On the performance of FDR control: constraints and a partial solution

DOI10.1214/009053607000000037zbMath1125.62075arXiv0710.3287OpenAlexW3105450569MaRDI QIDQ2456005

Zhiyi Chi

Publication date: 17 October 2007

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0710.3287

zbMATH Keywords

Bahadur representationpowermultiple hypothesis testingBenjamini-HochbergpFDR

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Hypothesis testing in multivariate analysis (62H15) Signal detection and filtering (aspects of stochastic processes) (60G35) Paired and multiple comparisons; multiple testing (62J15)

Related Items (18)

Powerful multiple testing of paired null hypotheses using a latent graph model ⋮ FarmTest: Factor-Adjusted Robust Multiple Testing With Approximate False Discovery Control ⋮ A double application of the Benjamini-Hochberg procedure for testing batched hypotheses ⋮ A scoring criterion for rejection of clustered \(p\)-values ⋮ Strong consistency and asymptotic normality for quantities related to the Benjamini-Hochberg false discovery rate procedure ⋮ A scan procedure for multiple testing: beyond threshold-type procedures ⋮ A central limit theorem for the Benjamini-Hochberg false discovery proportion under a factor model ⋮ Robust high-dimensional tuning free multiple testing ⋮ Exact calculations for false discovery proportion with application to least favorable configura\-tions ⋮ Simultaneous critical values for \(t\)-tests in very high dimensions ⋮ Asymptotic Bayes-optimality under sparsity of some multiple testing procedures ⋮ False discovery rate control with multivariate \(p\)-values ⋮ Asymptotic properties of false discovery rate controlling procedures under independence ⋮ On false discovery rate thresholding for classification under sparsity ⋮ On the false discovery rate and an asymptotically optimal rejection curve ⋮ Data Volume and Power of Multiple Tests with Small Sample Size Per Null ⋮ Adaptive \(p\)-value weighting with power optimality ⋮ New procedures controlling the false discovery proportion via Romano-Wolf's heuristic

Uses Software

• R

Cites Work

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