Weibull-Geometric Mixture Cure Rate Models With Applications

Abdallah Mahmoud Badr, Tarek Shams, Ahmed Abou Almaaty and Abd El-Hamid Eisa
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Abdallah Mahmoud Badr: College of Commerce, Al-Azhar University, Cairo, Egypt & College of Business, King Khalid University, Saudi Arabia
Tarek Shams: College of Commerce, Al-Azhar University, Cairo, Egypt & College of Business, King Khalid University, Saudi Arabia
Ahmed Abou Almaaty: College of Commerce, Al-Azhar University, Cairo, Egypt
Abd El-Hamid Eisa: College of Commerce, Al-Azhar University, Cairo, Egypt

International Journal of Information System Modeling and Design (IJISMD), 2025, vol. 16, issue 1, 1-26

Abstract: This article delves into a parametric survival model tailored for scenarios where the studied population encompasses long-term survivors or individuals with immunity. We initially conceptualized the cure rate model as a mixture model, which included a segment that represented the proportion of immune individuals and a distribution that characterized the lifetimes of susceptible individuals. Our contribution lies in proposing a cure rate model grounded in the Weibull-Geometric Distribution, adept at integrating the influences of risk factors or covariates on the likelihood of an individual becoming a long-term survivor. Cure rate models serve as powerful tools for modeling time-to-event dynamics across diverse contexts. Different methods of estimation are used to estimate the unknown parameters in complete and censored random samples.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jismd0:v:16:y:2025:i:1:p:1-26

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