Proportional Log Survival Model for Discrete Time-to-Event Data

Tiago Chandiona Ernesto Franque, Marcílio Ramos Pereira Cardial and Eduardo Yoshio Nakano ()
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Tiago Chandiona Ernesto Franque: Department of Exact Sciences, University of Save, Chongoene 1200, Mozambique
Marcílio Ramos Pereira Cardial: Institute of Mathematics and Statistics, Federal University of Goiás, Goiânia 74001-970, Brazil
Eduardo Yoshio Nakano: Department of Statistics, University of Brasilia, Campus Darcy Ribeiro, Asa Norte, Brasília 70910-900, Brazil

Mathematics, 2025, vol. 13, issue 5, 1-14

Abstract: The aim of this work is to propose a proportional log survival model (PLSM) as a discrete alternative to the proportional hazards (PH) model. This paper presents the formulation of PLSM as well as the procedures for verifying its assumption. The parameters of the PLSM are inferred using the maximum likelihood method, and a simulation study was carried out to investigate the usual asymptotic properties of the estimators. The PLSM was illustrated using data on the survival time of leukemia patients, and it was shown to be a viable alternative for modeling discrete survival data in the presence of covariates.

Keywords: discrete censored data; discrete Weibull distribution; proportional models; survival analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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