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Minimizing sample size when using exploratory factor analysis for measurement.

Kathryn G Sapnas1, Richard A Zeller

  • 1University of Miami, Jackson Memorial Hospital/Ryder Trauma Center, Miami, FL, USA. aesara@aol.com

Journal of Nursing Measurement
|March 7, 2003
PubMed
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For psychometric studies, traditional power analysis is insufficient for determining sample size. A sample size of 50-100 participants is adequate for evaluating social construct measures, avoiding sample size overkill.

Area of Science:

  • Psychometrics
  • Social Sciences Research Methodology

Background:

  • Traditional sample size determination relies on power analysis.
  • Power analysis is not suitable for hypotheses focused on psychometric properties.
  • Existing psychometric guidelines suggest 10 respondents per item.

Purpose of the Study:

  • To evaluate the adequacy of sample sizes for psychometric measurement properties.
  • To propose a more appropriate sample size range for psychometric research.
  • To address the issue of 'sample size overkill' in social construct measurement.

Main Methods:

  • Utilized subsample analysis with hypothetical and real research examples.
  • Evaluated psychometric properties of social construct measures.
  • Compared traditional guidelines with findings from subsample analysis.

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Main Results:

  • A sample size of 50 to 100 subjects is adequate for evaluating psychometric properties.
  • The '10 respondents per item' rule often results in sample size overkill.
  • Subsample analysis effectively determines appropriate sample sizes for psychometric evaluation.

Conclusions:

  • Sample size requirements for psychometric evaluation differ from those for traditional hypothesis testing.
  • A sample size of 50-100 participants is recommended for measuring social constructs.
  • Researchers should avoid excessive sample sizes to prevent inefficient research design.