Egger's Test

Egger's Test is a statistical method for detecting publication bias in meta-analyses by regressing the standardized effect size against its precision, where the presence of asymmetry in the funnel plot suggests small-study effects indicative of potential bias.

222

Publications

52.5K

Citations

855

Authors

384

Institutions

Publications per year

2017–2026

144

Variants

Egger's RegressionEgger's Regression Test

Authors

855

  1. JB
    Jack Bowden

    University of Bristol, United Kingdom

    7 publications · 11.1K citations

    7

    h-index

  2. GD
    George Davey Smith

    University of Bristol, United Kingdom

    6 publications · 10.8K citations

    6

    h-index

  3. JA
    Jonathan A C Sterne

    University of Bristol, United Kingdom

    6 publications · 13.8K citations

    6

    h-index

  4. AJ
    Alex J. Sutton

    University of Leicester, United Kingdom

    5 publications · 9.8K citations

    5

    h-index

  5. JL
    Jack L. Vevea

    University of Chicago, United States

    5 publications · 792 citations

    5

    h-index

1–5 of 855

Venues

  1. PubMed

    Repository · 7 publications · 257 citations

    7

    h-index

  2. Research Synthesis Methods

    6 publications · 1.4K citations

    6

    h-index

  3. Journal of Clinical Epidemiology

    6 publications · 9.7K citations

    6

    h-index

  4. Frontiers in Microbiology

    5 publications · 203 citations

    5

    h-index

  5. Frontiers in Endocrinology

    5 publications · 122 citations

    5

    h-index

1–5