Eigenvalue-based Factor Retention
Eigenvalue-Based Factor Retention is a dimensionality assessment method that determines the number of factors to retain in factor analysis by selecting components with eigenvalues exceeding a predetermined threshold, typically unity, to distinguish meaningful variance from noise.
53
Publications
18.3K
Citations
97
Authors
69
Institutions
Publications per year
2017–2026
7
Variants
Kaiser CriterionKaiser-guttman Rule
Parents
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University of Illinois System
Urbana, United States
3 h-index
4 publications
597 citations

Carestream (United States)
Rochester, United States
2 h-index
2 publications
467 citations
Texas A&M University
College Station, United States
2 h-index
6 publications
440 citations

Gonzaga University
Spokane, United States
2 h-index
4 publications
479 citations
Kodak (France)
Maisons-Alfort, France
2 h-index
2 publications
467 citations
University of California, Los Angeles
Los Angeles, United States
2 h-index
2 publications
85 citations
California State University, East Bay
Hayward, United States
1 h-index
1 publications
180 citations
College of New Jersey
Ewing, United States
1 h-index
2 publications
1.1K citations
1–8 of 69
4 publications · 1.2K citations
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3 publications · 1.6K citations
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MBR · 3 publications · 858 citations
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Repository · 2 publications · 938 citations
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2 publications · 768 citations
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