Analyzing the reliability of multidimensional measures: An example from intelligence research

Educational and Psychological Measurement

Volumn 65, Issue 2, 2005, Pages 227-240

  Brunner, Martin ^a   Süß, Heinz Martin ^b  

^a MAX PLANCK INSTITUTE FOR HUMAN DEVELOPMENT   (Germany)

^b OTTO VON GUERICKE UNIVERSITY   (Germany)

Author keywords

Confirmatory factor analysis; Hierarchical factor models; Multidimensional measures; Reliability analysis

Indexed keywords

EID: 17044423020     PISSN: 00131644     EISSN: None     Source Type: Journal    
DOI: 10.1177/0013164404268669     Document Type: Article

References (33)

1. Allen, M. P. (1974). Construction of composite measures by the canonical-factor-regression method. In H. L. Costner (Ed.), Sociological methodology (pp. S1-78). San Francisco: Jossey-Bass.
2. Bacon, D. R., Sauer, P. L., & Young, M. (1995). Composite reliability in structural equation modeling. Educational and Psychological Measurement, 55, 394-406.
3. Benito, J. G. (1989). Estimates of the internal consistency of a factorially complex composite. Educational and Psychological Measurement, 49, 571-578.
4. Bentler, P. M. (1995). EQS: A structural equations program manual. Encino, CA: Multivariate Software.
5. Bentler, P. M., & Dudgeon, P. (1996). Covariance structure analysis: Statistical practice, theory, and directions. Annual Review of Psychology, 47, 563-592.
6. Bollen, K. A. (1989). Structural equations with latent variables. New York: John Wiley.
7. Bollen, K. A., & Lennox, R. (1991). Conventional wisdom on measurement: A structural equation perspective. Psychological Bulletin, 110, 305-314.
8. Carroll, J. B. (1993). Human cognitive abilities - A survey of factor analytic studies. New York: Cambridge University Press.
9. Crocker, L., & Algina, J. (1986). Introduction to classical and modern test theory. New York: Holt, Rinehart & Winston.
10. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297-334.
11. DeShon, R. P. (1998). A cautionary note on measurement error in corrections in structural equation models. Psychological Methods, 3, 412-423.
12. Gustafsson, J., & Balke, G. (1993). General and specific abilities as predictors of school achievement. Multivariate Behavioral Research, 28, 407-434.
13. Hancock, G. R., & Mueller, R. O. (2001). Rethinking construct reliability within latent variable systems. In R. Cudeck, S. du Toit, & D. Soerbom (Eds.), Structural equation modeling: Present and future - A festschrift in honor of Karl Jöreskog (pp. 195-216). Lincolnwood, IL: Scientific Software International.
14. Hogan, T. P., Benjamin, A., & Brezinski, K. L. (2000). Reliability methods: A note on the frequency of use of various types. Educational and Psychological Measurement, 60, 523-531.
15. Hu, L.-T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3, 424- 453.
16. Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55.
17. Jäger, A. O., Süß, H.-M., & Beauducel, A. (1997). Berlin Intelligence Structure-Test, Form 4. Göttingen, Germany: Hogrefe.
18. Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental test scores. Reading, MA: Addison-Wesley.
19. MacCallum, R. (1986). Specification searches in covariance structure modeling. Psychological Bulletin, 100, 107-120.
20. MacCallum, R. C., Roznowski, M., & Necowitz, L. B. (1992). Model modifications in covariance structure-analysis - The problem of capitalization on chance. Psychological Bulletin, 111, 490-504.
21. McDonald, R. P. (1970). The theoretical foundations of principal factor analysis, canonical factor analysis, and alpha factor analysis. British Journal of Mathematical and Statistical Psychology, 23, 1-21.
22. McDonald, R. P. (1981). The dimensionality of tests and items. British Journal of Mathematical and Statistical Psychology, 34, 100-117.
23. McDonald, R. P. (1999). Test theory: A unified treatment. Mahwah, NJ: Lawrence Erlbaum.
24. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. New York: McGraw-Hill.
25. Raines-Eudy, R. (2000). Using structural equation modeling to test for differential reliability and validity: An empirical demonstration. Structural Equation Modeling, 7, 124-141.
26. Raykov, T. (1997). Estimation of composite reliability for congeneric measures. Applied Psychological Measurement, 21, 173-184.
27. Raykov, T. (1998a). Coefficient alpha and composite reliability with interrelated nonhomogeneous items. Applied Psychological Measurement, 22, 375-385.
28. Raykov, T. (1998b). A method for obtaining standard errors and confidence intervals of composite reliability for congeneric items. Applied Psychological Measurement, 22, 369-374.
29. Raykov, T., & Shrout, P. E. (2002). Reliability of scales with general structure: Point and interval estimation using a structural equation modeling approach. Structural Equation Modeling, 9, 195-212.
30. Süß, H.-M., Oberauer, K., Wittmann, W. W., Wilhelm, O., & Schulze, R. (2002). Working-memory capacity explains reasoning ability - And a little bit more. Intelligence, 30, 261-288.
31. Werts, C. E., Rock, D. A., Linn, R. L., & Joreskog, K. G. (1978). A general method of estimating the reliability of a composite. Educational and Psychological Measurement, 38, 933-938.
32. West, S. G., Finch, J. F., & Curran, P. J. (1995). Structural equation models with nonnormal variables: Problems and remedies. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 56-75). Thousand Oaks, CA: Sage.
33. Wilhelm, O., & Schulze, R. (2002). The relation of speeded and unspeeded reasoning with mental speed. Intelligence, 30, 537-554.