Hierarchical Bayesian Meta-analysis
Hierarchical Bayesian Meta-Analysis is a Bayesian meta-analytic model that belongs to the class of hierarchical models by structuring parameters in multiple levels to account for between-study heterogeneity and within-study variability, while distinguishing itself through the incorporation of prior distributions and joint probabilistic modeling of effect sizes and hyperparameters across studies.
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9.5K
Citations
1.3K
Authors
250
Institutions
Publications per year
2017–2026
55
Parents
105
Bin Zhou, A. Rayner, Edward W. Gregg et al. · The Lancet · 2024 · 793 citations · Full text
Jelena Savović, Rebecca Turner, David Mawdsley et al. · American Journal of Epidemiology · 2017 · 394 citations · Full text
Meta‐analysis of continuous outcome data from individual patients
Julian P. T. Higgins, Anne Whitehead, Rebecca Turner et al. · Statistics in Medicine · 2001 · 270 citations
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University of Minnesota
Minneapolis, United States
6 h-index
19 publications
438 citations
Korea University
Seoul, South Korea
5 h-index
8 publications
202 citations
University College London
London, United Kingdom
5 h-index
11 publications
635 citations

University of Bristol
Bristol, United Kingdom
5 h-index
16 publications
7.7K citations

University of Leicester
Leicester, United Kingdom
5 h-index
10 publications
542 citations
University of Washington
Seattle, United States
4 h-index
7 publications
253 citations
University of Pennsylvania
Philadelphia, United States
4 h-index
10 publications
748 citations
RWTH Aachen University
Aachen, Germany
3 h-index
12 publications
411 citations
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9 publications · 3K citations
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5 publications · 957 citations
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4 publications · 154 citations
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4 publications · 201 citations
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3 publications · 105 citations
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