Multivariate Survival Models with a Mixture of Positive Stable Frailties

Nalini Ravishanker () and Dipak K. Dey ()
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Nalini Ravishanker: University of Connecticut
Dipak K. Dey: University of Connecticut

Methodology and Computing in Applied Probability, 2000, vol. 2, issue 3, 293-308

Abstract: Abstract In this paper, we describe models for dependent multivariate survival data using finite mixtures of positive stable frailty distributions. We investigate the cross-ratio function as a local measure of association. We estimate the parameters in the stable mixture together with the parameters of the (conditional) proportional hazards model in a Bayesian framework using Markov chain Monte Carlo algorithms. We illustrate the methodology using data on kidney infections.

Keywords: dependent survival data; frailty distribution; infinite variance stable distribution; local association; proportional hazards model (search for similar items in EconPapers)
Date: 2000
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DOI: 10.1023/A:1010033329399

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