A note on the adaptive control of false discovery rates

By Michael A. Black. 2004

83 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ba752ea314297d1954263c8e5d341bb2dde4b1e5

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In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Mixed model prediction and small area estimation (2006, background): “It would be worthwhile to study the extent to which false discovery rates and related concepts (e.g., Benjamini and Hochberg, 1995; Black, 2004; Storey, 2002, and references cited therein) may provide better tools through which we could characterize and quantify inferential risk for such…”
Two simple sufficient conditions for FDR control (2008, methodology): “…e Because this function is now data-dependent, establishing FDR control for the resulting procedure is more delicate; it is the subject of numerous recent works (see, e.g., Black, 2004; Benjamini et al., 2006; Finner et al., 2008; see also Gavrilov et al., 2008 for an adaptive step-down procedure).”
Uncertainty and Inference for Verification Measures (2007, background): “Other recent references related to the topic include Black (2004), Cox and Wong (2004), Efron (2004), Perone Pacifico et al. (2004), Storey (2002), and Storey et al. (2004) Another aspect of hypothesis testing that has not been much discussed in the atmospheric science literature [Ventura et al.…”
Adaptive FDR control under independence and dependence (2007, methodology): “In this context, the challenge of adaptive control of the FDR (e.g., Benjamini and Hochberg, 2000; Black, 2004) is to integrate an estimation of the unknown proportion π0 in the threshold of the previous procedures and to prove that the FDR is still rigorously controlled by α.”
Implementing false discovery rate control: increasing your power (2005, methodology): “Their FDR procedure exploits estimation of the proportion of true null hypotheses among all tests, and is more powerful than the 1995 Benjamini and Hochberg procedure and equally powerful to the sharpened 2000 Benjamini and Hochberg procedure (Black 2004).”
Using false discovery rates for multiple comparisons in ecology and evolution (2011, background): “The only difference between FDR and pFDR is the way in which each quantity deals with the rare situation in which no comparison is called significant: the FDR is set to zero while the pFDR is undefined (Black 2004).”
Controlling the familywise error rate with plug‐in estimator for the proportion of true null hypotheses (2009, methodology): “t/, t ∈ [0, 1], was given in Genovese and Wasserman (2004). Among others, they introduced the term purity which means that ess inft{f.t/}=0, where f denotes the density with respect to F. This condition was also utilized in Swanepoel (1999). In connection with adaptive FDR control Black (2004) explo”
Estimation of a two‐component mixture model with applications to multiple testing (2012, background): “See Storey (2002), Black (2004), Langaas et al. (2005), Benjamini et al. (2006), and Donoho and Jin (2004) for a discussion on the importance of efficient estimation of α0 and some proposed estimators.”
BMC Bioinformatics (2005, unknown): “Careful simulation studies on the comparison of performance of π 0 estimation methods are done by Black [9] and Langaas et al. [10].”