Adjacent-categories Models

Adjacent-Categories Models is a statistical regression framework for ordinal categorical outcomes that generalizes logistic regression by modeling the log-odds of transitioning between consecutive categories using adjacent-category probabilities, thereby distinguishing it from other ordinal models that rely on cumulative or cumulative-adjacent probabilities.

49

Publications

3.3K

Citations

112

Authors

75

Institutions

Publications per year

2017–2026

4

Variants

Adjacent-category Models

Authors

112

  1. AA
    Alan Agresti

    University of Florida, United States

    4 publications · 564 citations

    4

    h-index

  2. MW
    Morten Wang Fagerland

    Oslo University Hospital, Norway

    2 publications · 128 citations

    2

    h-index

  3. KF
    Karim F. Hirji

    University of California, Los Angeles, United States

    2 publications · 40 citations

    2

    h-index

  4. AS
    Andrew S. Fullerton

    Oklahoma State University, United States

    2 publications · 54 citations

    2

    h-index

  5. FV
    Fabien Valet

    Université Paris Cité, France

    2 publications · 37 citations

    2

    h-index

1–5 of 112

Venues

  1. Statistical Modelling

    3 publications · 272 citations

    3

    h-index

  2. Statistics in Medicine

    3 publications · 64 citations

    3

    h-index

  3. Sociological Methods & Research

    SMR · 3 publications · 41 citations

    3

    h-index

  4. The American Statistician

    2 publications · 94 citations

    2

    h-index

  5. 2

    h-index

1–5