Crossed Random Effects Models is a type of mixed effects model in which the random effects are associated with multiple grouping factors that are not nested but instead cross each other, allowing for the simultaneous modeling of dependencies arising from distinct, independently varying sources of variability.
82
Publications
13.9K
Citations
213
Authors
113
Institutions
Publications per year
2017–2026
27
Variants
Crossed-random Effects Models
Parents
Publications
82
1–5 of 82
Authors
213
- RH
3
h-index
- JT
3
h-index
- DL
3
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- RZ
3
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- MF
3
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1–5 of 213
Institutions
113
Vanderbilt University
Nashville, United States
4 h-index
6 publications
250 citations
University of Zielona Góra
Zielona Góra, Poland
3 h-index
3 publications
50 citations
University of California, Berkeley
Berkeley, United States
3 h-index
3 publications
104 citations
Max Planck Institute for Psycholinguistics
Nijmegen, The Netherlands
3 h-index
3 publications
8.6K citations
KU Leuven
Leuven, Belgium
3 h-index
7 publications
201 citations
University of Lisbon
Lisbon, Portugal
3 h-index
5 publications
88 citations
University of Hull
Hull, United Kingdom
2 h-index
2 publications
45 citations
Middle Tennessee State University
Murfreesboro, United States
2 h-index
2 publications
58 citations
1–8 of 113
Venues
- British Journal of Mathematical and Statistical Psychology
5 publications · 151 citations
5
h-index
- Biometrics
3 publications · 123 citations
3
h-index
- Multivariate Behavioral Research
MBR · 3 publications · 331 citations
3
h-index
- Psychometrika
2 publications · 80 citations
2
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- The Annals of Statistics
2 publications · 35 citations
2
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1–5