Abstract
In this article, we propose inverse Gaussian correlated frailty model based on logistic exponential 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 estimated value of the parameters. Comparison of the proposed model with correlated gamma frailty model and without frailty model was done using Bayesian comparison techniques. The better model for the infectious disease data related to kidney infection is also suggested.
Acknowledgments
We thank the referee for the valuable suggestions and comments which improved the earlier version of the manuscript.