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Evaluating the use of exploratory factor analysis in psychological research.
Abstract
Despite the widespread use of exploratory factor analysis in psychological research, researchers often make questionable decisions when conducting these analyses. This article reviews the major design and analytical decisions that must be made when conducting a factor analysis and notes that each of these decisions has important consequences for the obtained results. Recommendations that have been made in the methodological literature are discussed. Analyses of 3 existing empirical data sets are used to illustrate how questionable decisions in conducting factor analyses can yield problematic results. The article presents a survey of 2 prominent journals that suggests that researchers routinely conduct analyses using such questionable methods. The implications of these practices for psychological research are discussed, and the reasons for current practices are reviewed. Since its initial development nearly a century ago (Spearman, 1904, 1927), exploratory factor analysis (EFA) has been one of the most widely used statistical procedures in psychological research. Despite this
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“The standardized loading coefficients for each observed item were significantly greater than 0.5, implying a high level of correlation between each dimension and its constituent latent variables (Table 1) [70]. The construct reliabilities (CR) of the latent variables were all greater than 0.7 and their average variance extractions (AVE) were all greater than 0.5, indicating high aggregation valid”
From Health and Wellness Tourists’ Motivation and Behavior Intention: The Role of Perceived Value (2023) · cites this paper as [70]
In the citing paper
“The variance inflation factors (VIFs) of the question items were all less than 3, and there was no significant multicollinearity among the items [70].”
From Health and Wellness Tourists’ Motivation and Behavior Intention: The Role of Perceived Value (2023) · cites this paper as [70]
In the citing paper
“The results showed that the factor loadings were all greater than 0.5, meaning that they all met the internal consistency reliability requirements [70,71].”
From Health and Wellness Tourists’ Motivation and Behavior Intention: The Role of Perceived Value (2023) · cites this paper as [70]
In the citing paper
“Therefore, the sample size is by and large specified by the nature of the data (Fabrigar et al., 1999).”
From Applied Psychometrics: Sample Size and Sample Power Considerations in Factor Analysis (EFA, CFA) and SEM in General (2018) · cites this paper as Fabrigar et al., 1999
In the citing paper
“The ML method is suitable for determining latent factors (Fabrigar et al., 1999)”
From Measuring undergraduate students’ reliance on generative AI during problem-solving: Scale development and validation. (2025) · cites this paper as Fabrigar et al., 1999
In the citing paper
“Given the exploratory nature of EPM, EFA represents an appropriate approach for assessing construct validity and is widely recommended for emerging areas of research (Fabrigar et al., 1999;Hair et al., 2019).”
From Exploring the Moderating Effect of Ethical Project Management Practices in the Success of IT Project: Evidence From the Public Sector (2026) · cites this paper as Fabrigar et al., 1999
In the citing paper
“It is essential to acknowledge that skipping EFA in the validation can have some limitations, such as the potential to overlook alternative factor structures or issues with item loadings (Fabrigar et al., 1999).”
From An expectancy value theory (EVT) based instrument for measuring student perceptions of generative AI (2023) · cites this paper as Fabrigar et al., 1999
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Developing and validating trust measures for e-commerce: an integrative typology
McKnight, D. H., Choudhury, V., & Kacmar, C. (2002) · Information Systems Research · doi:10.1287/isre.13.3.334.81 · Cited by 5,550
Assessing measurement model quality in PLS-SEM using confirmatory composite analysis
Hair, J. F., Howard, M. C., & Nitzl, C. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2019.11.069 · Cited by 5,446
Ethical leadership: A social learning perspective for construct development and testing
Brown, M. E., Treviño, L. K., & Harrison, D. A. (2005) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2005.03.002 · Cited by 5,435
Handbook on Constructing Composite Indicators: Methodology and User Guide
OECD, Union, E., & Joint Research Centre - European Commission (2008) · doi:10.1787/9789264043466-en · Cited by 3,960
Metadata
- Authors
- Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J.
- Affiliations
- Queen's University (CA)
- ORCID
- Wegener, Duane T.
- Venue
- Psychological Methods
- Published
- 1999-09
- Volume
- 4
- Issue
- 3
- Pages
- 272-299
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W1977775666
- Cited by
- 9,587
- References
- 128
- Citations by year
- 2026: 777 · 2025: 658 · 2024: 598 · 2023: 548 · 2022: 538 · 2021: 577 · 2020: 526 · 2019: 528 · 2018: 476 · 2017: 452 · 2016: 461 · 2015: 472 · 2014: 478 · 2013: 413 · 2012: 346
- FWCI
- 40.50
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Methods (publishedVersion)
- Funders
- National Institutes of Health
- Social Sciences and Humanities Research Council of Canada
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- exploratory factor analysis, questionable research practices, methodological recommendations, research integrity, publication practices
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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