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
28
Daniël Lakens · Collabra Psychology · 2022 · 1.6K citations · Full text
Daniël Lakens · 2021 · 217 citations · Full text
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National Research University Higher School of Economics, Russia
2 publications · 617 citations
2
h-index
1–5 of 52
43

University of Notre Dame
Notre Dame, United States
4 h-index
8 publications
1.5K citations

National Research University Higher School of Economics
Moscow, Russia
2 h-index
2 publications
617 citations
Eindhoven University of Technology
Eindhoven, The Netherlands
2 h-index
2 publications
1.8K citations
University of California, Los Angeles
Los Angeles, United States
2 h-index
4 publications
626 citations
Maastricht University
Maastricht, The Netherlands
1 h-index
1 publications
31 citations

Medical University of Lublin
Lublin, Poland
1 h-index
1 publications
63 citations

North-Eastern Federal University
Yakutsk, Russia
1 h-index
1 publications
12 citations
Indiana University – Purdue University Indianapolis
Indianapolis, United States
1 h-index
1 publications
18 citations
1–8 of 43
2 publications · 41 citations
2
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1 publications · 5.5K citations
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AJCN · 1 publications · 34 citations
1
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1 publications · 18 citations
1
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1 publications · 21 citations
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