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Title: Response Adaptive Designs in the Presence of Mismeasurement
Authors: LI, XUAN
Supervisor: Wang, Xikui (Statistics)
Examining Committee: Alfa, Attahiru (Electrical and Computer Engineering) Fu, James (Statistics) Johnson, Brad (Statistics) Yi, Grace Y. (University of Waterloo)
Graduation Date: October 2012
Keywords: Clinical trials
Optimal allocation
Response adaptive designs
Variance-penalized criterion
Issue Date: 2012
Publisher: Elsevier
Citation: Journal of Statistical Planning and Inference 142 (2012), pp. 2128-2135
Abstract: Response adaptive randomization represents a major advance in clinical trial methodology that helps balance the benefits of the collective and the benefits of the individual and improves efficiency without undermining the validity and integrity of the clinical research. Response adaptive designs use information so far accumulated from the trial to modify the randomization procedure and deliberately bias treatment allocation in order to assign more patients to the potentially better treatment. No attention has been paid to incorporating the problem of errors-in-variables in adaptive clinical trials. In this work, some important issues and methods of response adaptive design of clinical trials in the presence of mismeasurement are examined. We formulate response adaptive designs when the dichotomous response may be misclassified. We consider the optimal allocations under various objectives, investigate the asymptotically best response adaptive randomization procedure, and discuss effects of misclassification on the optimal allocation. We derive explicit expressions for the variance-penalized criterion with misclassified binary responses and propose a new target proportion of treatment allocation under the criterion. A real-life clinical trial and some related simulation results are also presented.
Appears in Collection(s):FGS - Electronic Theses & Dissertations (Public)

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