Título :	Proportional odds hazard model for discrete time-to-event data
Autor :	Vieira, Maria Gabriella Figueiredo Cardial, Marcílio Ramos Pereira Matsushita, Raul Nakano, Eduardo Yoshio
metadata.dc.identifier.orcid:	https://orcid.org/0000-0003-2533-4720 https://orcid.org/0000-0003-3610-1623 https://orcid.org/0000-0001-8864-6356 https://orcid.org/0000-0002-9071-8512
metadata.dc.contributor.affiliation:	University of Brasilia, Department of Statistics University of São Paulo, Institute of Mathematical and Computer Sciences, São Carlos University of Brasilia, Department of Statistics University of Brasilia, Department of Statistics
Assunto::	Modelo de regressão Análise de sobrevivência
Fecha de publicación :	6-dic-2023
Editorial :	MDPI
Citación :	VIEIRA, Maria Gabriella Figueiredo et al. Proportional odds hazard model for discrete time-to-event data. Axioms, v. 12, n. 12, 1102, 2023. DOI: https://doi.org/10.3390/axioms12121102. Disponível em: https://www.mdpi.com/2075-1680/12/12/1102. Acesso em: https://www.mdpi.com/2075-1680/12/12/1102. Acesso em: 01 fev. 2024.
Abstract:	: In this article, we present the development of the proportional odds hazard model for discrete time-to-event data. In this work, inferences about the model’s parameters were formulated considering the presence of right censoring and the discrete Weibull and log-logistic distributions. Simulation studies were carried out to check the asymptotic properties of the estimators. In addition, procedures for checking the proportional odds assumption were proposed, and the proposed model is illustrated using a dataset on the survival time of patients with low back pain.
metadata.dc.description.unidade:	Instituto de Ciências Exatas (IE) Departamento de Estatística (IE EST)
Licença::	Copyright: © 2023 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/axioms12121102
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