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Abstract Details
Activity Number:
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526
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract - #305194 |
Title:
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Piecewise Exponential Survival Times and Analysis of Case-Cohort Data
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Author(s):
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Barry I. Graubard*+ and Yan Li and Jay Lubin and Dale Preston and Mitchell H Gail
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Companies:
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National Cancer Institute and The University of Texas at Arlington and National Cancer Institute and Hirosoft International and National Cancer Institute
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Address:
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, Rockville, MD, 20852,
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Keywords:
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Poisson regression ;
Taylor linearization variance estimator ;
Sample weighting
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Abstract:
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Case-cohort designs select a random sample of a cohort to be used as controls with cases arising from the follow-up of the cohort. Analyses of case-cohort studies with time-varying exposures that use Cox partial likelihood methods can be computer intensive. We propose a piecewise-exponential approach where Poisson regression model parameters are estimated from a pseudo-likelihood and the corresponding variances are derived applying Taylor linearization methods that are used in survey research. The proposed approach is evaluated using Monte Carlo simulations. An illustration is provided using data from the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study of male smokers in Finland, where a case-cohort study of serum glucose level and pancreatic cancer was analyzed.
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