Mixed-effects Meta-regression

Mixed-Effects Meta-Regression is a statistical technique within meta-analytic methods that models the relationship between effect sizes and moderator variables by incorporating both fixed effects (systematic variation due to moderators) and random effects (residual heterogeneity across studies) to account for within- and between-study variability.

56

Publications

7.6K

Citations

374

Authors

171

Institutions

Publications per year

2017–2026

27

Authors

374

  1. JA
    José A López-López

    University of Bristol, United Kingdom

    3 publications · 340 citations

    3

    h-index

  2. EE
    Emily E. Tanner‐Smith

    Vanderbilt University, United States

    3 publications · 1.8K citations

    3

    h-index

  3. AG
    Antonio Gasparrini

    London School of Hygiene & Tropical Medicine, United Kingdom

    2 publications · 403 citations

    2

    h-index

  4. ET
    Elizabeth Tipton

    Columbia University, United States

    2 publications · 703 citations

    2

    h-index

  5. HD
    Hristos Doucouliagos

    Deakin University, Australia

    2 publications · 228 citations

    2

    h-index

1–5 of 374

Venues

  1. Research Synthesis Methods

    5 publications · 1.1K citations

    5

    h-index

  2. Statistics in Medicine

    5 publications · 688 citations

    5

    h-index

  3. 4

    h-index

  4. PubMed

    Repository · 3 publications · 245 citations

    3

    h-index

  5. Biostatistics

    2 publications · 377 citations

    2

    h-index

1–5