Variance-based Sample Size

Variance-Based Sample Size is a sample size determination method in Bayesian statistics that specifies the minimum number of observations required to achieve a desired level of precision by explicitly accounting for the variance of the posterior distribution.

31

Publications

2.1K

Citations

56

Authors

40

Institutions

Publications per year

2017–2026

3

Authors

56

  1. RJ
    Randall J. LeVeque

    University of Washington, United States

    2 publications · 423 citations

    2

    h-index

  2. GH
    Gene H. Golub

    Stanford University, United States

    2 publications · 423 citations

    2

    h-index

  3. TF
    Tony F. Chan

    University of California, Los Angeles, United States

    2 publications · 423 citations

    2

    h-index

  4. PI
    Phillip I. Good

    W.E. Upjohn Institute for Employment Research, United States

    1 publications · 67 citations

    1

    h-index

  5. AC
    Ajit C. Tamhane

    Northwestern University, United States

    1 publications · 10 citations

    1

    h-index

1–5 of 56

Venues

  1. The American Statistician

    4 publications · 487 citations

    4

    h-index

  2. Journal of Statistical Planning and Inference

    3 publications · 87 citations

    3

    h-index

  3. Statistics in Medicine

    3 publications · 121 citations

    3

    h-index

  4. PubMed

    Repository · 2 publications · 44 citations

    2

    h-index

  5. Measurement in Physical Education and Exercise Science

    MPEES · 1 publications · 47 citations

    1

    h-index

1–5