![]() We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We compute the type I error inflation as a function of the time trend magnitude to determine in which contexts the problem is most exacerbated. ![]() This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. The most common cause of this phenomenon is changes in the characteristics of recruited patients-referred to as patient drift. ![]() ![]() In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. Responseāadaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates.
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