Shared frailty model based on reversed hazard rate for left censored data

ABSTRACT

Frailty models are used in the survival analysis to account for the unobserved heterogeneity in the individual risks to disease and death. To analyze the bivariate data on related survival times (e.g., matched pairs experiments, twin or family data), the shared frailty models were suggested. In this article, we introduce the shared gamma frailty models with the reversed hazard rate. We develop the Bayesian estimation procedure using the Markov chain Monte Carlo (MCMC) technique to estimate the parameters involved in the model. We present a simulation study to compare the true values of the parameters with the estimated values. We apply the model to a real life bivariate survival dataset.

KEYWORDS:

• Bayesian estimation
• Gamma frailty
• Inverse Weibull distribution
• MCMC

MATHEMATICS SUBJECT CLASSIFICATION:

• 62F15
• 62N01
• 62P10

Acknowledgments

The authors thank all the referees and the associated editor for the valuable suggestions and comments that improved the earlier version of the manuscript.