Recent studies have indicated that under the proper circumstances factor anaylisis may be accurately performed in samples as small as N = 9. However, all of these studies have extracted a pre-known number of factors, leaving an examination of determining the proper number of factors to future studies. The current study uses examines the following methods for determining the proper number of factors: Monte Carlo data to examine the performance of common versions of the Kaiser Rule, minimum average partial, parallel analysis and salient loading criteria under the conditions created by all possible combinations of method, model strength, overdetermination and sample size. Method performance was compared for overall accuracy (percent correct), and average discrepancy (mean difference from correct). ANOVA revealed that item level methods, including salient loading criteria and MAP procedures, maintain accuracy when model strength is at least moderate and overdetermiantion is high. Use of selected empirical methods for determining the number of factors is possible in small sample sizes only when overdetermination and model strength are adequately high, larger sample sizes should be preferred when possible.
School of Behavioral Health
Boyd, Kendal C.
Herbozo, Sylvia M.
Morrell, Holly E. R.
Doctor of Philosophy (PhD)
Year Degree Awarded
Date (Title Page)
Library of Congress/MESH Subject Headings
Factor Analysis; Quantitative Research; Psychometrics; Variability (Psychometrics); Number Concept
Subject - Local
Monte Carlo Data; Kaiser Rule; Minimum Average Partial; Parallel Analysis; Salient Loading Criteria
Loma Linda University Libraries
This title appears here courtesy of the author, who has granted Loma Linda University a limited, non-exclusive right to make this publication available to the public. The author retains all other copyrights.
Porritt, Marc Thomas, "Performance of Number of Factors Procedures in Small Sample Sizes" (2015). Loma Linda University Electronic Theses, Dissertations & Projects. 283.
Loma Linda University Electronic Theses and Dissertations
Loma Linda University. Del E. Webb Memorial Library. University Archives