Bayesian Model Selection
Bayesian Model Selection is a statistical framework within Bayesian inference that uses posterior model probabilities, derived from prior probabilities and marginal likelihoods, to compare and select among competing models based on their joint fit to observed data and modeling assumptions.
1.3K
Publications
206.5K
Citations
3.1K
Authors
1.4K
Institutions
Publications per year
2017–2026
358
1.3K
Kenneth P. Burnham, David R. Anderson · Sociological Methods & Research · 2004 · 11.6K citations
Testing Structural Equation Models.
Clifford C. Clogg, Kenneth A. Bollen, J. Scott Long · Social Forces · 1995 · 8.3K citations
Bayesian Model Selection in Social Research
Adrian E. Raftery · Sociological Methodology · 1995 · 6.9K citations
Computing, Biostatistics, Sociology +17
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University College London
London, United Kingdom
37 h-index
135 publications
24.4K citations
Wellcome Centre for Human Neuroimaging
London, United Kingdom
21 h-index
61 publications
18.8K citations

Imperial College London
London, United Kingdom
19 h-index
49 publications
13.2K citations
University of Cambridge
Cambridge, United Kingdom
19 h-index
53 publications
3.8K citations
Duke University
Durham, United States
18 h-index
34 publications
2.3K citations

Centre National de la Recherche Scientifique
Paris, France
18 h-index
55 publications
3.5K citations
University of Zurich
Zurich, Switzerland
17 h-index
31 publications
4.9K citations
Utrecht University
Utrecht, The Netherlands
17 h-index
62 publications
4.1K citations
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43 publications · 10.1K citations
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28 publications · 1.8K citations
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PRD · 21 publications · 1.2K citations
19
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18 publications · 3.5K citations
17
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19 publications · 977 citations
17
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