Sample size determination for the false discovery rate.

Abstract

There is not a widely applicable method to determine the sample size for experiments basing statistical significance on the false discovery rate (FDR). We propose and develop the anticipated FDR (aFDR) as a conceptual tool for determining sample size. We derive mathematical expressions for the aFDR and anticipated average statistical power. These expressions are used to develop a general algorithm to determine sample size. We provide specific details on how to implement the algorithm for a k-group (k > or = 2) comparisons. The algorithm performs well for k-group comparisons in a series of traditional simulations and in a real-data simulation conducted by resampling from a large, publicly available dataset. Documented S-plus and R code libraries are freely available from www.stjuderesearch.org/depts/biostats.