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ERIC Number: EJ865099
Record Type: Journal
Publication Date: 2009
Pages: 35
Abstractor: As Provided
Reference Count: 61
ISSN: ISSN-0027-3171
Exploratory Factor Analysis with Small Sample Sizes
de Winter, J. C. F.; Dodou, D.; Wieringa, P. A.
Multivariate Behavioral Research, v44 n2 p147-181 2009
Exploratory factor analysis (EFA) is generally regarded as a technique for large sample sizes ("N"), with N = 50 as a reasonable absolute minimum. This study offers a comprehensive overview of the conditions in which EFA can yield good quality results for "N" below 50. Simulations were carried out to estimate the minimum required "N" for different levels of loadings (lambda), number of factors ("f"), and number of variables ("p") and to examine the extent to which a small "N" solution can sustain the presence of small distortions such as interfactor correlations, model error, secondary loadings, unequal loadings, and unequal "p/f." Factor recovery was assessed in terms of pattern congruence coefficients, factor score correlations, Heywood cases, and the gap size between eigenvalues. A subsampling study was also conducted on a psychological dataset of individuals who filled in a Big Five Inventory via the Internet. Results showed that when data are well conditioned (i.e., high lambda, low "f", high "p"), EFA can yield reliable results for "N" well below 50, even in the presence of small distortions. Such conditions may be uncommon but should certainly not be ruled out in behavioral research data. (Contains 4 figures, 5 tables, and 5 footnotes.)
Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A