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Activity Number: 583
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
Sponsor: Health Policy Statistics Section
Abstract - #304817
Title: Fitting Additive Hazards Models for Case-Cohort Studies: A Multiple Imputation Approach
Author(s): Jinhyouk Jung*+ and Sangwook Kang and Ofer Harel, Ph.D.
Companies: University of Connecticut and University of Connecticut and University of Connecticut
Address: 230 Zygmont RD.,, Storrs, CT, 06268, United States
Keywords: Additive hazards models ; Case-cohort study ; Multiple Imputation ; Missing covariates ; Survival analysis

In this paper, we consider fitting additive hazards models for case-cohort studies using a multiple imputation approach. In a case-cohort study, main exposure variables are measured only on some selected subjects but other covariates are often available for the whole cohort. This can be treated as a special case of a missing covariate problem. We propose to employ a popular incomplete data method, multiple imputation, for estimation of the regression parameters in additive hazards models. Finite sample properties of the proposed estimators are investigated via simulation studies and illustrated using a data example.

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