Multi-endpoint Dose-response Modeling

Multi-Endpoint Dose-Response Modeling is a statistical modeling framework that characterizes the quantitative relationships between varying doses of a stressor and multiple distinct biological responses simultaneously, distinguishing itself from single-endpoint approaches by integrating correlated outcomes to improve inference accuracy and capture complex, system-level hormetic effects.

5

Publications

200

Citations

37

Authors

23

Institutions

Publications per year

2017–2026

1

Authors

37

  1. DH
    David Henry

    University of Newcastle Australia, Australia

    1 publications · 125 citations

    1

    h-index

  2. CY
    C Yeh

    Procter & Gamble (United States), United States

    1 publications · 125 citations

    1

    h-index

  3. KC
    Kun Chen

    University of Connecticut, United States

    1 publications · 125 citations

    1

    h-index

  4. BS
    Bruce S. Hass

    National Center for Toxicological Research, United States

    1 publications · 21 citations

    1

    h-index

  5. ZG
    Zhong-Wei Gu

    Tongji University, China

    1 publications · 19 citations

    1

    h-index

1–5 of 37

Venues

  1. Human & Experimental Toxicology

    1 publications · 21 citations

    1

    h-index

  2. The Science of The Total Environment

    1 publications · 19 citations

    1

    h-index

  3. Pharmaceutical Statistics

    1 publications · 15 citations

    1

    h-index

  4. Mutagenesis

    1 publications · 20 citations

    1

    h-index

  5. Drug Information Journal

    DIA · 1 publications · 125 citations

    1

    h-index

1–5