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It is often important to incorporate covariate information in the design of clinical trials. In literature there are many designs of using stratification and covariate-adaptive random- ization to balance certain known covariate. Recently, some covariate-adjusted response-adaptive (CARA) designs have been proposed and their asymptotic properties have been studied (Ann. Statist. 2007). However, these CARA designs usually have high variabilities. In this paper, a new family of covariate-adjusted response-adaptive (CARA) designs is presented. It is shown that the new designs have less variables and therefore are more efficient.
It is often important to incorporate covariate information in the design of clinical trials. In literature there are many designs of using stratification and covariate-adaptive random- ization to balance certain known covariate. Recently, some covariate-adjusted response-adaptive (CARA) designs However, these CARA designs usually have have high variabilities. It has been proposed and their asymptotic properties have been studied (Ann. Statist. 2007). However, these CARA designs usually have have high variabilities. is shown that the new designs have less variables and therefore are more efficient.