Empirical P-values

Empirical P-Values is a statistical metric that quantifies the significance of a test statistic by estimating the probability of observing a value as or more extreme than the one obtained under the null hypothesis, derived through simulation or resampling methods rather than theoretical distributional assumptions.

81

Publications

13.1K

Citations

295

Authors

182

Institutions

Publications per year

2017–2026

14

Authors

295

  1. AA
    Alan Anticevic

    Yale University, United States

    2 publications · 592 citations

    2

    h-index

  2. JB
    Joshua B. Burt

    Yale University, United States

    2 publications · 592 citations

    2

    h-index

  3. JD
    John D. Murray

    Yale University, United States

    2 publications · 592 citations

    2

    h-index

  4. KR
    Kirk R. Wilhelmus

    Baylor College of Medicine, United States

    2 publications · 24 citations

    2

    h-index

  5. JP
    John P. A. Ioannidis

    Stanford University, United States

    2 publications · 2.5K citations

    2

    h-index

1–5 of 295

Venues

  1. 3

    h-index

  2. 3

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  3. The American Statistician

    2 publications · 223 citations

    2

    h-index

  4. SSRN Electronic Journal

    Repository · 2 publications · 62 citations

    2

    h-index

  5. Canadian Journal of Statistics

    CJS · 2 publications · 48 citations

    2

    h-index

1–5