Power For Two-sample Tests

Power for Two-Sample Tests is the probability that a statistical test correctly rejects the null hypothesis when a true difference exists between the parameters of two independent populations, distinguished from other power concepts by its specific application to designs comparing two distinct sample groups.

440

Publications

34.9K

Citations

697

Authors

341

Institutions

Publications per year

2017–2026

38

Authors

697

  1. RR
    Rand R. Wilcox

    University of Southern California, United States

    7 publications · 382 citations

    7

    h-index

  2. SO
    Stephen Olejnik

    University of Georgia, United States

    6 publications · 376 citations

    6

    h-index

  3. JE
    John E. Hewett

    University of Missouri, United States

    5 publications · 103 citations

    5

    h-index

  4. JE
    John E. Overall

    The University of Texas Medical Branch at Galveston, United States

    5 publications · 110 citations

    5

    h-index

  5. JF
    Joan F. Hilton

    University of California, San Francisco, United States

    4 publications · 208 citations

    4

    h-index

1–5 of 697

Venues

  1. Biometrics

    28 publications · 2.2K citations

    22

    h-index

  2. Journal of the American Statistical Association

    32 publications · 2.6K citations

    21

    h-index

  3. Statistics in Medicine

    24 publications · 1.3K citations

    21

    h-index

  4. Biometrika

    23 publications · 989 citations

    18

    h-index

  5. The Annals of Mathematical Statistics

    16 publications · 3.2K citations

    14

    h-index

1–5