Flexible Proportional Odds Regression Model with Applications
Ishag, M. A. S., Wanjoya, A., Adem, A., Alghamdi, A. S., and Afify, A. Z.
Corresponding Email: ahmed.afify@fcom.bu.edu.eg
Received date: 15 October 2024
Accepted date: 2 March 2025
Abstract:
This study proposes a flexible parametric proportional odds regression model that incorporates the exponentiated-Weibull distribution as a baseline for analyzing censored lifetime data. The proposed model is referred to as the exponentiated-Weibull proportional odds regression model. This model provides greater flexibility in capturing a wider range of hazard shapes and survival patterns. The paper discusses the theoretical framework as well as estimation methods for the model parameters. Additionally, extensive simulation studies are conducted to evaluate the proposed model's performance under different scenarios. The results demonstrate that the model effectively accommodates the unique characteristics of the exponentiated-Weibull distribution.
Furthermore, two real-world datasets are presented to illustrate and compare the model's practical application and performance with existing proportional odds regression models. The findings highlight the advantages of using the proposed model and its potential to enhance the analysis of survival data and capture complex survival patterns.
Keywords: proportional odds regression model; survival analysis; censored data; exponentiated Weibull distribution; maximum likelihood estimation; simulation study.