A multivariate survival model induced by discrete frailty

Detalhes bibliográficos
Autor(a) principal: Cancho, Vicente G.
Data de Publicação: 2020
Outros Autores: Suzuki, Adriano K., Barriga, Gladys D. C. [UNESP], Espirito Santo, Ana P. J. do
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1080/03610918.2020.1806323
http://hdl.handle.net/11449/195590
Resumo: Frailty models are generally used to model heterogeneity and dependence between individuals. The distribution of the frailty variable is often assumed to be continuous. However, there are situations where a discretely-distributed frailty may be appropriate. On the other hand, when a cure rate is present in survival data, these continuous distributions may not be appropriate since individuals with long-term survival times encompass zero frailty. Having zero frailty can be interpreted as being immune or cured (long-term survivors). In this paper, we propose a new multivariate survival model induced by frailty for multivariate lifetime data in the presence of surviving fractions and examine some of its properties. The inferential approach exploits the Bayesian methods. We provide some simulation results to assess the performance of the proposed model. Furthermore, we illustrate the performance of the proposed model by means of a real data set.
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spelling A multivariate survival model induced by discrete frailtyCured fractionFrailty modelsGibbs samplingMultivariate survival modelsFrailty models are generally used to model heterogeneity and dependence between individuals. The distribution of the frailty variable is often assumed to be continuous. However, there are situations where a discretely-distributed frailty may be appropriate. On the other hand, when a cure rate is present in survival data, these continuous distributions may not be appropriate since individuals with long-term survival times encompass zero frailty. Having zero frailty can be interpreted as being immune or cured (long-term survivors). In this paper, we propose a new multivariate survival model induced by frailty for multivariate lifetime data in the presence of surviving fractions and examine some of its properties. The inferential approach exploits the Bayesian methods. We provide some simulation results to assess the performance of the proposed model. Furthermore, we illustrate the performance of the proposed model by means of a real data set.Univ Sao Paulo, Dept Appl Math & Stat, Ave Trabalhador Saocarlense 400, BR-13566590 Sao Paulo, BrazilSao Paulo State Univ, Fac Engn Bauru, Sao Paulo, BrazilSao Paulo State Univ, Fac Engn Bauru, Sao Paulo, BrazilTaylor & Francis IncUniversidade de São Paulo (USP)Universidade Estadual Paulista (Unesp)Cancho, Vicente G.Suzuki, Adriano K.Barriga, Gladys D. C. [UNESP]Espirito Santo, Ana P. J. do2020-12-10T17:39:43Z2020-12-10T17:39:43Z2020-08-11info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article19http://dx.doi.org/10.1080/03610918.2020.1806323Communications In Statistics-simulation And Computation. Philadelphia: Taylor & Francis Inc, 19 p., 2020.0361-0918http://hdl.handle.net/11449/19559010.1080/03610918.2020.1806323WOS:000558961300001Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCommunications In Statistics-simulation And Computationinfo:eu-repo/semantics/openAccess2021-10-23T09:55:35Zoai:repositorio.unesp.br:11449/195590Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:13:36.015135Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A multivariate survival model induced by discrete frailty
title A multivariate survival model induced by discrete frailty
spellingShingle A multivariate survival model induced by discrete frailty
Cancho, Vicente G.
Cured fraction
Frailty models
Gibbs sampling
Multivariate survival models
title_short A multivariate survival model induced by discrete frailty
title_full A multivariate survival model induced by discrete frailty
title_fullStr A multivariate survival model induced by discrete frailty
title_full_unstemmed A multivariate survival model induced by discrete frailty
title_sort A multivariate survival model induced by discrete frailty
author Cancho, Vicente G.
author_facet Cancho, Vicente G.
Suzuki, Adriano K.
Barriga, Gladys D. C. [UNESP]
Espirito Santo, Ana P. J. do
author_role author
author2 Suzuki, Adriano K.
Barriga, Gladys D. C. [UNESP]
Espirito Santo, Ana P. J. do
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade de São Paulo (USP)
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Cancho, Vicente G.
Suzuki, Adriano K.
Barriga, Gladys D. C. [UNESP]
Espirito Santo, Ana P. J. do
dc.subject.por.fl_str_mv Cured fraction
Frailty models
Gibbs sampling
Multivariate survival models
topic Cured fraction
Frailty models
Gibbs sampling
Multivariate survival models
description Frailty models are generally used to model heterogeneity and dependence between individuals. The distribution of the frailty variable is often assumed to be continuous. However, there are situations where a discretely-distributed frailty may be appropriate. On the other hand, when a cure rate is present in survival data, these continuous distributions may not be appropriate since individuals with long-term survival times encompass zero frailty. Having zero frailty can be interpreted as being immune or cured (long-term survivors). In this paper, we propose a new multivariate survival model induced by frailty for multivariate lifetime data in the presence of surviving fractions and examine some of its properties. The inferential approach exploits the Bayesian methods. We provide some simulation results to assess the performance of the proposed model. Furthermore, we illustrate the performance of the proposed model by means of a real data set.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-10T17:39:43Z
2020-12-10T17:39:43Z
2020-08-11
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1080/03610918.2020.1806323
Communications In Statistics-simulation And Computation. Philadelphia: Taylor & Francis Inc, 19 p., 2020.
0361-0918
http://hdl.handle.net/11449/195590
10.1080/03610918.2020.1806323
WOS:000558961300001
url http://dx.doi.org/10.1080/03610918.2020.1806323
http://hdl.handle.net/11449/195590
identifier_str_mv Communications In Statistics-simulation And Computation. Philadelphia: Taylor & Francis Inc, 19 p., 2020.
0361-0918
10.1080/03610918.2020.1806323
WOS:000558961300001
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Communications In Statistics-simulation And Computation
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 19
dc.publisher.none.fl_str_mv Taylor & Francis Inc
publisher.none.fl_str_mv Taylor & Francis Inc
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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