An extended weibull regression for censored data : application for COVID-19 in Campinas, Brazil

Rodrigues, Gabriela Maria; Ortega, Edwin M. M.; Cordeiro, Gauss M.; Vila Gabriel, Roberto

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Campo DC	Valor	Idioma
dc.contributor.author	Rodrigues, Gabriela Maria	-
dc.contributor.author	Ortega, Edwin M. M.	-
dc.contributor.author	Cordeiro, Gauss M.	-
dc.contributor.author	Vila Gabriel, Roberto	-
dc.date.accessioned	2023-09-22T15:27:46Z	-
dc.date.available	2023-09-22T15:27:46Z	-
dc.date.issued	2022-10-05	-
dc.identifier.citation	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.	pt_BR
dc.identifier.uri	http://repositorio2.unb.br/jspui/handle/10482/46534	-
dc.language.iso	eng	pt_BR
dc.publisher	MDPI	pt_BR
dc.rights	Acesso Aberto	pt_BR
dc.title	An extended weibull regression for censored data : application for COVID-19 in Campinas, Brazil	pt_BR
dc.type	Artigo	pt_BR
dc.subject.keyword	Estatística matemática	pt_BR
dc.subject.keyword	Covid-19	pt_BR
dc.rights.license	(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/).	pt_BR
dc.identifier.doi	https://doi.org/10.3390/math10193644	pt_BR
dc.description.abstract1	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	pt_BR
dc.identifier.orcid	https://orcid.org/0000-0002-1985-8141	pt_BR
dc.identifier.orcid	https://orcid.org/0000-0003-3999-7402	pt_BR
dc.identifier.orcid	https://orcid.org/0000-0002-3052-6551	pt_BR
dc.identifier.orcid	https://orcid.org/0000-0003-1073-0114	pt_BR
dc.contributor.affiliation	University of São Paulo, Department of Exact Sciences	pt_BR
dc.contributor.affiliation	University of São Paulo, Department of Exact Sciences	pt_BR
dc.contributor.affiliation	Federal University of Pernambuco, Department of Statistics	pt_BR
dc.contributor.affiliation	University of Brasilia, Department of Statistics	pt_BR
dc.description.unidade	Instituto de Ciências Exatas (IE)	pt_BR
dc.description.unidade	Departamento de Estatística (IE EST)	pt_BR
Aparece nas coleções:	Artigos publicados em periódicos e afins UnB - Covid-19