Permutation-based Adjustment

Permutation-Based Adjustment is a statistical method for controlling family-wise error rate that relies on the resampling of observed data under permutations of the experimental design to empirically estimate the null distribution of test statistics.

30

Publications

2.2K

Citations

105

Authors

82

Institutions

Publications per year

2017–2026

8

Authors

105

  1. JL
    Jian Liang

    Chinese Academy of Sciences, China

    2 publications · 189 citations

    2

    h-index

  2. RH
    Ran He

    Institute of Automation, China

    2 publications · 189 citations

    2

    h-index

  3. DM
    David M. Murray

    University of Minnesota, United States

    2 publications · 152 citations

    2

    h-index

  4. TT
    Tieniu Tan

    Institute of Automation, China

    2 publications · 189 citations

    2

    h-index

  5. XG
    Xiaoyi Gao

    Washington University in St. Louis, United States

    2 publications · 481 citations

    2

    h-index

1–5 of 105

Venues

  1. Statistics in Medicine

    4 publications · 189 citations

    4

    h-index

  2. Genetic Epidemiology

    3 publications · 500 citations

    3

    h-index

  3. Biometrics

    2 publications · 70 citations

    2

    h-index

  4. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 2 publications · 32 citations

    2

    h-index

  5. NeuroImage

    2 publications · 188 citations

    2

    h-index

1–5