Multilevel Ordinal Models is a statistical modeling framework that extends ordinal regression by incorporating hierarchical data structures through random effects to account for dependencies among observations within clusters while maintaining the proportional odds assumption across ordered outcome categories.
82
Publications
4.4K
Citations
267
Authors
164
Institutions
Publications per year
2017–2026
20
Parents
Publications
82
1–5 of 82
Authors
267
- LG
5
h-index
- CR
4
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- MI
4
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4
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2
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1–5 of 267
Institutions
164
University of Naples Federico II
Naples, Italy
4 h-index
5 publications
205 citations
University of Florence
Florence, Italy
4 h-index
8 publications
238 citations
University of Illinois Chicago
Chicago, United States
3 h-index
3 publications
488 citations
Harvard University
Cambridge, United States
3 h-index
3 publications
120 citations
University of Colorado Denver
Denver, United States
2 h-index
5 publications
68 citations
Brown University
Providence, United States
2 h-index
2 publications
131 citations
University of Florida
Gainesville, United States
2 h-index
3 publications
63 citations
University of Kansas
Lawrence, United States
2 h-index
6 publications
1.3K citations
1–8 of 164
Venues
- Computational Statistics & Data Analysis
CSDA · 4 publications · 105 citations
4
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- Statistical Modelling
3 publications · 86 citations
3
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- PLoS ONE
3 publications · 163 citations
3
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- Structural Equation Modeling A Multidisciplinary Journal
SEM · 3 publications · 161 citations
3
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- Quality & Quantity
2 publications · 202 citations
2
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