Mixed-effects Logistic Regression
Mixed-Effects Logistic Regression is a statistical model within the class of generalized linear mixed models that extends standard logistic regression by incorporating both fixed and random effects to account for hierarchical or clustered data structures in binary response variables.
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Publications per year
2017–2026
665
Variants
Multilevel Logistic Regression
1K
A mixed‐effects multinomial logistic regression model
Donald Hedeker · Statistics in Medicine · 2003 · 372 citations
Business, Psychiatry, Homelessness +16
Negative Patient Descriptors: Documenting Racial Bias In The Electronic Health Record
Michael Sun, Tomasz Oliwa, Monica E. Peek et al. · Health Affairs · 2022 · 315 citations · Full text
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Harvard University
Cambridge, United States
20 h-index
92 publications
5.6K citations
University of California, San Francisco
San Francisco, United States
20 h-index
85 publications
5.5K citations
University of Gondar
Gonder, Ethiopia
20 h-index
110 publications
3.6K citations
Inserm
Paris, France
19 h-index
139 publications
4.2K citations
University College London
London, United Kingdom
19 h-index
94 publications
2.9K citations

Johns Hopkins University
Baltimore, United States
18 h-index
105 publications
3.8K citations
University of Washington
Seattle, United States
17 h-index
69 publications
6.2K citations
University of Pennsylvania
Philadelphia, United States
17 h-index
64 publications
2.1K citations
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41 publications · 1.8K citations
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25 publications · 808 citations
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11 publications · 315 citations
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11 publications · 325 citations
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9 publications · 261 citations
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