Bayesian Group Sequential Design

Bayesian Group Sequential Design is a statistical methodology for clinical trials that belongs to the class of group sequential designs and is distinguished by its incorporation of Bayesian inference to evaluate accumulating data at predefined interim analyses, allowing for adaptive decision-making regarding trial continuation, early stopping for efficacy or futility, and parameter estimation using prior and posterior probability distributions.

39

Publications

2.8K

Citations

160

Authors

86

Institutions

Publications per year

2017–2026

11

Authors

160

  1. DA
    Donald A. Berry

    The University of Texas MD Anderson Cancer Center, United States

    4 publications · 196 citations

    4

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  2. RL
    Roger Lewis

    UCLA Medical Center, United States

    3 publications · 164 citations

    3

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  3. BP
    Brian P. Hobbs

    The University of Texas MD Anderson Cancer Center, United States

    2 publications · 298 citations

    2

    h-index

  4. SH
    Steven H. Lin

    The University of Texas MD Anderson Cancer Center, United States

    2 publications · 298 citations

    2

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  5. YY
    Ying Yuan

    The University of Texas MD Anderson Cancer Center, United States

    2 publications · 131 citations

    2

    h-index

1–5 of 160

Venues

  1. Statistics in Medicine

    7 publications · 550 citations

    7

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  2. 3

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  3. Statistical Methods in Medical Research

    2 publications · 29 citations

    2

    h-index

  4. 2

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  5. Controlled Clinical Trials

    2 publications · 149 citations

    2

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1–5