1
Department of Statistics, Tarbiat Modares University
2
Statistics Department, Sadralmotalaheen Non-Profit and Non-Governmental Higher Education Institute
Abstract
In the analysis of survival data, due to the presence of censoring and skewness, models such as Weibull are used for analysis. In addition, parametric and semi-parametric models can be fitted to survival data through the basic hazard function in the Cox model.
Although these models are of interest to users due to their simplicity in calculations, they do not necessarily fit the best model to the data due to the fact that they do not consider unknown risk factors. In this article, the fragility model is introduced to include unknown risk factors by considering multiplicative random effects in the Cox model. Then, esophageal cancer data in Golestan province are modeled using the presented models, and the fitted models are evaluated and compared based on the criterion of generalized coefficient of determination.
Abyar, A., Mohammadzadeh, M. & Translator, K. (2016). Cox survival and fragility models for analyzing esophageal cancer data. Andishe_ye Amari, 21(1), 57-63.
MLA
Abyar, A., Mohammadzadeh, M., & Translator, K. "Cox survival and fragility models for analyzing esophageal cancer data.", Andishe_ye Amari, 21, 1, 2016, 57-63.
HARVARD
Abyar A., Mohammadzadeh M., Translator K. (2016). 'Cox survival and fragility models for analyzing esophageal cancer data.', Andishe_ye Amari, 21(1), pp. 57-63.
CHICAGO
A. Abyar, M. Mohammadzadeh & K. Translator, "Cox survival and fragility models for analyzing esophageal cancer data.," Andishe_ye Amari, 21 1 (2016): 57-63,
VANCOUVER
Abyar A., Mohammadzadeh M., Translator K. Cox survival and fragility models for analyzing esophageal cancer data. Andishe_ye Amari. 2016;21(1):57-63 (In Persian).
