Statistical Methodology Commons^™

Optimal Sample Size For Multiple Testing: The Case Of Gene Expression Microarrays, Peter Muller, Giovanni Parmigiani, Christian Robert, Judith Rousseau

Johns Hopkins University, Dept. of Biostatistics Working Papers

We consider the choice of an optimal sample size for multiple comparison problems. The motivating application is the choice of the number of microarray experiments to be carried out when learning about differential gene expression. However, the approach is valid in any application that involves multiple comparisons in a large number of hypothesis tests. We discuss two decision problems in the context of this setup: the sample size selection and the decision about the multiple comparisons. We adopt a decision theoretic approach,using loss functions that combine the competing goals of discovering as many ifferentially expressed genes as possible, while keeping …