A decision theoretic approach to sample size determination in clinical trials.

In this paper, we discuss a Behavioral Bayes approach to the determination of sample size in phase III clinical trials for which the data are assumed to come from a normal distribution for which the mean and variance are both unknown. Software is described which minimizes the expected net cost as a function of the sample size, thereby establishing the optimal sample size. This methodology extends previous work by the assumption of unknown variance. Numerical examples show that the more general model can have a large effect on the optimal sample size, compared with a procedure which uses the known variance model with an estimate of the variance.