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Activity Number:
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102
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 12, 2002 : 10:30 AM to 12:20 PM
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Sponsor:
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General Methodology
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| Abstract - #300764 |
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Title:
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On Multivariate Survival Models with a Skewed Frailty and Correlated Baseline Hazard Process
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Author(s):
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Dipak Dey*+
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Affiliation(s):
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University of Connecticut
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Address:
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U-4120, 215 Glenbrook Road, Storrs, Connecticut, 06269, USA
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Keywords:
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Frailty ; MCMC ; Reversible jump ; Stable distribution
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Abstract:
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Often, the dependence in multivariate survival data is modeled through an individual level effect called the frailty. In this talk we propose a very general class of robust frailty distribution called the log skew-t distribution, which includes many commonly used frailty distributions. The distributions often have heavier tails than the gamma and even the positive stable distributions. Conditional on frailty, the survival times are assumed to be independent with proportional hazard structure. The modelling process is then completed by assuming a correlated prior process on the baseline hazard function. Further, we consider such a process, which jumps according to a time-homogeneous Poisson process. We develop Bayesian methods to obtain posterior inference using a variable dimensional Markov chain Monte Carlo method. We illustrate and compare our methods using two practical examples.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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