Zhu, Chunhua; Chen, Guijing Some optimal adaptive designs in clinical trials. (English) Zbl 1165.62332 Chin. J. Appl. Probab. Stat. 21, No. 1, 67-75 (2005). Summary: We consider a clinical trials scenario where patients enter the trial sequentially, and the experimenter has to adaptively select the better of two competing treatments for future applications. This is particularly important since the subjects are human patients. In this article, based on statistical validity, we discuss several optimal allocation rules in clinical trials, which depend on the unknown parameters. Then the corresponding adaptive design is proposed, and some asymptotic properties are obtained. With these asymptotic results, we show that the adaptive designs in this article lead to asymptotically optimal allocations. MSC: 62L05 Sequential statistical design 62P10 Applications of statistics to biology and medical sciences; meta analysis 62K05 Optimal statistical designs Keywords:urn model; strong convergence; asymptotic normality; adaptive design PDFBibTeX XMLCite \textit{C. Zhu} and \textit{G. Chen}, Chin. J. Appl. Probab. Stat. 21, No. 1, 67--75 (2005; Zbl 1165.62332)