1. Multiple testing with discrete data: proportion of true null hypotheses and two adaptive FDR procedures
- Author
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Chen, Xiongzhi, Doerge, Rebecca W., and Heyse, Joseph F.
- Subjects
Statistics - Methodology - Abstract
We consider multiple testing with false discovery rate (FDR) control when p-values have discrete and heterogeneous null distributions. We propose a new estimator of the proportion of true null hypotheses and demonstrate that it is less upwardly biased than Storey's estimator and two other estimators. The new estimator induces two adaptive procedures, i.e., an adaptive Benjamini-Hochberg (BH) procedure and an adaptive Benjamini-Hochberg-Heyse (BHH) procedure. We prove that the the adaptive BH procedure is conservative non-asymptotically. Through simulation studies, we show that these procedures are usually more powerful than their non-adaptive counterparts and that the adaptive BHH procedure is usually more powerful than the adaptive BH procedure and a procedure based on randomized p-value. The adaptive procedures are applied to a study of HIV vaccine efficacy, where they identify more differentially polymorphic positions than the BH procedure at the same FDR level., Comment: This version is essentially a different paper than the previous one. A new estimator of the proportion of true null hypotheses has been developed, and it induces two adaptive FDR procedures. One such procedure has been proved to be conservative non-asymptotically, and the other has been empirically shown to be conservative
- Published
- 2014
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