Several recent publications have focused on statistical considerations that arise in multipopulation tailoring clinical trials that evaluate treatment effect in an overall patient population as well as one or more predefined subpopulations. This paper presents a decision-making framework applicable to these trials and evaluates the operating characteristics of this framework versus one based solely on the results of primary hypothesis tests. The operating characteristics are presented as rates of applicable errors, known as influence errors and interaction errors.
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