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Abstract Details

Activity Number: 130
Type: Contributed
Date/Time: Monday, July 30, 2012 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #305889
Title: Use of a Joint Modeling Approach to Estimate Covariate Effects When Competing Risks Are Present
Author(s): Bo Fu*+ and Chung-Chou H Chang
Companies: and University of Pittsburgh
Address: 5030 Centre Ave., Pittsburgh, PA, 15213, United States
Keywords: competing risks ; joint modeling

We propose a joint modeling approach that estimates covariate effects on survival by adjusting for the informative dropout caused by the presence of competing risks. The approach allows us to set different covariates for the main event model and the competing event model, thereby allowing for the inclusion of appropriate model selection for different events. We used three estimation methods to simultaneously estimate the covariate effects and the dependence between the main and competing events. In simulations, we compared the performance of the three estimation methods. When we applied the approach to a dataset, we were able to estimate the effects of several risk factors on the development of Alzheimer's disease.

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