Título:	An extended weibull regression for censored data : application for COVID-19 in Campinas, Brazil
Autor(es):	Rodrigues, Gabriela Maria Ortega, Edwin M. M. Cordeiro, Gauss M. Vila Gabriel, Roberto
ORCID:	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
Afiliação do autor:	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
Assunto:	Estatística matemática Covid-19
Data de publicação:	5-Out-2022
Editora:	MDPI
Referência:	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.
Abstract:	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
Unidade Acadêmica:	Instituto de Ciências Exatas (IE) Departamento de Estatística (IE EST)
Licença:	(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/).
DOI:	https://doi.org/10.3390/math10193644
Aparece nas coleções:	Artigos publicados em periódicos e afins UnB - Covid-19

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