The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Choosing the Optimal Number of Factors in Exploratory Factor Analysis: A Model Selection Perspective
Abstract
A central problem in the application of exploratory factor analysis is deciding how many factors to retain (m). Although this is inherently a model selection problem, a model selection perspective is rarely adopted for this task. We suggest that Cudeck and Henly's (1991) framework can be applied to guide the selection process. Researchers must first identify the analytic goal: identifying the (approximately) correct m or identifying the most replicable m. Second, researchers must choose fit indices that are most congruent with their goal. Consistent with theory, a simulation study showed that different fit indices are best suited to different goals. Moreover, model selection with one goal in mind (e.g., identifying the approximately correct m) will not necessarily lead to the same number of factors as model selection with the other goal in mind (e.g., identifying the most replicable m). We recommend that researchers more thoroughly consider what they mean by "the right number of factors" before they choose fit indices.
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Cites
Alternative Ways of Assessing Model Fit
Browne, M. W., & Cudeck, R. (1992) · Sociological Methods & Research · doi:10.1177/0049124192021002005 · Cited by 27,200
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Akaike, H. (1987) · Springer Series in Statistics · doi:10.1007/978-1-4612-1694-0_29 · Cited by 4,027
Normal personality assessment in clinical practice: the NEO personality inventory
Costa, P. T., & McCrae, R. R. (1992) · Psychological Assessment · doi:10.1037/1040-3590.4.1.5 · Cited by 3,414
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Metadata
- Authors
- Preacher, K. J., Zhang, G., Kim, C., & Mels, G.
- Venue
- Multivariate Behavioral Research
- Publisher
- Informa UK Limited
- Published
- 2013-01
- Volume
- 48
- Issue
- 1
- Pages
- 28-56
- ISSN
- 0027-3171 (ISSN-L)
- 1532-7906
- OpenAlex
- W2044946104
- Cited by
- 344
- References
- 4
- FWCI
- 27.20
- Type
- journal article
- Language
- en
- Open access
- closed
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