Cited by 416Psychometric Methodologies and TestingHealth Education and ValidationStatistical Methods in Epidemiology

Minimizing Sample Size When Using Exploratory Factor Analysis for Measurement

Sapnas, Kathryn G., Zeller, Richard A.·2002·Journal of Nursing 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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Crossref · 10.1891/jnum.10.2.135.52552

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  • Sapnas and Zeller showed that 50 to 100 participants can suffice when items are strongly inter-related.

    “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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Authors
Sapnas, K. G., & Zeller, R. A.
Affiliations
  • University of Miami (US)
  • Kent State University (US)
Venue
Journal of Nursing Measurement
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
  • Social Sciences › Education › 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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