserved.
dc.description.firstpage75
dc.description.issuenumber1
dc.description.lastpage87
dc.description.volume56
dc.identifier.doi10.1016/j.csda.2011.05.008
dc.identifier.issn0167-9473
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/36892
dc.relation.ispartofComputational Statistics and Data Analysis
dc.rightsAcesso Restrito
dc.subject.otherlanguageLong-term survivors
dc.subject.otherlanguageMetropolis-Hastings
dc.subject.otherlanguageRandom effects
dc.subject.otherlanguageREML
dc.titleRandom effects in promotion time cure rate models
dc.typeArtigo
local.scopus.citations15
local.scopus.eid2-s2.0-80052036216
local.scopus.subjectBayesian approaches
local.scopus.subjectCure rate
local.scopus.subjectLong-term survivors
local.scopus.subjectMarkov chain monte carlo
local.scopus.subjectMetropolis-Hastings
local.scopus.subjectMetropolis-Hastings algorithm
local.scopus.subjectOropharynx cancer
local.scopus.subjectRandom effects
local.scopus.subjectREML
local.scopus.subjectRestricted maximum likelihood
local.scopus.subjectSimulation studies
local.scopus.subjectStandard deviation
local.scopus.subjectSurvival model
local.scopus.subjectSurviving fractions
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=80052036216&origin=inward
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