Random Effects Selection
Random Effects Selection is a model selection procedure that identifies the appropriate set of random effects in a mixed-effects model by distinguishing between fixed and random sources of variability across groups or clusters in hierarchical data structures.
123
Publications
7K
Citations
298
Authors
177
Institutions
Publications per year
2017–2026
19
Parents
123
Experimental Vignette Studies in Survey Research
Christiane Atzmüller, Peter M. Steiner · Methodology · 2010 · 958 citations
Random Effects Selection in Linear Mixed Models
Zhen Chen, David B. Dunson · Biometrics · 2003 · 240 citations
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177

University of Waikato
Hamilton, New Zealand
4 h-index
4 publications
670 citations
North Carolina State University
Raleigh, United States
4 h-index
10 publications
226 citations
Motu Economic and Public Policy Research
Wellington, New Zealand
4 h-index
4 publications
670 citations
University of Nebraska–Lincoln
Lincoln, United States
4 h-index
13 publications
719 citations
University of Cambridge
Cambridge, United Kingdom
3 h-index
3 publications
500 citations

University of Georgia
Athens, United States
3 h-index
5 publications
203 citations
University of California, Davis
Davis, United States
3 h-index
6 publications
123 citations
University of Southern California
Los Angeles, United States
2 h-index
4 publications
196 citations
1–8 of 177
9 publications · 441 citations
9
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Repository · 5 publications · 80 citations
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4 publications · 592 citations
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3 publications · 81 citations
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2 publications · 245 citations
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