Comparison of additive shared frailty models under Lindley baseline distribution

Abstract

In this article, we propose additive shared gamma frailty model and additive shared inverse Gaussian frailty model with Lindley as baseline distribution to analyze the infectious disease data set of McGilchrist and Aisbett. The Bayesian approach of Markov Chain Monte Carlo technique was employed to estimate the parameters involved in the models. A simulation study was also carried out to compare the true values and estimated values of the parameters. Comparison of proposed models and the existing models was also done by using Bayesian information criteria such as BIC, WBIC and Bayes factor. A better model was also recommended for infectious disease data.

Keywords:

• Additive shared frailty
• Bayesian approach
• Gamma frailty
• Inverse Gaussian frailty
• Lindley distribution
• MCMC