Common Language Effect Size

Common Language Effect Size is a probabilistic interpretive metric that expresses the magnitude of a difference between two groups as the probability that a randomly selected score from one group will be greater than a randomly selected score from the other group, thereby translating statistical effects into intuitively accessible language for non-specialist audiences.

20

Publications

4.3K

Citations

41

Authors

31

Institutions

Publications per year

2017–2026

3

Variants

ClesCommon Language Effect Size Statistic

Authors

41

  1. WP
    William P. Dunlap

    Tulane University, United States

    3 publications · 133 citations

    3

    h-index

  2. HD
    Harold D. Delaney

    University of New Mexico, United States

    2 publications · 1.7K citations

    2

    h-index

  3. KO
    Kenneth O. McGraw

    University of Mississippi, United States

    2 publications · 975 citations

    2

    h-index

  4. PG
    Paul Gendreau

    University of New Brunswick, Canada

    1 publications · 51 citations

    1

    h-index

  5. DK
    Dina Krasikova

    The University of Texas at San Antonio, United States

    1 publications · 11 citations

    1

    h-index

1–5 of 41

Venues

  1. Psychological Bulletin

    4 publications · 1.1K citations

    4

    h-index

  2. Psychological Methods

    3 publications · 545 citations

    3

    h-index

  3. Journal of Educational and Behavioral Statistics

    2 publications · 1.7K citations

    2

    h-index

  4. Journal of Applied Psychology

    2 publications · 78 citations

    2

    h-index

  5. Criminal Justice and Behavior

    2 publications · 174 citations

    2

    h-index

1–5