Power Curves

Power Curves is a graphical representation in statistical hypothesis testing that depicts the relationship between statistical power and effect size for a given sample size and significance level, serving as a tool in sample size planning to evaluate the sensitivity of a study design.

747

Publications

339.7K

Citations

1.6K

Authors

780

Institutions

Publications per year

2017–2026

147

Authors

1.6K

  1. GS
    Gwowen Shieh

    National Yang Ming Chiao Tung University, Taiwan

    7 publications · 245 citations

    7

    h-index

  2. AF
    Andrés Feijóo

    Universidade de Vigo, Spain

    6 publications · 255 citations

    6

    h-index

  3. DI
    David Infield

    University of Strathclyde, United Kingdom

    6 publications · 322 citations

    6

    h-index

  4. JC
    Jacob Cohen

    New York University, United States

    6 publications · 2.1K citations

    6

    h-index

  5. KE
    Keith E. Muller

    University of North Carolina at Chapel Hill, United States

    6 publications · 100.5K citations

    6

    h-index

1–5 of 1.6K

Venues

  1. Journal of the American Statistical Association

    20 publications · 39.8K citations

    16

    h-index

  2. Statistics in Medicine

    18 publications · 2.5K citations

    16

    h-index

  3. Biometrika

    16 publications · 898 citations

    14

    h-index

  4. The Annals of Mathematical Statistics

    12 publications · 430 citations

    12

    h-index

  5. Educational and Psychological Measurement

    13 publications · 809 citations

    12

    h-index

1–5