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Article type: Research Article
Authors: de Oliveira, Ricardo Puziola; * | de Oliveira Peres, Marcos Viniciusa | Bertoli, Wesleyb | Achcar, Jorge Albertoa
Affiliations: [a] Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil | [b] Department of Statistics, Federal University of Technology – Paraná, Curitiba, PR, Brazil
Correspondence: [*] Corresponding author: Ricardo Puziol de Oliveira, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil. E-mail: rpuziol.oliveira@gmail.com.
Abstract: The present study considers non-mixture models based on the discrete Burr XIII distribution to model recurrent event data in the presence of a cure fraction. In this context, we provide an alternative to the standard Cox proportional hazards model using a discretized distribution to analyze lifetime data assuming a non-mixture structure for cure rates. In a Bayesian setting, the proposed methodology was considered for analyzing a real dataset from a retrospective cohort study that aimed to evaluate specific clinical conditions that affect the lifetimes of 299 heart failure patients admitted to the Institute of Cardiology and Allied Hospital – Faisalabad, Pakistan (April-December, 2015). The model validation process was addressed using the Cox-Snell residuals, which allowed us to identify the suitability of the proposed non-mixture cure rate model.
Keywords: Bayesian approach, Burr XIII distribution, heart failure, non-mixture model, survival regression analysis
DOI: 10.3233/MAS-221341
Journal: Model Assisted Statistics and Applications, vol. 18, no. 1, pp. 45-55, 2023
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