Logistic Regression Model Averaging

Logistic Regression Model Averaging is a Bayesian model averaging framework that combines multiple logistic regression models by weighting their posterior probabilities to improve predictive accuracy and account for model uncertainty in binary or categorical outcome settings.

14

Publications

1.7K

Citations

47

Authors

28

Institutions

Publications per year

2017–2026

1

Authors

47

  1. VV
    Valérie Viallefont

    Inserm, France

    2 publications · 288 citations

    2

    h-index

  2. SR
    Sylvia Richardson

    Imperial College London, United Kingdom

    2 publications · 288 citations

    2

    h-index

  3. AT
    Alan T. K. Wan

    City University of Hong Kong, Hong Kong SAR China

    2 publications · 80 citations

    2

    h-index

  4. AE
    Adrian E. Raftery

    University of Washington, United States

    2 publications · 288 citations

    2

    h-index

  5. SF
    Silvia Figini

    University of Pavia, Italy

    1 publications · 14 citations

    1

    h-index

1–5 of 47

Venues

  1. Statistics in Medicine

    3 publications · 424 citations

    3

    h-index

  2. Journal of Multivariate Analysis

    1 publications · 14 citations

    1

    h-index

  3. Epidemiologic Perspectives & Innovations

    1 publications · 12 citations

    1

    h-index

  4. 1

    h-index

  5. British Journal of Audiology

    1 publications · 29 citations

    1

    h-index

1–5