Bayesian Linear Mixed Models
Bayesian Linear Mixed Models is a statistical modeling framework within the class of linear mixed models that incorporates Bayesian inference to estimate fixed and random effects by specifying prior distributions on model parameters and updating them to posterior distributions through the application of Bayes' theorem.
138
Publications
9.4K
Citations
717
Authors
380
Institutions
Publications per year
2017–2026
74
Variants
Bayesian Hierarchical Linear ModelsBayesian Multilevel Models
Parents
138
Polygenic Modeling with Bayesian Sparse Linear Mixed Models
Xiang Zhou, Peter Carbonetto, Matthew Stephens · PLoS Genetics · 2013 · 936 citations · Full text
Model Selection in Linear Mixed Models
Samuel Müller, Janice L. Scealy, A. H. Welsh · Statistical Science · 2013 · 339 citations · Full text
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380
University College London
London, United Kingdom
8 h-index
13 publications
5K citations
University of Wisconsin–Madison
Madison, United States
8 h-index
19 publications
1.1K citations
University of Potsdam
Potsdam, Germany
6 h-index
11 publications
739 citations

Vanderbilt University
Nashville, United States
5 h-index
6 publications
328 citations
KU Leuven
Leuven, Belgium
5 h-index
14 publications
553 citations

Tilburg University
Tilburg, The Netherlands
4 h-index
5 publications
164 citations
University of Chicago
Chicago, United States
4 h-index
12 publications
3.8K citations

The University of Melbourne
Melbourne, Australia
4 h-index
13 publications
188 citations
1–8 of 380
CSDA · 7 publications · 317 citations
7
h-index
6 publications · 299 citations
6
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5 publications · 111 citations
5
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5 publications · 223 citations
5
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GSE · 3 publications · 268 citations
3
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1–5