Within-study Variance

Within-Study Variance is the component of variability in observed effect sizes that arises from sampling error and measurement imprecision within individual studies, distinguished from between-study variation by reflecting stochastic fluctuations unique to each study’s data collection process.

255

Publications

39.2K

Citations

1K

Authors

426

Institutions

Publications per year

2017–2026

57

Authors

1K

  1. DJ
    Dan Jackson

    MRC Biostatistics Unit, United Kingdom

    9 publications · 2.6K citations

    9

    h-index

  2. RR
    Robert Rosenthal

    Harvard University Press, United States

    8 publications · 3K citations

    8

    h-index

  3. MM
    Mariola Moeyaert

    University at Albany, State University of New York, United States

    5 publications · 225 citations

    5

    h-index

  4. SN
    S. Natasha Beretvas

    The University of Texas at Austin, United States

    5 publications · 252 citations

    5

    h-index

  5. JM
    John M. Ferron

    University of South Florida, United States

    5 publications · 244 citations

    5

    h-index

1–5 of 1K

Venues

  1. Statistics in Medicine

    16 publications · 1.1K citations

    14

    h-index

  2. Psychological Methods

    9 publications · 2.3K citations

    9

    h-index

  3. 9

    h-index

  4. Psychological Bulletin

    8 publications · 897 citations

    8

    h-index

  5. Biometrics

    7 publications · 229 citations

    7

    h-index

1–5