![]() However, aBOIN outperformed BOIN in moderate sample sizes. ![]() Simulation studies to examine performances of the aBOIN design in small and large sample sizes revealed comparable performances for the aBOIN and original BOIN designs for small sample sizes. This modified design is called adaptive BOIN (aBOIN). Second, we propose a method to relax the fixed boundaries of the BOIN design to be adaptive, such that the accumulative information can be used more appropriately. ![]() An algorithm to automatically generate parameters for prior set-up is introduced. In this paper, we first propose a new method for developing a phase I design, Bayesian optimal interval design (BOIN), for formally incorporating historical information. Although many novel phase I designs have been developed in recent years, few studies have discussed how to incorporate external information into dose-finding designs.
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