Bias and Conditioning in Sequential Medical Trials

Randomized Controlled Trials (RCTs) are currently the gold standard within evidencebased medicine. Usually, they are conducted as sequential trials allowing for monitoring for early signs of effectiveness or harm. However, evidence from early stopped trials is often charged with being biased towards implausibly large effects (e.g., Bassler et al. 2010). To our mind, this skeptical attitude is unfounded and caused by the failure to perform appropriate conditioning in the statistical analysis of the evidence. We contend that a shift from unconditional hypothesis tests in the style of Neyman and Pearson to conditional hypothesis tests (Berger, Brown and Wolpert 1994) gives a superior appreciation of the obtained evidence and significantly improves the practice of sequential medical trials, while staying firmly rooted in frequentist methodology.