Regression models for grouped survival data: Estimation and sensitivity analysis

Detalhes bibliográficos
Autor(a) principal: Hashimoto, Elizabeth M.
Data de Publicação: 2011
Outros Autores: Ortega, Edwin M.M., Paula, Gilberto A., Barreto, Mauricio Lima
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFBA
Texto Completo: http://www.repositorio.ufba.br/ri/handle/ri/5518
Resumo: texto completo: acesso restrito. p. 993–1007
id UFBA-2_2725d5dc370e5e9c38742fb37dd14333
oai_identifier_str oai:repositorio.ufba.br:ri/5518
network_acronym_str UFBA-2
network_name_str Repositório Institucional da UFBA
repository_id_str 1932
spelling Hashimoto, Elizabeth M.Ortega, Edwin M.M.Paula, Gilberto A.Barreto, Mauricio LimaHashimoto, Elizabeth M.Ortega, Edwin M.M.Paula, Gilberto A.Barreto, Mauricio Lima2012-03-06T20:19:55Z20110167-9473)http://www.repositorio.ufba.br/ri/handle/ri/5518v. 55.texto completo: acesso restrito. p. 993–1007In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models.Submitted by Ana Valéria de Jesus Moura (anavaleria_131@hotmail.com) on 2012-03-06T20:19:55Z No. of bitstreams: 1 Regression models for grouped survival data_ Estimation and sensitivity analysis.pdf: 954201 bytes, checksum: a9cd7951adcd732c06eef0caf9c6693d (MD5)Made available in DSpace on 2012-03-06T20:19:55Z (GMT). No. of bitstreams: 1 Regression models for grouped survival data_ Estimation and sensitivity analysis.pdf: 954201 bytes, checksum: a9cd7951adcd732c06eef0caf9c6693d (MD5) Previous issue date: 2011doi:10.1016/j.csda.2010.08.004reponame:Repositório Institucional da UFBAinstname:Universidade Federal da Bahia (UFBA)instacron:UFBACensored dataGrouped survival dataLink functionRegression modelSensitivity analysisRegression models for grouped survival data: Estimation and sensitivity analysisComputational Statistics and Data Analysisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article10000-01-01enginfo:eu-repo/semantics/openAccessORIGINALRegression models for grouped survival data_ Estimation and sensitivity analysis.pdfRegression models for grouped survival data_ Estimation and sensitivity analysis.pdfapplication/pdf954201https://repositorio.ufba.br/bitstream/ri/5518/1/Regression%20models%20for%20grouped%20survival%20data_%20Estimation%20and%20sensitivity%20analysis.pdfa9cd7951adcd732c06eef0caf9c6693dMD51LICENSElicense.txtlicense.txttext/plain1762https://repositorio.ufba.br/bitstream/ri/5518/2/license.txt1b89a9a0548218172d7c829f87a0eab9MD52TEXTRegression models for grouped survival data_ Estimation and sensitivity analysis.pdf.txtRegression models for grouped survival data_ Estimation and sensitivity analysis.pdf.txtExtracted texttext/plain52618https://repositorio.ufba.br/bitstream/ri/5518/3/Regression%20models%20for%20grouped%20survival%20data_%20Estimation%20and%20sensitivity%20analysis.pdf.txt6e539f4de4b19e07ce21a838033ef14bMD53ri/55182022-07-05 14:03:21.063oai:repositorio.ufba.br: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Repositório InstitucionalPUBhttp://192.188.11.11:8080/oai/requestopendoar:19322022-07-05T17:03:21Repositório Institucional da UFBA - Universidade Federal da Bahia (UFBA)false
dc.title.pt_BR.fl_str_mv Regression models for grouped survival data: Estimation and sensitivity analysis
dc.title.alternative.pt_BR.fl_str_mv Computational Statistics and Data Analysis
title Regression models for grouped survival data: Estimation and sensitivity analysis
spellingShingle Regression models for grouped survival data: Estimation and sensitivity analysis
Hashimoto, Elizabeth M.
Censored data
Grouped survival data
Link function
Regression model
Sensitivity analysis
title_short Regression models for grouped survival data: Estimation and sensitivity analysis
title_full Regression models for grouped survival data: Estimation and sensitivity analysis
title_fullStr Regression models for grouped survival data: Estimation and sensitivity analysis
title_full_unstemmed Regression models for grouped survival data: Estimation and sensitivity analysis
title_sort Regression models for grouped survival data: Estimation and sensitivity analysis
author Hashimoto, Elizabeth M.
author_facet Hashimoto, Elizabeth M.
Ortega, Edwin M.M.
Paula, Gilberto A.
Barreto, Mauricio Lima
author_role author
author2 Ortega, Edwin M.M.
Paula, Gilberto A.
Barreto, Mauricio Lima
author2_role author
author
author
dc.contributor.author.fl_str_mv Hashimoto, Elizabeth M.
Ortega, Edwin M.M.
Paula, Gilberto A.
Barreto, Mauricio Lima
Hashimoto, Elizabeth M.
Ortega, Edwin M.M.
Paula, Gilberto A.
Barreto, Mauricio Lima
dc.subject.por.fl_str_mv Censored data
Grouped survival data
Link function
Regression model
Sensitivity analysis
topic Censored data
Grouped survival data
Link function
Regression model
Sensitivity analysis
description texto completo: acesso restrito. p. 993–1007
publishDate 2011
dc.date.issued.fl_str_mv 2011
dc.date.accessioned.fl_str_mv 2012-03-06T20:19:55Z
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://www.repositorio.ufba.br/ri/handle/ri/5518
dc.identifier.issn.none.fl_str_mv 0167-9473)
dc.identifier.number.pt_BR.fl_str_mv v. 55.
identifier_str_mv 0167-9473)
v. 55.
url http://www.repositorio.ufba.br/ri/handle/ri/5518
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.pt_BR.fl_str_mv doi:10.1016/j.csda.2010.08.004
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFBA
instname:Universidade Federal da Bahia (UFBA)
instacron:UFBA
instname_str Universidade Federal da Bahia (UFBA)
instacron_str UFBA
institution UFBA
reponame_str Repositório Institucional da UFBA
collection Repositório Institucional da UFBA
bitstream.url.fl_str_mv https://repositorio.ufba.br/bitstream/ri/5518/1/Regression%20models%20for%20grouped%20survival%20data_%20Estimation%20and%20sensitivity%20analysis.pdf
https://repositorio.ufba.br/bitstream/ri/5518/2/license.txt
https://repositorio.ufba.br/bitstream/ri/5518/3/Regression%20models%20for%20grouped%20survival%20data_%20Estimation%20and%20sensitivity%20analysis.pdf.txt
bitstream.checksum.fl_str_mv a9cd7951adcd732c06eef0caf9c6693d
1b89a9a0548218172d7c829f87a0eab9
6e539f4de4b19e07ce21a838033ef14b
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
repository.name.fl_str_mv Repositório Institucional da UFBA - Universidade Federal da Bahia (UFBA)
repository.mail.fl_str_mv
_version_ 1808459396050583552

Registros relacionados