Simulation-based Power Analysis

Simulation-Based Power Analysis is a computational methodology within the field of statistical genetics that uses simulated data sets to evaluate the ability of a mixed-stock analysis model to correctly assign individuals to their source populations, thereby distinguishing it from analytical power assessment techniques by its reliance on iterative stochastic modeling.

167

Publications

248.4K

Citations

472

Authors

277

Institutions

Publications per year

2017–2026

58

Authors

472

  1. KE
    Keith E. Muller

    University of North Carolina at Chapel Hill, United States

    5 publications · 100.4K citations

    5

    h-index

  2. CB
    Charles Bellemare

    Université Laval, Canada

    4 publications · 115 citations

    4

    h-index

  3. LB
    Luc Bissonnette

    Université Laval, Canada

    4 publications · 115 citations

    4

    h-index

  4. RD
    Roy Dz-Ching Ju

    Intel (United States), United States

    3 publications · 123 citations

    3

    h-index

  5. GL
    Guei-Yuan Lueh

    Intel (United States), United States

    3 publications · 123 citations

    3

    h-index

1–5 of 472

Venues

  1. Statistics in Medicine

    6 publications · 221 citations

    5

    h-index

  2. 4

    h-index

  3. International Journal of Epidemiology

    4 publications · 2.4K citations

    4

    h-index

  4. BMC Bioinformatics

    4 publications · 234 citations

    4

    h-index

  5. Behavior Research Methods

    BRM · 4 publications · 64.9K citations

    4

    h-index

1–5