Shared Frailty Survival Analysis Using Semiparametric Bayesian Method
by Shaban A. Shaban and Ayman A. Mostafa.
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
Gibbs sampling technique is used to assess the posterior quantities of interest.
An illustrative analysis within the context of survival time data is given.
LSR; Survival Analysis, Regression Models, Additive Survival Analysis, Bayesian Inference, Frailty Models, BUGS
Shaban A. Shaban, email@example.com
Ayman A. Mostafa, firstname.lastname@example.org
Ghorai, Jugal K., email@example.com
READING THE ARTICLE: You can read the article in
portable document (.pdf) format (205405 bytes.)
NOTE: The content of this article is the intellectual property of the authors, who retains all rights to future publication.
This page has been accessed 3395 times since July 24, 2006.
Return to the Home Page.