Permutation-based Exact Inference

Permutation-Based Exact Inference is a statistical inference method that belongs to the class of exact inference techniques for categorical data, distinguished by its reliance on permutation principles to compute exact p-values and confidence intervals without invoking asymptotic approximations.

20

Publications

2.6K

Citations

37

Authors

24

Institutions

Publications per year

2017–2026

3

Authors

37

  1. NR
    Nitin R. Patel

    Cytel (United States), United States

    3 publications · 563 citations

    3

    h-index

  2. CR
    Cyrus R. Mehta

    Cytel (United States), United States

    3 publications · 563 citations

    3

    h-index

  3. KJ
    Kenneth J. Berry

    Colorado State University, United States

    2 publications · 36 citations

    2

    h-index

  4. PW
    Paul W. Mielke

    Colorado State University, United States

    2 publications · 36 citations

    2

    h-index

  5. MP
    Markus Pauly

    TU Dortmund University, Germany

    2 publications · 33 citations

    2

    h-index

1–5 of 37

Venues

  1. Statistical Science

    3 publications · 1.3K citations

    3

    h-index

  2. 3

    h-index

  3. Psychological Reports

    1 publications · 10 citations

    1

    h-index

  4. Statistical Methods in Medical Research

    1 publications · 13 citations

    1

    h-index

  5. World Politics

    1 publications · 96 citations

    1

    h-index

1–5