Abdo, D., Abd-Elmegaly, A., Abo EL Nasr, M. (2024). Survival models including excess hazard model and multilevel excess hazard model with application. The Egyptian Statistical Journal, 68(1), 78-90. doi: 10.21608/esju.2024.284028.1033
Doaa A. Abdo; Alaa Ahmed Abd-Elmegaly; Mona Abo EL Nasr. "Survival models including excess hazard model and multilevel excess hazard model with application". The Egyptian Statistical Journal, 68, 1, 2024, 78-90. doi: 10.21608/esju.2024.284028.1033
Abdo, D., Abd-Elmegaly, A., Abo EL Nasr, M. (2024). 'Survival models including excess hazard model and multilevel excess hazard model with application', The Egyptian Statistical Journal, 68(1), pp. 78-90. doi: 10.21608/esju.2024.284028.1033
Abdo, D., Abd-Elmegaly, A., Abo EL Nasr, M. Survival models including excess hazard model and multilevel excess hazard model with application. The Egyptian Statistical Journal, 2024; 68(1): 78-90. doi: 10.21608/esju.2024.284028.1033
Survival models including excess hazard model and multilevel excess hazard model with application
1Department of applied statistics, Faculty of Commerce, Mansoura University
2Higher Institute of Advanced Management Sciences and Computers, Al-Buhayrah, Egypt
3Department of applied statistics and insurance, Faculty of Commerce, Mansoura University
Abstract
This paper presents a comprehensive analysis of procedures for the excess hazard model. A common issue with hazard models is estimating the overall hazard rather than the excess hazard, leading to inaccurate parameter estimates. The paper suggests applying various survival models, including the excess hazard model and the multilevel excess hazard model, to enhance the accuracy and reliability of the results. The primary objective of this study is to estimate the excess hazard for both models and conduct a comparative analysis between them. Two statistical criteria, Akaike's Information Criterion (AIC) and Bayesian Information Criterion (BIC), were utilized to evaluate model accuracy. All calculations were performed using the R software system, specifically R version 4.2.2. The multilevel excess hazard model demonstrated superior performance in terms of AIC and BIC compared to the excess hazard model.
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