Shared Frailty Survival Analysis Using Semiparametric Bayesian Method

by Shaban A. Shaban and Ayman A. Mostafa.

Abstract: In survival data analysis, the proportional hazard model was introduced by Cox (1972) in order to estimate the effects of different covariates influencing the time-to-event data. The proportional hazard model has been used extensively in biomedicine, reliability engineering and, recently, interest in its application in different areas of knowledge has increased. However, proportional hazard model makes a number of assumptions, which may be violated. The object of this article is to present a Bayesian analysis for survival models with frailty under additive framework for the hazard function in contrast to proportional hazard model. Frailty models in survival analysis deal with the unobserved heterogeneity among subjects. Gibbs sampling technique is used to assess the posterior quantities of interest. An illustrative analysis within the context of survival time data is given.

Key Words: LSR; Survival Analysis, Regression Models, Additive Survival Analysis, Bayesian Inference, Frailty Models, BUGS

Authors:
Shaban A. Shaban, drshaban@hotmail.com
Ayman A. Mostafa, aymaneisa70@yahoo.com

Editor: Ghorai, Jugal K., jugal@csd.uwm.edu

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