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Estimation of treatment effect following a clinical trial with adaptive design
Xiaolong Luo1, Mingyu Li, Weichung Joe Shih
1Celgene Corporation, Summit, NJ, USA. xluo@celgene.com
Abstract:
Parameter estimation following an adaptive design or group sequential design has been extremely challenging due to potential random high from its face value estimate. In this paper, we introduce a new framework to model clinical trial data flow based on a marked point process (MPP). The MPP model allows us to use methods of stochastic calculus for analyses of any adaptive clinical trial. As an example, we apply this method to a two stage treatment selection design and derive a procedure to estimate the treatment effect. Numerical examples will be used to evaluate the performance of the proposed procedure.
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