A Comparison of Five Rules for Determining the Number of Components in Complex Patterns
Year: 1983
Type: article
Abstract: The performance of five methods for determining the number of components to retain (Horn's parallel analysis, Velicer is MAP, Cattell is SCREE, Bartlett's test and Kaiser's eigenvalue greater than unity) was investigated across seven systematically varied factors (sample size, number of variables, number of components, component saturation, equal or unequal numbers of variables per component, and the presence or absence of unique and complex variables). Five sample correlation matrices were generated at each of two levels of sample size from the 48 known population correlation matrices representing six levels of component pattern complexity. The performance of the parallel analysis and the MAP methods was generally the best across all situations. The SCREE test was generally accurate but variable. Bartlett's test was less accurate and more variable than the SCREE test. Kaiser's method tended to severely overestimate the number of components. Recommendations concerning the conditions under which the methods are accurate and the most effective and useful applications of combinations of methods are discussed.
Author: Zwick, William R.
Institution: University of Rhode Island
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6980604671