Hierarchical Bayesian Design
Hierarchical Bayesian Design is a Bayesian adaptive design framework that incorporates multiple levels of uncertainty by structuring prior distributions hierarchically to model dependencies across parameters, thereby enabling information borrowing across subgroups or stages in a principled manner.
90
Publications
7.7K
Citations
474
Authors
280
Institutions
Publications per year
2017–2026
35
Parents
90
Checking consistency in mixed treatment comparison meta‐analysis
Sofia Dias, Nicky J. Welton, Deborah M Caldwell et al. · Statistics in Medicine · 2010 · 2.5K citations
The Effect of Banner Advertising on Internet Purchasing
Puneet Manchanda, Jean-Pierre Dubé, Khim Yong Goh et al. · Journal of Marketing Research · 2006 · 466 citations
1–5 of 90
474
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280
University of Pennsylvania
Philadelphia, United States
6 h-index
7 publications
1.1K citations
United States Geological Survey
Reston, United States
4 h-index
13 publications
520 citations
University of Michigan
Ann Arbor, United States
4 h-index
10 publications
1.8K citations
University of Chicago
Chicago, United States
4 h-index
8 publications
1.1K citations

Pennsylvania State University
State College, United States
4 h-index
4 publications
685 citations
University of California, Irvine
Irvine, United States
3 h-index
17 publications
338 citations

The University of Western Australia
Perth, Australia
3 h-index
3 publications
96 citations
University of Florida
Gainesville, United States
3 h-index
7 publications
712 citations
1–8 of 280
5 publications · 259 citations
5
h-index
5 publications · 2.8K citations
5
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3 publications · 173 citations
3
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3 publications · 451 citations
3
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3 publications · 808 citations
3
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1–5