Covariance Structure Modeling is a statistical framework within mixed model analysis that specifies and estimates the pattern of variances and covariances among random effects and residuals to accurately represent the hierarchical or correlated structure of observed data.
1K
Publications
265.2K
Citations
2K
Authors
908
Institutions
Publications per year
2017–2026
133
Parents
Publications
1K
1–5 of 1K
Authors
2K
- PMPeter M. Bentler
University of California, Los Angeles, United States
33 publications · 146.1K citations
26
h-index
- RC
16
h-index
- KY
15
h-index
- TR
14
h-index
- MW
9
h-index
1–5 of 2K
Institutions
908
University of California, Los Angeles
Los Angeles, United States
27 h-index
48 publications
125.4K citations
University of Illinois Urbana-Champaign
Urbana, United States
19 h-index
48 publications
5.2K citations
University of Michigan
Ann Arbor, United States
17 h-index
32 publications
4.6K citations
The Ohio State University
Columbus, United States
16 h-index
25 publications
9.2K citations
University of Amsterdam
Amsterdam, The Netherlands
15 h-index
24 publications
5.2K citations
Arizona State University
Tempe, United States
15 h-index
21 publications
2.6K citations
Harvard University
Cambridge, United States
14 h-index
38 publications
3.1K citations
University of Chicago
Chicago, United States
13 h-index
15 publications
1.5K citations
1–8 of 908
Venues
- Multivariate Behavioral Research
MBR · 50 publications · 6.1K citations
30
h-index
- Structural Equation Modeling A Multidisciplinary Journal
SEM · 44 publications · 108.9K citations
29
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- Psychological Bulletin
21 publications · 29.8K citations
21
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- Psychometrika
22 publications · 2.3K citations
20
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- Journal of the American Statistical Association
26 publications · 2.6K citations
20
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