Study Weights

Study Weights is a statistical weighting mechanism in random-effects models that assigns each study a weight proportional to the inverse of its total variance, combining both within-study and between-study variability, to reflect its relative contribution to the overall effect size estimate.

76

Publications

6.6K

Citations

252

Authors

152

Institutions

Publications per year

2017–2026

23

Variants

Inverse-variance Weights

Authors

252

  1. MR
    Michael Reich

    University of California, Berkeley, United States

    3 publications · 347 citations

    3

    h-index

  2. RD
    Richard D Riley

    Keele University, United Kingdom

    3 publications · 123 citations

    3

    h-index

  3. BZ
    Ben Zipperer

    University of Massachusetts Amherst, United States

    3 publications · 347 citations

    3

    h-index

  4. SA
    Sylvia Allegretto

    University of California, Berkeley, United States

    3 publications · 347 citations

    3

    h-index

  5. AD
    Arindrajit Dubé

    University of Massachusetts Amherst, United States

    3 publications · 347 citations

    3

    h-index

1–5 of 252

Venues

  1. Statistics in Medicine

    7 publications · 494 citations

    7

    h-index

  2. JAMA Network Open

    2 publications · 301 citations

    2

    h-index

  3. Journal of Biopharmaceutical Statistics

    JBS · 2 publications · 61 citations

    2

    h-index

  4. Statistical Methods in Medical Research

    2 publications · 103 citations

    2

    h-index

  5. PubMed

    Repository · 2 publications · 37 citations

    2

    h-index

1–5