Random Effects Estimation is a statistical inference method used in mixed-effects models to quantify variability attributable to random factors in a split-plot design, distinguishing it from fixed effects by treating levels of a factor as randomly selected from a population rather than as fixed, controlled conditions.
335
Publications
33.1K
Citations
730
Authors
413
Institutions
Publications per year
2017–2026
89
Parents
Publications
335
Balancing Type I error and power in linear mixed models
Hannes Matuschek, Reinhold Kliegl, Shravan Vasishth et al. · Journal of Memory and Language · 2017 · 2K citations · Full text
Random group effects and the precision of regression estimates
Brent R. Moulton · Journal of Econometrics · 1986 · 1.7K citations
1–5 of 335
Authors
730
- DH
6
h-index
- DA
5
h-index
- SR
5
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- DJ
4
h-index
- KM
4
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1–5 of 730
Institutions
413
University of Wisconsin–Madison
Madison, United States
7 h-index
10 publications
5.3K citations
University of Illinois Chicago
Chicago, United States
6 h-index
9 publications
1K citations
University of Washington
Seattle, United States
5 h-index
15 publications
1.4K citations
University of California, Berkeley
Berkeley, United States
5 h-index
5 publications
832 citations
KU Leuven
Leuven, Belgium
5 h-index
11 publications
537 citations
Institute for Health Metrics and Evaluation
Seattle, United States
4 h-index
17 publications
1.2K citations
The Ohio State University
Columbus, United States
4 h-index
5 publications
152 citations
Case Western Reserve University
Cleveland, United States
4 h-index
4 publications
311 citations
1–8 of 413
Venues
- Biometrics
17 publications · 1.9K citations
15
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- Journal of the American Statistical Association
13 publications · 1K citations
12
h-index
- Computational Statistics & Data Analysis
CSDA · 11 publications · 357 citations
11
h-index
- Statistics in Medicine
11 publications · 1.3K citations
11
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- Communication in Statistics- Theory and Methods
10 publications · 348 citations
10
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1–5