Bivariate Mixed Model Analysis

Bivariate Mixed Model Analysis is a statistical method that extends univariate mixed models to jointly analyze two traits by estimating their genetic and environmental variance components and covariances using random effects structures in a multivariate framework.

66

Publications

4.4K

Citations

251

Authors

136

Institutions

Publications per year

2017–2026

15

Authors

251

  1. HJ
    Hélène Jacqmin‐Gadda

    Inserm, France

    3 publications · 222 citations

    3

    h-index

  2. PJ
    Paul J. Catalano

    Dana-Farber Cancer Institute, United States

    3 publications · 288 citations

    3

    h-index

  3. LR
    Louise Ryan

    Harvard University, United States

    2 publications · 277 citations

    2

    h-index

  4. CW
    Claire Welsh

    University of Glasgow, United Kingdom

    2 publications · 36 citations

    2

    h-index

  5. GC
    Geneviève Chêne

    Inserm, France

    2 publications · 133 citations

    2

    h-index

1–5 of 251

Venues

  1. Statistics in Medicine

    5 publications · 626 citations

    5

    h-index

  2. Biometrics

    3 publications · 322 citations

    3

    h-index

  3. Journal of Animal Science

    3 publications · 90 citations

    3

    h-index

  4. 3

    h-index

  5. Journal of Biopharmaceutical Statistics

    JBS · 2 publications · 100 citations

    2

    h-index

1–5