Bayesian Sample Size Determination

Bayesian Sample Size Determination is a statistical methodology that belongs to the class of sample size determination techniques, distinguished by its incorporation of prior information and probabilistic inference under a Bayesian framework to ascertain the minimum sample size required for achieving prespecified levels of posterior precision, power, or decision-theoretic utility in parameter estimation or hypothesis testing.

112

Publications

4.4K

Citations

194

Authors

129

Institutions

Publications per year

2017–2026

12

Authors

194

  1. LJ
    Lawrence Joseph

    McGill University, Canada

    10 publications · 757 citations

    10

    h-index

  2. FD
    Fulvio De Santis

    Sapienza University of Rome, Italy

    9 publications · 296 citations

    9

    h-index

  3. JD
    James D. Stamey

    Baylor University, United States

    7 publications · 94 citations

    7

    h-index

  4. DB
    David B. Wolfson

    McGill University, Canada

    5 publications · 332 citations

    5

    h-index

  5. SG
    Stefania Gubbiotti

    Sapienza University of Rome, Italy

    4 publications · 138 citations

    4

    h-index

1–5 of 194

Venues

  1. Statistics in Medicine

    20 publications · 1K citations

    16

    h-index

  2. 10

    h-index

  3. Biometrics

    7 publications · 432 citations

    7

    h-index

  4. 4

    h-index

  5. Clinical Trials

    4 publications · 197 citations

    4

    h-index

1–5