Heterogeneity Testing

Heterogeneity Testing is a statistical method used in Mendelian randomization studies to assess whether causal effect estimates derived from multiple genetic variants are consistent with each other, thereby identifying potential violations of the instrumental variable assumptions due to biological or methodological differences across variants.

175

Publications

14.7K

Citations

566

Authors

274

Institutions

Publications per year

2017–2026

43

Authors

566

  1. HJ
    H. J. Keselman

    University of Manitoba, Canada

    8 publications · 387 citations

    8

    h-index

  2. RR
    Rand R. Wilcox

    University of Southern California, United States

    4 publications · 207 citations

    4

    h-index

  3. GD
    George Davey Smith

    University of Bristol, United Kingdom

    3 publications · 185 citations

    3

    h-index

  4. SB
    Stephen Burgess

    University of Cambridge, United Kingdom

    3 publications · 329 citations

    3

    h-index

  5. RE
    Robert E. Tarone

    National Cancer Institute, United States

    3 publications · 125 citations

    3

    h-index

1–5 of 566

Venues

  1. Biometrika

    12 publications · 1.4K citations

    11

    h-index

  2. Biometrics

    8 publications · 739 citations

    8

    h-index

  3. 6

    h-index

  4. 4

    h-index

  5. Computational Statistics & Data Analysis

    CSDA · 4 publications · 87 citations

    4

    h-index

1–5