Bayesian Adaptive Design
Bayesian Adaptive Design is a type of clinical trial design that uses Bayesian statistical methods to sequentially modify trial procedures or hypotheses based on accumulating data, allowing for flexible decision-making while maintaining rigorous inferential validity.
251
Publications
14.9K
Citations
826
Authors
441
Institutions
Publications per year
2017–2026
106
Variants
Bayesian Adaptive Designs
Parents
251
The American Statistician · 1947 · 3.7K citations
Translation of Innovative Designs Into Phase I Trials
André Rogatko, David J. Schoeneck, William Jonas et al. · Journal of Clinical Oncology · 2007 · 220 citations · Full text
1–5 of 251
826
The University of Texas MD Anderson Cancer Center, United States
21 publications · 859 citations
19
h-index
The University of Texas MD Anderson Cancer Center, United States
23 publications · 1.6K citations
18
h-index
The University of Texas MD Anderson Cancer Center, United States
12 publications · 720 citations
12
h-index
11
h-index
9
h-index
1–5 of 826
441
The University of Texas MD Anderson Cancer Center
Houston, United States
36 h-index
134 publications
8.3K citations
Berry & Associates (United States)
Dexter, United States
16 h-index
41 publications
2K citations
University of Michigan
Ann Arbor, United States
11 h-index
17 publications
550 citations
MRC Biostatistics Unit
Cambridge, United Kingdom
10 h-index
15 publications
565 citations
Novartis (Switzerland)
Basel, Switzerland
9 h-index
21 publications
1.5K citations
Harvard University
Cambridge, United States
7 h-index
8 publications
352 citations
Dana-Farber Cancer Institute
Boston, United States
7 h-index
22 publications
1.1K citations

University of Minnesota
Minneapolis, United States
7 h-index
10 publications
415 citations
1–8 of 441
37 publications · 1.6K citations
23
h-index
18 publications · 991 citations
17
h-index
15 publications · 1.1K citations
15
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JBS · 15 publications · 455 citations
13
h-index
11 publications · 352 citations
11
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