An extended weibull regression for censored data : application for COVID-19 in Campinas, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UnB |
Texto Completo: | http://repositorio2.unb.br/jspui/handle/10482/46534 https://doi.org/10.3390/math10193644 https://orcid.org/0000-0002-1985-8141 https://orcid.org/0000-0003-3999-7402 https://orcid.org/0000-0002-3052-6551 https://orcid.org/0000-0003-1073-0114 |
Resumo: | This work aims to study the factors that increase the risk of death of hospitalized patients diagnosed with COVID-19 through the odd log-logistic regression model for censored data with two systematic components, as well as provide new mathematical properties of this distribution. To achieve this, a dataset of individuals residing in the city of Campinas (Brazil) was used and simulations were performed to investigate the accuracy of the maximum likelihood estimators in the proposed regression model. The provided properties, such as stochastic representation, identifiability, and moments, among others, can help future research since they provide important information about the distribution structure. The simulation results revealed the consistency of the estimates for different censoring percentages and show that the empirical distribution of the modified deviance residuals converge to the standard normal distribution. The proposed model proved to be efficient in identifying the determinant variables for the survival of the individuals in this study, which can help to find more opportune treatments and medical interventions. Therefore, the new model can be considered an interesting alternative for future works that evaluate censored lifetimes |
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Rodrigues, Gabriela MariaOrtega, Edwin M. M.Cordeiro, Gauss M.Gabriel, Roberto VilaUniversity of São Paulo, Department of Exact SciencesUniversity of São Paulo, Department of Exact SciencesFederal University of Pernambuco, Department of StatisticsUniversity of Brasilia, Department of Statistics2023-09-22T15:27:46Z2023-09-22T15:27:46Z2022-10-05RODRIGUES, Gabriela M. et al. An extended weibull regression for censored data: application for COVID-19 in Campinas, Brazil. Mathematics, [S.l.], v. 10, n. 19, 3644. DOI: https://doi.org/10.3390/math10193644. Disponível em: https://www.mdpi.com/2227-7390/10/19/3644. Acesso em: 22 set. 2023.http://repositorio2.unb.br/jspui/handle/10482/46534https://doi.org/10.3390/math10193644https://orcid.org/0000-0002-1985-8141https://orcid.org/0000-0003-3999-7402https://orcid.org/0000-0002-3052-6551https://orcid.org/0000-0003-1073-0114engMDPI(CC BY) Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).info:eu-repo/semantics/openAccessAn extended weibull regression for censored data : application for COVID-19 in Campinas, Brazilinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleEstatística matemáticaCovid-19This work aims to study the factors that increase the risk of death of hospitalized patients diagnosed with COVID-19 through the odd log-logistic regression model for censored data with two systematic components, as well as provide new mathematical properties of this distribution. To achieve this, a dataset of individuals residing in the city of Campinas (Brazil) was used and simulations were performed to investigate the accuracy of the maximum likelihood estimators in the proposed regression model. The provided properties, such as stochastic representation, identifiability, and moments, among others, can help future research since they provide important information about the distribution structure. The simulation results revealed the consistency of the estimates for different censoring percentages and show that the empirical distribution of the modified deviance residuals converge to the standard normal distribution. The proposed model proved to be efficient in identifying the determinant variables for the survival of the individuals in this study, which can help to find more opportune treatments and medical interventions. Therefore, the new model can be considered an interesting alternative for future works that evaluate censored lifetimesInstituto de Ciências Exatas (IE)Departamento de Estatística (IE EST)reponame:Repositório Institucional da UnBinstname:Universidade de Brasília (UnB)instacron:UNBORIGINALARTIGO_Extended Weibull Regression.pdfARTIGO_Extended Weibull Regression.pdfapplication/pdf995808http://repositorio2.unb.br/jspui/bitstream/10482/46534/1/ARTIGO_Extended%20Weibull%20Regression.pdfd55d070842dc8505e301ee922b36dce4MD51open accessLICENSElicense.txtlicense.txttext/plain102http://repositorio2.unb.br/jspui/bitstream/10482/46534/2/license.txtaed4704d04bb260d4decd80db311aaa5MD52open access10482/465342023-09-27 17:27:32.063open accessoai:repositorio2.unb.br:10482/46534U3VibWlzc8OjbyBlZmV0aXZhZGEgZGUgYWNvcmRvIGNvbSBsaWNlbsOnYSBjb25jZWRpZGEgcGVsbyBhdXRvciBlL291IGRldGVudG9yIGRvcyBkaXJlaXRvcyBhdXRvcmFpcy4KBiblioteca Digital de Teses e DissertaçõesPUBhttps://repositorio.unb.br/oai/requestopendoar:2023-09-27T20:27:32Repositório Institucional da UnB - Universidade de Brasília (UnB)false |
