Decision rules for small vaccine experiments with binary outcomes based on conditional and expected power and size of the Fisher exact test

Vaccine experiments with a binary outcome typically use a small number of animals for financial and ethical reasons. The choice of a design, characterized by the total number of animals and the allocation of animals to treated and control groups, needs to be based on an assessment of change in expected size and power, with corresponding changes in the nominal significance level. This paper shows how an analysis of the conditional and the expected size and power of the Fisher-exact test, given predicted values for the proportions of success in control and treated groups, can lead to appropriate decision rules.