Simulation-based Sample Size Determination
Simulation-Based Sample Size Determination is a method within Bayesian sample size determination that uses repeated stochastic simulations to evaluate the operating characteristics of a proposed study design, thereby distinguishing itself from analytical or rule-of-thumb approaches by empirically estimating the sample size required to achieve prespecified inferential goals under uncertainty.
382
Publications
59.3K
Citations
836
Authors
478
Institutions
Publications per year
2017–2026
77
382
1–5 of 382
836
10
h-index
6
h-index
The University of Texas Southwestern Medical Center, United States
5 publications · 181 citations
5
h-index
5
h-index
4
h-index
1–5 of 836
478

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
11 h-index
12 publications
647 citations
Utrecht University
Utrecht, The Netherlands
8 h-index
11 publications
1.4K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
6 h-index
9 publications
401 citations
Inserm
Paris, France
6 h-index
11 publications
292 citations
University of Florida
Gainesville, United States
6 h-index
6 publications
200 citations

Imperial College London
London, United Kingdom
5 h-index
14 publications
1.8K citations
Albert Einstein College of Medicine
Bronx, United States
5 h-index
12 publications
563 citations
Yale University
New Haven, United States
5 h-index
9 publications
833 citations
1–8 of 478
46 publications · 3.7K citations
27
h-index
12 publications · 853 citations
11
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JBS · 15 publications · 260 citations
11
h-index
9 publications · 21.1K citations
9
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BRM · 8 publications · 2.1K citations
8
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1–5