dc.title.pt_BR.fl_str_mv |
An extended weibull regression for censored data : application for COVID-19 in Campinas, Brazil |
title |
An extended weibull regression for censored data : application for COVID-19 in Campinas, Brazil |
spellingShingle |
An extended weibull regression for censored data : application for COVID-19 in Campinas, Brazil Rodrigues, Gabriela Maria Estatística matemática Covid-19 |
title_short |
An extended weibull regression for censored data : application for COVID-19 in Campinas, Brazil |
title_full |
An extended weibull regression for censored data : application for COVID-19 in Campinas, Brazil |
title_fullStr |
An extended weibull regression for censored data : application for COVID-19 in Campinas, Brazil |
title_full_unstemmed |
An extended weibull regression for censored data : application for COVID-19 in Campinas, Brazil |
title_sort |
An extended weibull regression for censored data : application for COVID-19 in Campinas, Brazil |
author |
Rodrigues, Gabriela Maria |
author_facet |
Rodrigues, Gabriela Maria Ortega, Edwin M. M. Cordeiro, Gauss M. Gabriel, Roberto Vila |
author_role |
author |
author2 |
Ortega, Edwin M. M. Cordeiro, Gauss M. Gabriel, Roberto Vila |
author2_role |
author author author |
dc.contributor.affiliation.pt_BR.fl_str_mv |
University of São Paulo, Department of Exact Sciences University of São Paulo, Department of Exact Sciences Federal University of Pernambuco, Department of Statistics University of Brasilia, Department of Statistics |
dc.contributor.author.fl_str_mv |
Rodrigues, Gabriela Maria Ortega, Edwin M. M. Cordeiro, Gauss M. Gabriel, Roberto Vila |
dc.subject.keyword.pt_BR.fl_str_mv |
Estatística matemática Covid-19 |
topic |
Estatística matemática Covid-19 |
description |
This work aims to study the factors that increase the risk of death of hospitalized patients diagnosed with COVID-19 through the odd log-logistic regression model for censored data with two systematic components, as well as provide new mathematical properties of this distribution. To achieve this, a dataset of individuals residing in the city of Campinas (Brazil) was used and simulations were performed to investigate the accuracy of the maximum likelihood estimators in the proposed regression model. The provided properties, such as stochastic representation, identifiability, and moments, among others, can help future research since they provide important information about the distribution structure. The simulation results revealed the consistency of the estimates for different censoring percentages and show that the empirical distribution of the modified deviance residuals converge to the standard normal distribution. The proposed model proved to be efficient in identifying the determinant variables for the survival of the individuals in this study, which can help to find more opportune treatments and medical interventions. Therefore, the new model can be considered an interesting alternative for future works that evaluate censored lifetimes |
publishDate |
2022 |
dc.date.issued.fl_str_mv |
2022-10-05 |
dc.date.accessioned.fl_str_mv |
2023-09-22T15:27:46Z |
dc.date.available.fl_str_mv |
2023-09-22T15:27:46Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
format |
article |
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publishedVersion |
dc.identifier.citation.fl_str_mv |
RODRIGUES, Gabriela M. et al. An extended weibull regression for censored data: application for COVID-19 in Campinas, Brazil. Mathematics, [S.l.], v. 10, n. 19, 3644. DOI: https://doi.org/10.3390/math10193644. Disponível em: https://www.mdpi.com/2227-7390/10/19/3644. Acesso em: 22 set. 2023. |
dc.identifier.uri.fl_str_mv |
http://repositorio2.unb.br/jspui/handle/10482/46534 |
dc.identifier.doi.pt_BR.fl_str_mv |
https://doi.org/10.3390/math10193644 |
dc.identifier.orcid.pt_BR.fl_str_mv |
https://orcid.org/0000-0002-1985-8141 https://orcid.org/0000-0003-3999-7402 https://orcid.org/0000-0002-3052-6551 https://orcid.org/0000-0003-1073-0114 |
identifier_str_mv |
RODRIGUES, Gabriela M. et al. An extended weibull regression for censored data: application for COVID-19 in Campinas, Brazil. Mathematics, [S.l.], v. 10, n. 19, 3644. DOI: https://doi.org/10.3390/math10193644. Disponível em: https://www.mdpi.com/2227-7390/10/19/3644. Acesso em: 22 set. 2023. |
url |
http://repositorio2.unb.br/jspui/handle/10482/46534 https://doi.org/10.3390/math10193644 https://orcid.org/0000-0002-1985-8141 https://orcid.org/0000-0003-3999-7402 https://orcid.org/0000-0002-3052-6551 https://orcid.org/0000-0003-1073-0114 |
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