Bayesian Multilevel Inference
Bayesian Multilevel Inference is a statistical inference framework that belongs to the class of hierarchical modeling methods, distinguished by its incorporation of prior distributions at multiple levels of a parameter hierarchy to enable coherent uncertainty quantification and information sharing across groups.
326
Publications
30K
Citations
1.3K
Authors
554
Institutions
Publications per year
2017–2026
206
Parents
326
Multilevel linear modelling for FMRI group analysis using Bayesian inference
Mark W. Woolrich, Timothy E.J. Behrens, Christian F. Beckmann et al. · NeuroImage · 2004 · 1.8K citations
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Harvard University
Cambridge, United States
9 h-index
17 publications
3.5K citations
Columbia University
New York, United States
9 h-index
15 publications
2.8K citations

University of Coimbra
Coimbra, Portugal
8 h-index
11 publications
255 citations

Imperial College London
London, United Kingdom
8 h-index
14 publications
1.1K citations
Universidade Federal de Santa Catarina
Florianópolis, Brazil
7 h-index
20 publications
555 citations
University of Münster
Münster, Germany
7 h-index
11 publications
9.7K citations
Universidade de São Paulo
São Paulo, Brazil
7 h-index
26 publications
995 citations
University of Bern
Bern, Switzerland
7 h-index
14 publications
380 citations
1–8 of 554
11 publications · 355 citations
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Repository · 6 publications · 147 citations
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4 publications · 91 citations
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SEM · 5 publications · 252 citations
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5 publications · 238 citations
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