Simulation-based Sample Size Determination

Simulation-Based Sample Size Determination is a method within Bayesian sample size determination that uses repeated stochastic simulations to evaluate the operating characteristics of a proposed study design, thereby distinguishing itself from analytical or rule-of-thumb approaches by empirically estimating the sample size required to achieve prespecified inferential goals under uncertainty.

382

Publications

59.3K

Citations

836

Authors

478

Institutions

Publications per year

2017–2026

77

Authors

836

  1. GS
    Gwowen Shieh

    National Yang Ming Chiao Tung University, Taiwan

    10 publications · 619 citations

    10

    h-index

  2. SJ
    Sin‐Ho Jung

    Duke University, United States

    6 publications · 192 citations

    6

    h-index

  3. CA
    Chul Ahn

    The University of Texas Southwestern Medical Center, United States

    5 publications · 181 citations

    5

    h-index

  4. TF
    Tim Friede

    Universitätsmedizin Göttingen, Germany

    5 publications · 101 citations

    5

    h-index

  5. LJ
    Lawrence Joseph

    McGill University, Canada

    4 publications · 201 citations

    4

    h-index

1–5 of 836

Venues

  1. Statistics in Medicine

    46 publications · 3.7K citations

    27

    h-index

  2. Biometrics

    12 publications · 853 citations

    11

    h-index

  3. Journal of Biopharmaceutical Statistics

    JBS · 15 publications · 260 citations

    11

    h-index

  4. BMC Medical Research Methodology

    9 publications · 21.1K citations

    9

    h-index

  5. Behavior Research Methods

    BRM · 8 publications · 2.1K citations

    8

    h-index

1–5