False Discovery Control

False Discovery Control is a statistical methodology in subgroup effectiveness analysis that governs the expected proportion of incorrectly rejected null hypotheses among all rejected hypotheses to mitigate erroneous findings in multiple testing scenarios.

260

Publications

146.1K

Citations

630

Authors

324

Institutions

Publications per year

2017–2026

100

Authors

630

  1. YB
    Yoav Benjamini

    Tel Aviv University, Israel

    13 publications · 126.7K citations

    13

    h-index

  2. AR
    Aaditya Ramdas

    Carnegie Mellon University, United States

    11 publications · 317 citations

    11

    h-index

  3. ÉR
    Étienne Roquain

    Laboratoire de Probabilités et Modèles Aléatoires, France

    7 publications · 351 citations

    7

    h-index

  4. TC
    Tommaso Cai

    University of Pennsylvania, United States

    7 publications · 484 citations

    7

    h-index

  5. SK
    Sanat K. Sarkar

    Temple University, United States

    6 publications · 226 citations

    7

    h-index

1–5 of 630

Venues

  1. The Annals of Statistics

    17 publications · 12.3K citations

    15

    h-index

  2. Journal of the American Statistical Association

    15 publications · 1.4K citations

    15

    h-index

  3. 14

    h-index

  4. arXiv (Cornell University)

    Repository · 15 publications · 282 citations

    13

    h-index

  5. Bioinformatics

    8 publications · 756 citations

    9

    h-index

1–5