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Activity Number: 526
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #305194
Title: Piecewise Exponential Survival Times and Analysis of Case-Cohort Data
Author(s): Barry I. Graubard*+ and Yan Li and Jay Lubin and Dale Preston and Mitchell H Gail
Companies: National Cancer Institute and The University of Texas at Arlington and National Cancer Institute and Hirosoft International and National Cancer Institute
Address: , Rockville, MD, 20852,
Keywords: Poisson regression ; Taylor linearization variance estimator ; Sample weighting

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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