Effect Size Planning

Effect Size Planning is a methodological framework within Bayesian sample size determination that specifies the anticipated magnitude of a phenomenon of interest to inform the selection of sample size based on desired posterior precision, statistical power, or decision-theoretic criteria.

28

Publications

9.5K

Citations

52

Authors

43

Institutions

Publications per year

2017–2026

14

Authors

52

  1. KK
    Ken Kelley

    University of Notre Dame, United States

    3 publications · 483 citations

    3

    h-index

  2. DL
    Daniël Lakens

    Eindhoven University of Technology, Netherlands

    2 publications · 1.8K citations

    2

    h-index

  3. SE
    Scott E. Maxwell

    University of Notre Dame, United States

    2 publications · 453 citations

    2

    h-index

  4. SF
    Samantha F. Anderson

    Arizona State University, United States

    2 publications · 455 citations

    2

    h-index

  5. AL
    Andrey Lovakov

    National Research University Higher School of Economics, Russia

    2 publications · 617 citations

    2

    h-index

1–5 of 52

Venues

  1. Journal of Psychiatric Research

    2 publications · 41 citations

    2

    h-index

  2. Journal of Graduate Medical Education

    1 publications · 5.5K citations

    1

    h-index

  3. American Journal of Clinical Nutrition

    AJCN · 1 publications · 34 citations

    1

    h-index

  4. Industrial and Organizational Psychology

    1 publications · 18 citations

    1

    h-index

  5. Landscape and Urban Planning

    1 publications · 21 citations

    1

    h-index

1–5