A Monte Carlo study involving 10,080 factor analyses examined the optimal value of k for promax factor rotations. The value of k was varied from 2 to 10 using three versions of promax. Error and bias of the sample factor pattern were found to be lower when k [.lessequal] 5 than when k > 5 but changed only slightly as k varied between 2 and 5. The best value of k was 2, 3, or 4, depending on the version of promax. It is concluded that in factor analytic studies using promax, the value of k may be appropriately set at 2, 3, or 4.
Get full access to this article
View all access options for this article.
References
1.
Cureton, E. E. (1976). Studies of the promax and optres rotations. Multivariate Behavioral Research, 4, 449-460.
2.
Gorsuch, R. L. (1983). Factor analysis (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
3.
Hakstian, A. R. (1971). A comparative evaluation of several prominent methods of oblique factor transformation. Psychometrika, 36, 175-193.
4.
Hays, W. L. (1981). Statistics (3rd ed.). New York: Holt, Rinehart & Winston.
5.
Hendrickson, A. E. , & White, P. O. (1964). Promax: A quick method for rotation to oblique simple structure. British Journal of Statistical Psychology, 17, 65-70.
6.
SAS Institute Inc. (1988). SAS/STAT user’s guide, Release 6.03 edition. Cary, NC: Author.
7.
Snook, S. C. , & Gorsuch, R. L. (1989). Component analysis versus common factor analysis: A Monte Carlo study. Psychological Bulletin, 106, 148-154.
8.
Thompson, B. , & Daniel, L. G. (1996). Factor analytic evidence for the construct validity of scores: An historical overview and some guidelines. Educational and Psychological Measurement, 56, 213-224.
9.
Velicer, W. F. , Peacock, A. C., & Jackson, D. N. (1982). A comparison of component and factor patterns: A Monte Carlo approach. Multivariate Behavioral Research, 17, 371-388.
10.
Wood, J. M. , Tataryn, D. J., & Gorsuch, R. L. (1996). Effects of under- and over-extraction on principal axis factor analysis with varimax rotation. Psychological Methods, 1, 354-365.
