Operating Characteristics and Extensions of the False Discovery Rate Procedure
错误发现率程序的运行特征与扩展AI 解读 ↓
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错误发现率程序的运行特征与扩展AI 解读 ↓
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Summary We investigate the operating characteristics of the Benjamini–Hochberg false discovery rate procedure for multiple testing. This is a distribution-free method that controls the expected fraction of falsely rejected null hypotheses among those rejected. The paper provides a framework for understanding more about this procedure. We first study the asymptotic properties of the ‘deciding point' D that determines the critical p-value. From this, we obtain explicit asymptotic expressions for a particular risk function. We introduce the dual notion of false non-rejections and we consider a risk function that combines the false discovery rate and false non-rejections. We also consider the optimal procedure with respect to a measure of conditional risk.