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Título: Proportional odds hazard model for discrete time-to-event data
Autor(es): Vieira, Maria Gabriella Figueiredo
Cardial, Marcílio Ramos Pereira
Matsushita, Raul
Nakano, Eduardo Yoshio
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
Afiliação do autor: 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
Data de publicação: 6-Dez-2023
Editora: MDPI
Referência: 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.
Unidade Acadêmica: 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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