Bayesian Longitudinal Dose-response Models

Bayesian Longitudinal Dose-Response Model is a statistical framework that integrates Bayesian inference with longitudinal data structures to estimate time-varying dose-response relationships while formally quantifying uncertainty through prior distributions and iterative updating of posterior estimates.

5

Publications

112

Citations

14

Authors

10

Institutions

Publications per year

2017–2026

1

Authors

14

  1. CJ
    Craig J. Newschaffer

    Drexel University, United States

    1 publications · 15 citations

    1

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  2. GB
    Ghassan B. Hamra

    University of North Carolina at Chapel Hill, United States

    1 publications · 15 citations

    1

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  3. JW
    John Whitehead

    University of Reading, United Kingdom

    1 publications · 36 citations

    1

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  4. JF
    Jonathan French

    Pfizer (United States), United States

    1 publications · 25 citations

    1

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  5. NT
    Neal Thomas

    Pfizer (United States), United States

    1 publications · 25 citations

    1

    h-index

1–5 of 14

Venues

  1. 1

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  2. Statistics in Medicine

    1 publications · 25 citations

    1

    h-index

  3. 1

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  4. Biostatistics

    1 publications · 22 citations

    1

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  5. Drug Information Journal

    DIA · 1 publications · 36 citations

    1

    h-index

1–5