A Mixture Shared Frailty Model based on Log-logistic Baseline Distribution

Abstract

Frailty model is a survival model designed to account for unobserved heterogeneity in the population. In this paper, we propose a new shared frailty model based on log-logistic as baseline distribution. The Bayesian approach of Markov Chain Monte Carlo (MCMC) technique was employed to estimate the parameters involved in the models. A simulation study was performed to compare the true values and the estimated values of the parameters. Comparison of different proposed models was done by using Bayesian comparison techniques. We apply to real life data set related to kidney infection due to insertion of catheter and the better model is suggested.