Bayesian Binomial Regression

Bayesian Binomial Regression is a statistical modeling framework within the class of Bayesian generalized linear models that specifies a binomial likelihood for the response variable and incorporates prior distributions on model parameters to infer posterior distributions under a Bayesian paradigm.

18

Publications

842

Citations

85

Authors

67

Institutions

Publications per year

2017–2026

11

Authors

85

  1. DA
    D. Andrew Brown

    University of Georgia, United States

    3 publications · 112 citations

    3

    h-index

  2. MJ
    Michael J. Yabsley

    University of Georgia, United States

    3 publications · 112 citations

    3

    h-index

  3. CS
    Christopher S. McMahan

    Clemson University, United States

    3 publications · 112 citations

    3

    h-index

  4. SS
    Stella Self

    University of South Carolina, United States

    3 publications · 112 citations

    3

    h-index

  5. JR
    Jenna R. Gettings

    University of Georgia, United States

    3 publications · 112 citations

    3

    h-index

1–5 of 85

Venues

  1. Parasites & Vectors

    2 publications · 91 citations

    2

    h-index

  2. PLoS ONE

    2 publications · 61 citations

    2

    h-index

  3. The American Statistician

    2 publications · 125 citations

    2

    h-index

  4. Journal of Exposure Science & Environmental Epidemiology

    JESEE · 1 publications · 16 citations

    1

    h-index

  5. Statistics in Medicine

    1 publications · 117 citations

    1

    h-index

1–5