Power Analysis

Power Analysis is a statistical procedure used in experimental design to determine the minimum sample size required to detect an effect of a given size with a specified degree of confidence, thereby distinguishing it from related analytical methods by its focus on the sensitivity and reliability of hypothesis tests within randomized experiments, including those in A/B testing and community organizing research.

4.1K

Publications

847.4K

Citations

7.2K

Authors

2.4K

Institutions

Publications per year

2017–2026

640

Authors

7.2K

  1. RR
    Rand R. Wilcox

    University of Southern California, United States

    27 publications · 1.8K citations

    21

    h-index

  2. KE
    Keith E. Muller

    University of North Carolina at Chapel Hill, United States

    26 publications · 101.7K citations

    20

    h-index

  3. JA
    James Algina

    University of Florida, United States

    24 publications · 3.6K citations

    20

    h-index

  4. SO
    Stephen Olejnik

    University of Georgia, United States

    20 publications · 3.8K citations

    17

    h-index

  5. DL
    Daniël Lakens

    Eindhoven University of Technology, Netherlands

    17 publications · 6K citations

    16

    h-index

1–5 of 7.2K

Venues

  1. Statistics in Medicine

    209 publications · 18.2K citations

    63

    h-index

  2. Journal of the American Statistical Association

    159 publications · 52.5K citations

    58

    h-index

  3. Biometrics

    98 publications · 11.2K citations

    50

    h-index

  4. Psychological Methods

    63 publications · 28.7K citations

    42

    h-index

  5. Biometrika

    61 publications · 4.8K citations

    34

    h-index

1–5