Mixed Model Diagnostics
Mixed Model Diagnostics is a statistical methodology used to assess the validity, assumptions, and performance of mixed effects models by identifying influential observations, detecting model misspecification, and evaluating the fit of both fixed and random effects structures.
35
Publications
2.8K
Citations
76
Authors
54
Institutions
Publications per year
2017–2026
5
Parents
35
1–5 of 35
76
3
h-index
3
h-index
Universidade Federal de São Paulo, Brazil
2 publications · 56 citations
2
h-index
2
h-index
2
h-index
1–5 of 76
54
KU Leuven
Leuven, Belgium
3 h-index
10 publications
245 citations

Hasselt University
Hasselt, Belgium
3 h-index
9 publications
210 citations
Universidade de São Paulo
São Paulo, Brazil
3 h-index
5 publications
176 citations
Yale University
New Haven, United States
2 h-index
2 publications
100 citations

Uppsala University
Uppsala, Sweden
2 h-index
7 publications
5.7K citations
University of Delaware
Newark, United States
2 h-index
2 publications
38 citations
Los Alamos National Laboratory
Los Alamos, United States
2 h-index
2 publications
206 citations

Universidade Federal de São Paulo
São Paulo, Brazil
2 h-index
2 publications
56 citations
1–8 of 54
6 publications · 467 citations
6
h-index
CSDA · 2 publications · 79 citations
2
h-index
2 publications · 90 citations
2
h-index
2 publications · 100 citations
2
h-index
JCGS · 1 publications · 32 citations
1
h-index
1–5