Bayesian analysis of an inverse Gaussian correlated frailty model

  • Authors:

  • Soleiman Kheiri;Alan Kimber;Mohammad Reza Meshkani

  • Affiliations:

  • Department of Biostatistics and Epidemiology, Faculty of Health, Shahrekord University of Medical Sciences, Shahrekord, Iran;Section of Applied Statistics, The University of Reading, Reading RG6 6FN, UK;Department of Statistics, School of Mathematical Sciences, Shahid Beheshti University, Tehran 19839, Iran

  • Venue:
  • Computational Statistics & Data Analysis
  • Year:
  • 2007

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Abstract

In survival analysis frailty is often used to model heterogeneity between individuals or correlation within clusters. Typically frailty is taken to be a continuous random effect, yielding a continuous mixture distribution for survival times. A Bayesian analysis of a correlated frailty model is discussed in the context of inverse Gaussian frailty. An MCMC approach is adopted and the deviance information criterion is used to compare models. As an illustration of the approach a bivariate data set of corneal graft survival times is analysed.