Mixed-effects Model Development
Mixed-Effects Model Development is a methodological contribution in statistical modeling that integrates both fixed and random effects to account for population-level and group-level variations in data, distinguishing itself by enabling inference on hierarchical or longitudinal structures while preserving efficiency and interpretability.
88
Publications
6.5K
Citations
323
Authors
172
Institutions
Publications per year
2017–2026
29
Parents
88
Weight loss in Huntington disease increases with higher CAG repeat number
N. Ahmad Aziz, J.M.M. van der Burg, G. Bernhard Landwehrmeyer et al. · Neurology · 2008 · 259 citations
Life Sciences, Genetics, Neurology +17
1–5 of 88
323
Institute of Forest Resource Information Techniques, China
2 publications · 81 citations
2
h-index
University of North Carolina at Chapel Hill, United States
2 publications · 283 citations
2
h-index
2
h-index
University of North Carolina at Chapel Hill, United States
2 publications · 283 citations
2
h-index
2
h-index
1–5 of 323
172
University of South Carolina
Columbia, United States
3 h-index
6 publications
898 citations
State Forestry and Grassland Administration
Beijing, China
3 h-index
6 publications
207 citations
Erasmus MC
Rotterdam, The Netherlands
2 h-index
7 publications
197 citations

Washington University in St. Louis
St Louis, United States
2 h-index
2 publications
568 citations

Novo Nordisk (Denmark)
Copenhagen, Denmark
2 h-index
6 publications
264 citations
University of Michigan
Ann Arbor, United States
2 h-index
3 publications
104 citations

Johns Hopkins University
Baltimore, United States
2 h-index
8 publications
112 citations

Imperial College London
London, United Kingdom
2 h-index
7 publications
333 citations
1–8 of 172
3 publications · 80 citations
3
h-index
3 publications · 142 citations
3
h-index
2 publications · 324 citations
2
h-index
AMPPS · 2 publications · 707 citations
2
h-index
2 publications · 123 citations
2
h-index
1–5