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Factor Analysis and AIC
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“The Akaike Information Criterion (AIC; Akaike, 1987) was used for the purposes of model comparison, with the smallest value being indicative of the most parsimonious model (Byrne, 2012).”
From Examining Potential Psychological Protective and Risk Factors for Stress and Burnout in Social Workers. (2025) · cites this paper as Akaike, 1987
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Metadata
- Authors
- Akaike, H.
- Affiliations
- The Institute of Statistical Mathematics (JP)
- Corresponding author
- Akaike, Hirotugu
- Venue
- Springer Series in Statistics
- Publisher
- Springer New York
- Published
- 1987
- Pages
- 371-386
- ISSN
- 0172-7397 (ISSN-L)
- OpenAlex
- W2078977693
- Cited by
- 4,027
- References
- 24
- Citations by year
- 2026: 8 · 2025: 14 · 2024: 19 · 2023: 51 · 2022: 62 · 2021: 191 · 2020: 214 · 2019: 227 · 2018: 188 · 2017: 203 · 2016: 200 · 2015: 241 · 2014: 248 · 2013: 233 · 2012: 213
- FWCI
- 43.81
- Type
- book chapter
- Language
- en
- Open access
- closed
- Licence
- Locations
- Springer series in statistics (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Keywords
- factor analysis, number of factors, Bayesian model selection, improper solutions, prior distributions, factor loadings, maximum likelihood estimation, autoregressive model order selection
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