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Optimal adaptive generalized Polya urn design for multi-arm clinical trials

Listed author(s):
  • Yuan, Ao
  • Chai, Gen Xiang
Registered author(s):

    A class of optimal adaptive multi-arm clinical trial designs is proposed based on an extended generalized Polya urn (GPU) model. The design is applicable to both the qualitative and quantitative responses and achieves, asymptotically, some pre-specified optimality criterion. Such criterion is specified by a functional of the response distributions and is implemented through the relationship between the design matrix and its first eigenvector. The asymptotic properties of the design are studied using the existing methods on GPU. Some examples for commonly used clinical designs are given as illustration.

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    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 99 (2008)
    Issue (Month): 1 (January)
    Pages: 1-24

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    Handle: RePEc:eee:jmvana:v:99:y:2008:i:1:p:1-24
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    1. Janson, Svante, 2004. "Functional limit theorems for multitype branching processes and generalized PĆ³lya urns," Stochastic Processes and their Applications, Elsevier, vol. 110(2), pages 177-245, April.
    2. Bai, Z. D. & Hu, Feifang, 1999. "Asymptotic theorems for urn models with nonhomogeneous generating matrices," Stochastic Processes and their Applications, Elsevier, vol. 80(1), pages 87-101, March.
    3. William F. Rosenberger & Nigel Stallard & Anastasia Ivanova & Cherice N. Harper & Michelle L. Ricks, 2001. "Optimal Adaptive Designs for Binary Response Trials," Biometrics, The International Biometric Society, vol. 57(3), pages 909-913, 09.
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