The DOI matches its Crossref record; 17 of the 20 references it cites were found in a registry or an index.
Minimizing Sample Size When Using Exploratory Factor Analysis for Measurement
Abstract
Traditional protocol for the determination of an adequate sample size is power analysis. Such a protocol is not useful when the primary hypothesis focuses on psychometric measurement properties. Traditional psychometrics advises that there should be 10 respondents per item. Both hypothetical and real research examples illustrate the usefulness of subsample analysis in determining that a sample size of at least 50 and not more than 100 subjects is adequate to represent and evaluate the psychometric properties of measures of social constructs. The "10 respondents per item" advice builds a sample size disincentive into the research design; it also represents "sample size overkill." Sample-size overkill occurs when the research design specifies a number of cases needed, which is in excess of the number actually needed for a desired inference.
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“Sapnas & Zeller (2002) demonstrate that sample sizes between 50 and 100 can be adequate when items are highly inter-related.”
From The Brief Serenity Scale (2009) · cites this paper as Sapnas & Zeller (2002)
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Cites
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Reliability and Validity Assessment
Carmines, E., & Zeller, R. (1979) · doi:10.4135/9781412985642 · Cited by 5,884
Self-citationSample size in factor analysis.
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Reliability and Validity Assessment
Kurian, G. T. (2011) · CQ Press eBooks · doi:10.4135/9781608712434.n1341 · Cited by 5,046
An Easy Guide to Factor Analysis
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3 of the 20 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- Kerlinger, F. (1986). Factor analysis. In F. Kerlinger, Foundations in behavioral research (3rd ed., pp. 569-593). Fort Worth: Holt, Rinehart, and Winston.
- 10.1037//1082-989X.4.1.84 · DOI · Paper page
- Zeller, R. A. (1980). Measurement in the social sciences. London: Cambridge University Press.
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Subaihi, B. A. (2013) · Coventry University Open Collections (Coventry university)
Metadata
- Authors
- Sapnas, K. G., & Zeller, R. A.
- Affiliations
- University of Miami (US)
- Kent State University (US)
- Venue
- Journal of Nursing Measurement
- Publisher
- Springer Publishing Company
- Published
- 2002-09
- Volume
- 10
- Issue
- 2
- Pages
- 135-154
- ISSN
- 1061-3749 (ISSN-L)
- 1945-7049
- OpenAlex
- W2088701782
- Cited by
- 405
- References
- 20
- Citations by year
- 2026: 24 · 2025: 26 · 2024: 30 · 2023: 34 · 2022: 28 · 2021: 19 · 2020: 22 · 2019: 17 · 2018: 27 · 2017: 22 · 2016: 28 · 2015: 20 · 2014: 24 · 2013: 17 · 2012: 15
- FWCI
- 5.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Nursing Measurement (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of Miami
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Health Sciences › Nursing › Research and Theory › Health Education and Validation
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- sample size determination, exploratory factor analysis, psychometric assessment, power analysis, measurement properties
- MeSH terms
- Computer Simulation, Factor Analysis, Statistical, Humans, Monte Carlo Method, Psychometrics, Likelihood Functions, Sample Size
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