Multilevel Latent Variable Models
Multilevel Latent Variable Models is a statistical modeling framework that extends latent variable models by incorporating hierarchically structured data through multiple levels of random effects, thereby accounting for both unobserved heterogeneity and nested data dependencies within a single integrated model.
505
Publications
55.7K
Citations
1.1K
Authors
523
Institutions
Publications per year
2017–2026
175
Parents
505
1–5 of 505
1.1K
18
h-index
13
h-index
11
h-index
Leibniz Institute for Science and Mathematics Education, Germany
9 publications · 2.4K citations
9
h-index
8
h-index
1–5 of 1.1K
523
University of California, Los Angeles
Los Angeles, United States
24 h-index
42 publications
7.2K citations

Pennsylvania State University
State College, United States
14 h-index
32 publications
2.6K citations

Tilburg University
Tilburg, The Netherlands
13 h-index
31 publications
2.4K citations

University of Tübingen
Tübingen, Germany
13 h-index
25 publications
3.2K citations
Utrecht University
Utrecht, The Netherlands
11 h-index
15 publications
1.4K citations
University of Southern California
Los Angeles, United States
10 h-index
14 publications
1.5K citations
University of Oxford
Oxford, United Kingdom
10 h-index
14 publications
3.2K citations
Michigan State University
East Lansing, United States
10 h-index
12 publications
339 citations
1–8 of 523
SEM · 35 publications · 6.2K citations
25
h-index
MBR · 18 publications · 1.6K citations
15
h-index
13 publications · 2.8K citations
13
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14 publications · 1.1K citations
13
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12 publications · 2.4K citations
12
h-index
1–5