Dynamic Logistic Regression

Dynamic Logistic Regression is a statistical modeling framework within the class of generalized linear models that extends standard logistic regression by incorporating time-varying coefficients or parameters to account for temporal dynamics in repeated categorical outcome data.

30

Publications

762

Citations

97

Authors

75

Institutions

Publications per year

2017–2026

8

Authors

97

  1. HO
    Hannu Oja

    3 publications · 48 citations

    3

    h-index

  2. TH
    Tyler H. McCormick

    University of Washington, United States

    2 publications · 112 citations

    2

    h-index

  3. JT
    Jim Todd

    London School of Hygiene & Tropical Medicine, United Kingdom

    2 publications · 25 citations

    2

    h-index

  4. PM
    Peter Mugyenyi

    Joint Clinical Research Centre, Uganda

    2 publications · 25 citations

    2

    h-index

  5. SK
    Sylvia Kiwuwa-Muyingo

    London School of Hygiene & Tropical Medicine, United Kingdom

    2 publications · 25 citations

    2

    h-index

1–5 of 97

Venues

  1. Statistics in Medicine

    3 publications · 63 citations

    3

    h-index

  2. BMC Infectious Diseases

    2 publications · 25 citations

    2

    h-index

  3. International Journal of Forecasting

    2 publications · 59 citations

    2

    h-index

  4. American Journal of Agricultural Economics

    1 publications · 50 citations

    1

    h-index

  5. Journal of Migration and Health

    1 publications · 20 citations

    1

    h-index

1–5