Dose-response Model Selection

Dose-Response Model Selection is the statistical methodology determining the most appropriate functional form that characterizes the relationship between the magnitude of an exposure (dose) and the resulting biological or toxicological effect (response) based on empirical data, distinguished from general model selection by its focus on biologically plausible, dose-dependent response patterns.

56

Publications

3.8K

Citations

189

Authors

97

Institutions

Publications per year

2017–2026

8

Authors

189

  1. EJ
    Edward J. Calabrese

    University of Massachusetts Amherst, United States

    4 publications · 66 citations

    4

    h-index

  2. MT
    Masahiro Tajiri

    Kitasato University, Japan

    2 publications · 165 citations

    2

    h-index

  3. WM
    Wolfgang Mueck

    Bayer (Germany), Germany

    2 publications · 165 citations

    2

    h-index

  4. KZ
    Kathryn Z. Guyton

    Centre international de recherche sur le cancer, France

    2 publications · 158 citations

    2

    h-index

  5. TT
    Takahiko Tanigawa

    Bayer (Japan), Japan

    2 publications · 165 citations

    2

    h-index

1–5 of 189

Venues

  1. Risk Analysis

    4 publications · 285 citations

    4

    h-index

  2. Biometrics

    3 publications · 101 citations

    3

    h-index

  3. Regulatory Toxicology and Pharmacology

    RTP · 3 publications · 88 citations

    3

    h-index

  4. 3

    h-index

  5. Statistics in Medicine

    3 publications · 153 citations

    3

    h-index

1–5