Generalizability Models
Generalizability Models is a class of statistical frameworks that extend generalizability theory by quantifying the dependability of measurements across diverse facets of observation, distinguishing itself through the explicit modeling of variance components associated with admissible observational universes to assess the robustness of inferences under varying conditions.
340
Publications
30.6K
Citations
1.4K
Authors
494
Institutions
Publications per year
2017–2026
122
340
1–5 of 340
1.4K
California State University, Fullerton, United States
8 publications · 252 citations
8
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7
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5
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4
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4
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1–5 of 1.4K
494
University of Iowa
Iowa City, United States
8 h-index
17 publications
1.2K citations
University of Illinois Urbana-Champaign
Urbana, United States
7 h-index
12 publications
2.6K citations

University of Calgary
Calgary, Canada
7 h-index
17 publications
652 citations

California State University, Fullerton
Fullerton, United States
6 h-index
7 publications
231 citations
University of California, Los Angeles
Los Angeles, United States
6 h-index
10 publications
1.6K citations
National Board of Medical Examiners
Philadelphia, United States
6 h-index
8 publications
216 citations
Virginia Commonwealth University
Richmond, United States
5 h-index
10 publications
1.8K citations
University of Oxford
Oxford, United Kingdom
5 h-index
10 publications
3.9K citations
1–8 of 494
9 publications · 333 citations
9
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8 publications · 235 citations
8
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Repository · 8 publications · 208 citations
8
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7 publications · 204 citations
7
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Repository · 7 publications · 308 citations
7
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