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B1210
Title: Response adaptive designs with asymptotic optimality Authors:  Yanqing Yi - Memorial University of Newfoundland (Canada) [presenting]
Abstract: The asymptotic optimality of statistical inference for response adaptive designs, which have the ethical advantages over the traditional methods for clinical trials, is discussed. The upper bound of statistical power of asymptotically level tests is derived and the Wald statistic is shown to be asymptotically optimal in terms of achieving the upper bound. The rates of coverage error probability of the confidence interval are proven to depend on the convergence rate of the allocation proportions for non-normally distributed responses. When the response density functions are normal density functions, it is proven that the coverage error probability and the type I error rate has the order of $n^{-1}$.