Nonlinear Exposure-response Models

Nonlinear Exposure-Response Models is a statistical modeling framework that characterizes the relationship between the magnitude of exposure to a substance or agent and the resulting biological or health outcome, in which the response is not proportional to the exposure level and is described by a curved or non-straight-line function.

34

Publications

3.8K

Citations

184

Authors

104

Institutions

Publications per year

2017–2026

12

Authors

184

  1. MA
    Michał Abrahamowicz

    McGill University, Canada

    2 publications · 65 citations

    2

    h-index

  2. CJ
    C.M.J. Jacobs

    Wageningen University & Research, Netherlands

    1 publications · 24 citations

    1

    h-index

  3. UK
    Ute Kraus

    Helmholtz Zentrum München, Germany

    1 publications · 118 citations

    1

    h-index

  4. MC
    M. C. B. Ellis

    Silsoe Research Institute, United Kingdom

    1 publications · 24 citations

    1

    h-index

  5. AP
    Ana P. Lacerda

    AbbVie (United States), United States

    1 publications · 22 citations

    1

    h-index

1–5 of 184

Venues

  1. American Journal of Epidemiology

    AJE · 4 publications · 1.5K citations

    4

    h-index

  2. Statistics in Medicine

    2 publications · 865 citations

    2

    h-index

  3. Environmental Science & Technology

    2 publications · 450 citations

    2

    h-index

  4. CPT Pharmacometrics & Systems Pharmacology

    PSP · 1 publications · 10 citations

    1

    h-index

  5. Inhalation Toxicology

    1 publications · 55 citations

    1

    h-index

1–5