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A traditional way to design a binary response experiment is to design the experiment to be most efficient for a best guess of the parameter values. A design which is optimal for a best guess however may not be efficient for parameter values close to that best guess. We propose designs which formally account for the prior uncertainty in the parameter values. A design for a situation where the best guess has substantial uncertainty attached to it is very different from a design for a situationdoi:10.1016/0378-3758(89)90004-9 fatcat:thrvfqadzraozaz4t4aava2lqm