Random Effects Modeling is a statistical modeling approach in population pharmacokinetics that represents inter-individual and other hierarchical sources of variability by specifying probability distributions for subject-specific parameters within a mixed-effects framework, thereby distinguishing random variability from fixed (typical) population effects.
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3K
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1.2K
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Publications per year
2017–2026
264
Variants
Random Effects ModelRandom-effects Modeling
Parents
Publications
1.5K
nlme : Linear and nonlinear mixed effects models
Saikat DebRoy · Medical Entomology and Zoology · 2006 · 10.2K citations
Mixed-Effects Models in S and S-PLUS
Technometrics · 2001 · 9.4K citations · Full text
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- DH
23
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- GV
17
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- EL
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- GM
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- FM
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Institutions
1.2K
Harvard University
Cambridge, United States
26 h-index
73 publications
14.6K citations
KU Leuven
Leuven, Belgium
25 h-index
85 publications
5.5K citations
MRC Biostatistics Unit
Cambridge, United Kingdom
24 h-index
48 publications
5.4K citations
University of Illinois Chicago
Chicago, United States
23 h-index
59 publications
5.8K citations
University of Washington
Seattle, United States
22 h-index
50 publications
5.8K citations
University of Michigan
Ann Arbor, United States
21 h-index
47 publications
4.9K citations
University of Wisconsin–Madison
Madison, United States
19 h-index
38 publications
17.4K citations
Inserm
Paris, France
18 h-index
46 publications
3.3K citations
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Venues
- Biometrics
133 publications · 14.4K citations
58
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- Statistics in Medicine
184 publications · 12.3K citations
53
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- Journal of the American Statistical Association
85 publications · 13.7K citations
46
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- Biometrika
35 publications · 8.9K citations
27
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- Computational Statistics & Data Analysis
CSDA · 36 publications · 1.6K citations
21
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