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Activity Number:
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393
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Type:
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Invited
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Date/Time:
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Thursday, August 12, 2004 : 8:30 AM to 10:20 AM
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Sponsor:
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ENAR
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| Abstract - #300161 |
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Title:
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Model Selection for Dynamic Survival Analysis
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Author(s):
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Ian W. McKeague*+
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Companies:
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Florida State University
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Address:
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Department of Statistics, Tallahassee, FL, 32306-4330,
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Keywords:
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hazard function regression ; censored data ; additive risk model ; covariate selection ; nonproportional hazards
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Abstract:
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Model selection methods are well developed in parametric settings, and in recent years they have been extended to wide classes of nonparametric models. For dynamic survival models which involve complex time-dependent covariates and coefficients, however, generally applicable and fully validated procedures are not yet available. This talk discusses a new approach that applies to a flexible class of nonproportional hazard function regression models in which the influence of the covariates splits into the sum of a parametric part and a time-dependent nonparametric part. The approach allows covariate selection for the parametric part by adjusting for the implicit fitting of the nonparametric part. Asymptotic consistency is established, leading to asymptotically normal estimators of both parametric and nonparametric parts of the model in the presence of covariate selection. The approach is illustrated using real and simulated data.
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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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