Abstract
In microarray and other genomic studies, in view of an abundance of genes, one statistical approach is to hold the family wise error rate to a prescribed limit while controlling the false discovery rate by suitable multiple hypothesis testing procedures, thus generally compromising the power properties to a certain extent. Since the genes are not generally independent or even marginally identically distributed, model flexibility is an essential task regardless of dependent structures among genes. In this respect, incorporating a version of the Chen-Stein theorem, two-stage procedure has been considered; it seems to have better average power without much elevation of false discovery rate compared to single-stage procedure. Simulation studies and applications in microarray data models are also stressed with the methodological developments.
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