Bayesian joint modeling of longitudinal and spatial survival AIDS data
Autor(a) principal: | |
---|---|
Data de Publicação: | 2016 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.26/17916 |
Resumo: | "Joint analysis of longitudinal and survival data has received increasing attention in the recent years, especially for analyzing cancer and AIDS data. As both repeated measurements (longitudinal) and time-to-event (survival) outcomes are observed in an individual, a joint modeling is more appropriate because it takes into account the dependence between the two types of responses, which are often analyzed separately. We propose a Bayesian hierarchical model for jointly modeling longitudinal and survival data considering functional time and spatial frailty effects, respectively. That is, the proposed model deals with nonlinear longitudinal effects and spatial survival effects accounting for the unobserved heterogeneity among individuals living in the same region. This joint approach is applied to a cohort study of patients with HIV/AIDS in Brazil during the years 2002–2006. Our Bayesian joint model presents considerable improvements in the estimation of survival times of the Brazilian HIV/AIDS patients when compared with those ones obtained through a separate survival model and shows that the spatial risk of death is the same across the different Brazilian states." |
id |
RCAP_b012850a17dcc794e2f0c887124840d5 |
---|---|
oai_identifier_str |
oai:comum.rcaap.pt:10400.26/17916 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Bayesian joint modeling of longitudinal and spatial survival AIDS dataJoint modelRepeated measurementsBayesian analysisTime-to-event dataSpatial frailty"Joint analysis of longitudinal and survival data has received increasing attention in the recent years, especially for analyzing cancer and AIDS data. As both repeated measurements (longitudinal) and time-to-event (survival) outcomes are observed in an individual, a joint modeling is more appropriate because it takes into account the dependence between the two types of responses, which are often analyzed separately. We propose a Bayesian hierarchical model for jointly modeling longitudinal and survival data considering functional time and spatial frailty effects, respectively. That is, the proposed model deals with nonlinear longitudinal effects and spatial survival effects accounting for the unobserved heterogeneity among individuals living in the same region. This joint approach is applied to a cohort study of patients with HIV/AIDS in Brazil during the years 2002–2006. Our Bayesian joint model presents considerable improvements in the estimation of survival times of the Brazilian HIV/AIDS patients when compared with those ones obtained through a separate survival model and shows that the spatial risk of death is the same across the different Brazilian states."WileyRepositório ComumMartins, RuiSilva, Giovani L.Andreozzi, Valeska2017-08-31T00:30:12Z2016-08-01T00:00:00Z2016-08-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.26/17916engMartins, R., Silva, G. L., and Andreozzi, V. (2016) Bayesian joint modeling of longitudinal and spatial survival AIDS data. Statist. Med., 35: 3368–3384. doi: 10.1002/sim.69371097-025810.1002/sim.6937info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-10-06T14:52:47Zoai:comum.rcaap.pt:10400.26/17916Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T15:08:46.741443Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Bayesian joint modeling of longitudinal and spatial survival AIDS data |
title |
Bayesian joint modeling of longitudinal and spatial survival AIDS data |
spellingShingle |
Bayesian joint modeling of longitudinal and spatial survival AIDS data Martins, Rui Joint model Repeated measurements Bayesian analysis Time-to-event data Spatial frailty |
title_short |
Bayesian joint modeling of longitudinal and spatial survival AIDS data |
title_full |
Bayesian joint modeling of longitudinal and spatial survival AIDS data |
title_fullStr |
Bayesian joint modeling of longitudinal and spatial survival AIDS data |
title_full_unstemmed |
Bayesian joint modeling of longitudinal and spatial survival AIDS data |
title_sort |
Bayesian joint modeling of longitudinal and spatial survival AIDS data |
author |
Martins, Rui |
author_facet |
Martins, Rui Silva, Giovani L. Andreozzi, Valeska |
author_role |
author |
author2 |
Silva, Giovani L. Andreozzi, Valeska |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Repositório Comum |
dc.contributor.author.fl_str_mv |
Martins, Rui Silva, Giovani L. Andreozzi, Valeska |
dc.subject.por.fl_str_mv |
Joint model Repeated measurements Bayesian analysis Time-to-event data Spatial frailty |
topic |
Joint model Repeated measurements Bayesian analysis Time-to-event data Spatial frailty |
description |
"Joint analysis of longitudinal and survival data has received increasing attention in the recent years, especially for analyzing cancer and AIDS data. As both repeated measurements (longitudinal) and time-to-event (survival) outcomes are observed in an individual, a joint modeling is more appropriate because it takes into account the dependence between the two types of responses, which are often analyzed separately. We propose a Bayesian hierarchical model for jointly modeling longitudinal and survival data considering functional time and spatial frailty effects, respectively. That is, the proposed model deals with nonlinear longitudinal effects and spatial survival effects accounting for the unobserved heterogeneity among individuals living in the same region. This joint approach is applied to a cohort study of patients with HIV/AIDS in Brazil during the years 2002–2006. Our Bayesian joint model presents considerable improvements in the estimation of survival times of the Brazilian HIV/AIDS patients when compared with those ones obtained through a separate survival model and shows that the spatial risk of death is the same across the different Brazilian states." |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-08-01T00:00:00Z 2016-08-01T00:00:00Z 2017-08-31T00:30:12Z |
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://hdl.handle.net/10400.26/17916 |
url |
http://hdl.handle.net/10400.26/17916 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Martins, R., Silva, G. L., and Andreozzi, V. (2016) Bayesian joint modeling of longitudinal and spatial survival AIDS data. Statist. Med., 35: 3368–3384. doi: 10.1002/sim.6937 1097-0258 10.1002/sim.6937 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Wiley |
publisher.none.fl_str_mv |
Wiley |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799129955651551232 |