Weight-function Models

Weight-Function Models is a statistical framework that belongs to the class of selection models used in meta-analysis, distinguished by its explicit modeling of the probability that a study is published or included in the analysis as a function of its sample size or precision, thereby addressing publication bias and small-study effects through a weighted likelihood approach.

42

Publications

2.3K

Citations

88

Authors

58

Institutions

Publications per year

2017–2026

9

Variants

Weight Function Models

Authors

88

  1. JL
    Jack L. Vevea

    University of Chicago, United States

    3 publications · 161 citations

    3

    h-index

  2. NS
    Nancy Silliman

    Center for Drug Evaluation and Research, United States

    3 publications · 74 citations

    3

    h-index

  3. BM
    Brad McKay

    McMaster University, Canada

    2 publications · 44 citations

    2

    h-index

  4. JH
    Julia Hussien

    University of Ottawa, Canada

    2 publications · 44 citations

    2

    h-index

  5. HF
    H. F. Bueckner

    General Electric (United States), United States

    2 publications · 65 citations

    2

    h-index

1–5 of 88

Venues

  1. Statistical Science

    3 publications · 965 citations

    3

    h-index

  2. Psychological Methods

    2 publications · 150 citations

    2

    h-index

  3. Journal of Applied Mechanics

    2 publications · 56 citations

    2

    h-index

  4. Engineering Fracture Mechanics

    2 publications · 56 citations

    2

    h-index

  5. 2

    h-index

1–5