Bayesian Response-adaptive Randomization
Bayesian Response-Adaptive Randomization is a clinical trial design methodology that dynamically allocates patients to treatment arms based on accumulating efficacy and safety data, using Bayesian statistical models to update probability assignments and optimize allocation toward more promising interventions while maintaining randomization.
39
Publications
2.1K
Citations
373
Authors
197
Institutions
Publications per year
2017–2026
20
Parents
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Brett L. Houston, Patrick R. Lawler, Ewan C. Goligher et al. · Clinical Trials · 2020 · 68 citations · Full text
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The University of Texas MD Anderson Cancer Center, United States
3 publications · 882 citations
3
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1–5 of 373
197
Dana-Farber Cancer Institute
Boston, United States
9 h-index
89 publications
2.5K citations
Berry & Associates (United States)
Dexter, United States
7 h-index
12 publications
2K citations
The University of Texas MD Anderson Cancer Center
Houston, United States
6 h-index
27 publications
974 citations
Harvard University
Cambridge, United States
6 h-index
53 publications
914 citations

Sorbonne Université
Paris, France
4 h-index
84 publications
3.7K citations
University of Virginia
Charlottesville, United States
4 h-index
7 publications
226 citations

Brigham and Women's Hospital
Boston, United States
4 h-index
66 publications
1.7K citations

University of Alabama at Birmingham
Birmingham, United States
3 h-index
31 publications
359 citations
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4 publications · 193 citations
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4 publications · 201 citations
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3 publications · 85 citations
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JBS · 2 publications · 28 citations
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2 publications · 75 citations
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