Bayesian Categorical Data Analysis

Bayesian Categorical Data Analysis is a branch of statistical methodology that applies Bayesian inference to categorical data, distinguished by its use of prior distributions and posterior updating for discrete outcomes within hierarchical or multinomial structures.

121

Publications

5.6K

Citations

282

Authors

176

Institutions

Publications per year

2017–2026

24

Authors

282

  1. DB
    David B. Dunson

    Duke University, United States

    5 publications · 423 citations

    5

    h-index

  2. CD
    Carlos Daniel Paulino

    Instituto Superior Técnico, Portugal

    4 publications · 159 citations

    4

    h-index

  3. TL
    Tom Leonard

    University of Wisconsin–Madison, United States

    4 publications · 192 citations

    4

    h-index

  4. AA
    Alan Agresti

    University of Florida, United States

    4 publications · 298 citations

    4

    h-index

  5. JW
    Jai Won Choi

    National Center for Health Statistics, United States

    3 publications · 73 citations

    3

    h-index

1–5 of 282

Venues

  1. Biometrics

    12 publications · 774 citations

    11

    h-index

  2. Statistics in Medicine

    13 publications · 305 citations

    11

    h-index

  3. 9

    h-index

  4. Biometrika

    4 publications · 107 citations

    4

    h-index

  5. 4

    h-index

1–5