Generalised Lindley shared additive frailty regression model for bivariate survival data
Generalised Lindley shared additive frailty regression model for bivariate survival data

Summary/Abstract: Frailty models are the possible choice to counter the problem of the unobserved heterogeneity in individual risks of disease and death. Based on earlier studies, shared frailty modelscan be utilised in the analysis of bivariate data related to survival times (e.g. matched pairsexperiments, twin or family data). In this article, we assume that frailty acts additively to thehazard rate. A new class of shared frailty models based on generalised Lindley distributionis established. By assuming generalised Weibull and generalised log-logistic baseline distributions, we propose a new class of shared frailty models based on the additive hazard rate.We estimate the parameters in these frailty models and use the Bayesian paradigm of theMarkov Chain Monte Carlo (MCMC) technique. Model selection criteria have been appliedfor the comparison of models. We analyse kidney infection data and suggest the best model.

• Details
• Contents