Relation of sample size to the stability of component patterns.
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Factor replicability is more likely when factors have at least four measured variables with structure coefficients > |.6|, irrespectively of the size of the sample.
“They proposed that factor replicability is more likely when: 1) factors have at least four measured variables with structure coefficients > |.6|, irrespectively of the size of the sample;”
From Applied Psychometrics: Sample Size and Sample Power Considerations in Factor Analysis (EFA, CFA) and SEM in General (2018) · cites this paper as Guadagnoli & Velicer, 1988
The crucial parameter in EFA sample size is the degree of factor saturation by the measured variables.
“In a similar vein, the Monte Carlo simulation work by Guadagnoli and Velicer (1988) suggested that the crucial parameter in EFA sample size is the degree of factor saturation by the measured variables.”
From Applied Psychometrics: Sample Size and Sample Power Considerations in Factor Analysis (EFA, CFA) and SEM in General (2018) · cites this paper as Guadagnoli and Velicer (1988)
For N > 150, factors are defined with 10 or more structure coefficients of about |.4| (and low p/m ratio), when 300 ≤ N ≤ 400.
“2) for N > 150 factors are defined with 10 or more structure coefficients of about |.4| (and low p/m ratio), when 300 ≤ N ≤ 400 (Guadagnoli & Velicer, 1988: p. 274 quoted in Dimitrov, 2012).”
From Applied Psychometrics: Sample Size and Sample Power Considerations in Factor Analysis (EFA, CFA) and SEM in General (2018) · cites this paper as Guadagnoli & Velicer, 1988
Strength of item loadings, uniformity of the communalities, and number of items per factor ('strong data') are vital for the stability, reliability, and replicability of a factor solution.
“studies suggest that strength of item loadings, uniformity of the communalities and number of items per factor (Guadagnoli & Velicer, 1988) or in two words 'Strong data' (Costello & Osborne, 2005) are vital for the stability, reliability, and replicability of a factor solution (Wang et al., 2013).”
From Applied Psychometrics: Sample Size and Sample Power Considerations in Factor Analysis (EFA, CFA) and SEM in General (2018) · cites this paper as Guadagnoli & Velicer, 1988
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“Generally, the findings of Velicer and Fava (1998) see also Guadagnoli & Velicer, 1988) about the size of the factor loadings and the number of variables as a function of the sample size are important elements for obtaining a good CFA or SEM model as DOI: 10.4236/psych.2018.98126 2212…”
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“Somewhere between 100 and 300 subjects have been suggested as the minimum number of subjects, whereby Guadagnoli and Velicer (1988) even suggested that 100 subjects may be acceptable.”
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“Loadings of this size have been shown to be interpretable whatever the sample size used (Guadagnoli & Velicer, 1988).”
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- Authors
- Guadagnoli, E., & Velicer, W. F.
- Affiliations
- Brown University (US)
- ORCID
- Velicer, Wayne F.
- Venue
- Psychological Bulletin
- Published
- 1988-03
- Volume
- 103
- Issue
- 2
- Pages
- 265-275
- ISSN
- 0033-2909 (ISSN-L)
- 1939-1455
- OpenAlex
- W2058513103
- Cited by
- 2,880
- References
- 2
- Citations by year
- 2026: 123 · 2025: 160 · 2024: 183 · 2023: 202 · 2022: 186 · 2021: 171 · 2020: 141 · 2019: 117 · 2018: 138 · 2017: 95 · 2016: 110 · 2015: 86 · 2014: 105 · 2013: 99 · 2012: 89
- FWCI
- 22.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Bulletin (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute (CA 27821)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- sample size, factor analysis
- MeSH terms
- Factor Analysis, Statistical, Humans, Monte Carlo Method, Sampling Studies
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