Generalised Lindley shared additive frailty regression model for bivariate survival data

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