Reducing the number of inferior treatments in clinical trials.
In clinical trials comparing two treatments, one would often like to control the probability of erroneous decision while minimizing not the total sample size but the number of patients given the inferior treatment. To do this obviously requires that one use a datadependent allocation rule for the two treatments rather than the conventional equal sample size scheme, whether fixed or sequential. We show here how this may be done in the case of deciding which of two normally distributed treatment effects has the greater mean, when the variances are assumed to be equal and known. Similar methods can be used under other hypotheses on the underlying probability distributions, and will provide a considerable increase in flexibility in the design of sequential clinical trials.
D002986:Clinical Trials as Topic; D006801:Humans; D008962:Models, Theoretical; D012107:Research Design; D013223:Statistics as Topic; D013812:Therapeutics