The effects of underextraction in factor and component analyses

Educational and Psychological Measurement

Volumn 56, Issue 6, 1996, Pages 907-929

  Fava, Joseph L ^a   Velicer, Wayne F ^b  

^a UNIVERSITY OF RHODE ISLAND   (United States)

^b NONE

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0030329206     PISSN: 00131644     EISSN: None     Source Type: Journal    
DOI: 10.1177/0013164496056006001     Document Type: Article

References (40)

1. Anderson, T. W., & Rubin, H. (1956). Statistical inference in factor analysis. In J. Neyman (Ed.), Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability (pp. 111-150). Berkeley: University of California Press.
2. Bartlett, M. S. (1937). The statistical conception of mental factors. British Journal of Psychology, 28, 97-104.
3. Boomsma, A. (1982). The robustness of LISREL against small sample sizes in factor analysis models. In K. G. Jöreskog & H. Wold (Eds.), Systems under indirect observation (Part 1, pp. 149-173). Amsterdam: North Holland.
4. Browne, M. W. (1968). A comparison of factor analytic techniques. Psychometrika, 33, 267-334.
5. Cattell, R. B. (1952). Factor analysis: An introduction and manual for the psychologist and scholar scientist. New York: Harper & Brothers.
6. Cattell, R. B. (1958). Extracting the correct number of factors in factor analysis. Educational and Psychological Measurement, 18, 791-838.
7. Cattell, R. B. (1978). The scientific use of factor analysis in behavioral and life sciences. New York: Plenum.
8. Comrey, A. L. (1973). A first course in factor analysis. New York: Plenum.
9. Comrey, A. L. (1978). Common methodological problems in factor analytic studies. Journal of Consulting and Clinical Psychology, 46, 648-659.
10. Fava, J. L., & Velicer, W. F. (1992a). The effects of overextraction on factor and component analysis. Multivariate Behavioral Research, 27, 387-415.
11. Fava, J. L., & Velicer, W. F. (1992b). An empirical comparison of factor, image, component, and scale scores. Multivariate Behavioral Research, 27, 301-322.
12. Gorsuch, R. L. (1983). Factor analysis (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
13. Guadagnoli, E., & Velicer, W. F. (1988). The relationship of sample size to the stability of component patterns. Psychological Bulletin, 103, 265-275.
14. Guadagnoli, E., & Velicer, W. F. (1991). A comparison of pattern matching indices. Multivariate Behavioral Research, 26, 323-343.
15. Guertin, W. H., & Bailey, J. P., Jr. (1970). Introduction to modern factor analysis. Ann Arbor, MI: Edwards Brothers.
16. Guttman, L. (1955). The determinancy of factor score matrices with implications for five other basic problems of common-factor theory. British Journal of Statistical Psychology, 8, 65-81.
17. Harris, C. W. (1967). On factors and factor scores. Psychometrika, 32, 363-379.
18. 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.
19. Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30, 179-185.
20. Hotelling, H. (1933). Analysis of a complex of statistical variables into principal components. Journal of Educational Psychology, 24, 417-441, 498-520.
21. Kaiser, H. F. (1958). The varimax criterion for analytic rotation in factor analysis. Psychometrika, 23, 187-200.
22. McDonald, R. P., & Burr, E. J. (1967). A comparison of four methods of constructing factor scores. Psychometrika, 32, 381-401.
23. Montanelli, R. G., Jr. (1975). A computer program to generate sample correlation and covariance matrices. Educational and Psychological Measurement, 35, 195-197.
24. Mosier, C. I. (1939). Influence of chance error on simple structure: An empirical investigation of the effect of chance error and estimated communalities on simple structure in factorial analysis. Psychometrika, 4, 33-44.
25. Odell, P. L., & Feiveson, A. H. (1966). A numerical procedure to generate a sample covariance matrix. Journal of the American Statistical Association, 61, 199-203.
26. Rindskopf, D. (1984). Structural equation models: Empirical identification, Heywood cases, and related problems. Sociological Methods & Research, 13, 109-119.
27. Rummel, R. J. (1970). Applied factor analysis. Evanston, IL: Northwestern University Press.
28. Schönemann, P. H., & Wang, M. (1972). Some new results on factor indeterminacy. Psychometrika, 37, 61-91.
29. Thomson, G. (1936). Some points of mathematical technique in the factorial analysis of ability. Journal of Educational Psychology, 27, 37-54.
30. Thurstone, L. L. (1935). The vectors of mind. Chicago: University of Chicago Press.
31. Thurstone, L. L. (1947). Multiple-factor analysis: A development and expansion of The Vectors of Mind. Chicago: University of Chicago Press.
32. Velicer, W. F. (1976a). Determining the number of components from the matrix of partial correlations. Psychometrika, 41, 321-327.
33. Velicer, W. F. (1976b). The relation between factor score estimates, image scores, and principal component scores. Educational and Psychological Measurement, 36, 149-159.
34. Velicer, W. F., & Fava, J. L. (1987). An evaluation of the effects of variable sampling on component, image, and factor analysis. Multivariate Behavioral Research, 22, 193-209.
35. Velicer, W. F., & Fava, J. L. (1996). The effects of variable and subject sampling on factor pattern recovery. Manuscript submitted for publication.
36. Velicer, W. F., & Jackson, D. N. (1990a). Component analysis versus common factor analysis: Some further observations. Multivariate Behavioral Research, 25, 97-114.
37. Velicer, W. F., & Jackson, D. N. (1990b). Component analysis versus common factor analysis: Some issues in selecting an appropriate procedure. Multivariate Behavioral Research, 25, 1-28.
38. 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.
39. Zwick, W. R., & Velicer, W. F. (1982). Factors influencing four rules for determining the number of components to retain. Multivariate Behavioral Research, 17, 253-269.
40. Zwick, W. R., & Velicer, W. F. (1986). A comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99, 432-442.