Mixed Model Methodology is a statistical modeling framework that integrates both fixed and random effects within a single model to account for multiple sources of variation in data, particularly in longitudinal or hierarchical animal studies.
497
Publications
78.2K
Citations
1.7K
Authors
704
Institutions
Publications per year
2017–2026
97
Parents
Publications
497
1–5 of 497
Authors
1.7K
- HP
10
h-index
- GV
6
h-index
- AJ
5
h-index
- MD
5
h-index
- IS
5
h-index
1–5 of 1.7K
Institutions
704
Cornell University
Ithaca, United States
10 h-index
25 publications
1.5K citations
Harvard University
Cambridge, United States
10 h-index
22 publications
704 citations
University of Hohenheim
Stuttgart, Germany
8 h-index
15 publications
1.7K citations
Brazilian Agricultural Research Corporation
Brasília, Brazil
8 h-index
18 publications
313 citations
Texas A&M University
College Station, United States
8 h-index
10 publications
1.1K citations
KU Leuven
Leuven, Belgium
7 h-index
18 publications
593 citations
Ludwig-Maximilians-Universität München
Munich, Germany
7 h-index
11 publications
1.6K citations
University of Nebraska–Lincoln
Lincoln, United States
7 h-index
10 publications
2.3K citations
1–8 of 704
Venues
- Biometrics
20 publications · 2.2K citations
17
h-index
- Journal of Animal Science
24 publications · 1.3K citations
16
h-index
- Statistics in Medicine
14 publications · 1.2K citations
14
h-index
- Journal of Dairy Science
JDS · 10 publications · 550 citations
10
h-index
- The American Statistician
9 publications · 993 citations
9
h-index
1–5