This note summarizes my remarks on the application of reliability of the principal component and the eigenvalue-greater-than-1 rule for determining the number of factors in principal component analysis of a correlation matrix. Due to the unpredictability and uselessness of the reliability approach and the Kaiser-Guttman rule, research workers are encouraged to use other methods such as the scree test.
References
1.
CattellR. B. (1966) The scree test for the number of factors. Multivariate Behavioral Research, 1, 245–276.
2.
CliffN. (1988) The eigenvalue-greater-than-one rule and the reliability of components. Psychological Bulletin, 103, 276–279.
3.
KaiserH. F. (1992) On Cliff's formula, the Kaiser-Guttman rule, and the number of factors. Perceptual and Motor Skills, 74, 595–598.
4.
TzengO. C. S. (1992a). Comparisons of four input matrices for principal component analysis of bipolar ratings. (Unpublished manuscript, Indiana University-Purdue University at Indianapolis, Department of Psychology, Indianapolis)
5.
TzengO. C. S. (1992b) Psychometric measurement theories and issues. In TzengO. C. S., Measurement of love and intimate relations: Theories, scales and application for love development, maintenance and dissolution. New York: Praeger. (Chapter 5).
