Abstract
Exploratory factor analysis (EFA) is a complex, multi-step process. The goal of this paper is to collect, in one article, information that will allow researchers and practitioners to understand the various choices available through popular software packages, and to make decisions about “best practices” in exploratory factor analysis. In particular, this paper provides practical information on making decisions regarding (a) extraction, (b) rotation, (c) the number of factors to interpret, and (d) sample size.
Keywords
Exploratory factor analysisFactor (programming language)Exploratory analysisComputer sciencePsychologyStatisticsData scienceMathematicsStructural equation modelingProgramming language
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Publication Info
- Year
- 2020
- Type
- article
- Volume
- 10
- Issue
- 1
- Pages
- 1-9
- Citations
- 9998
- Access
- Closed
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Cite This
Anna B. Costello,
Jason W. Osborne
(2020).
Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis.
Scholarworks (University of Massachusetts Amherst)
, 10
(1)
, 1-9.
https://doi.org/10.7275/jyj1-4868
Identifiers
- DOI
- 10.7275/jyj1-4868