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Abstract Details
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Activity Number:
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53
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Type:
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Invited
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Date/Time:
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Sunday, July 29, 2012 : 4:00 PM to 5:50 PM
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Sponsor:
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General Methodology
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| Abstract - #303819 |
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Title:
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Application of Dependent Processes to Covariate-Adjusted Frailty Distributions in the Proportional Hazards Model
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Author(s):
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Timothy Hanson*+ and Alejandro Jara and Lianming Wang
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Companies:
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University of South Carolina and Pontificia Universidad Católica de Chile and University of South Carolina
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Address:
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, , 29208,
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Keywords:
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Frailty ;
Tailfree process ;
Bayesian nonparametric ;
Survival analysis
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Abstract:
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Frailties are a convenient way to incorporate dependence among clustered survival times within the proportional hazards model. Frailties are typically assume to be exchangeable. We relax the exchangeability assumption by introducing a novel, dynamic median-zero frailty distribution that smoothly changes shape with cluster-level predictors. The frailty distribution is modeled as a linear dependent tailfree process (Jara and Hanson, 2011). The model is illustrated with simulated and real data.
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