Confirmatory factor analysis of ordinal variables with misspecified models

Structural Equation Modeling

Volumn 17, Issue 3, 2010, Pages 392-423

  Yang Wallentin, Fan ^a,b   Jöreskog, Karl G ^a,b   Luo, Hao ^a  

^a UPPSALA UNIVERSITY   (Sweden)

^b BI NORWEGIAN BUSINESS SCHOOL   (Norway)

Author keywords

[No Author keywords available]

Indexed keywords

ASYMPTOTIC COVARIANCE MATRIX; CONFIRMATORY FACTOR ANALYSIS; EMPIRICAL INVESTIGATION; MAXIMUM LIKELIHOOD METHODS; SIMULATION EVALUATION; SOCIAL AND BEHAVIORAL SCIENCE; STRUCTURAL EQUATION MODELS; WEIGHTED LEAST SQUARES;

BEHAVIORAL RESEARCH; COMPUTER SIMULATION; COVARIANCE MATRIX; FACTOR ANALYSIS; NORMAL DISTRIBUTION; PARAMETER ESTIMATION; VOLTAGE MEASUREMENT;

LEAST SQUARES APPROXIMATIONS;

EID: 77954442639     PISSN: 10705511     EISSN: None     Source Type: Journal    
DOI: 10.1080/10705511.2010.489003     Document Type: Article

References (25)

1. Bentler, P. M. (1995). EQS structural equations program manual. Encino, CA: Multivariate Software.
2. Browne, M. W. (1984). Asymptotically distribution-free methods for the analysis of covariance structures. British Journal of Mathematical & Statistical Psychology, 37, 62-83.
3. Curran, P. J., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological Methods, 1, 16-29.
4. Dolan, C. V. (1994). Factor analysis of variables with 2, 3, 5, and 7 response categories: A comparison of categorical variable estimators using simulated data. British Journal of Mathematical & Statistical Psychology, 47, 309-326.
5. Flora, D. B., & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9, 466-491.
6. Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34, 183-202.
7. Jöreskog, K. G. (1990). New developments in Lisrel: analysis of ordinal variables using polychoric correlations and weighted least squares. Quality and Quantity, 24, 387-404.
8. Jöreskog, K. G. (1994). On the estimation of polychoric correlations and their asymptotic covariance matrix. Psychometrika, 59, 381-389.
9. Jöreskog, K. G. (2002-2005). Structural equation modeling with ordinal variables using Lisrel. Available at http:// www.ssicentral.com/lisrel/techdocs/ordinal.pdf
10. Jöreskog, K. G., & Sörbom, D. (1996a). LISREL 8: User's reference guide. Chicago, IL: Scientific Software International.
11. Jöreskog, K. G., & Sörbom, D. (1996b). PRELIS 2: User's reference guide. Chicago, IL: Scientific Software International.
12. Jöreskog, K. G., Sörbom, D., du Toit, S., & du Toit, M. (2003). LISREL 8: New statistical features. Chicago, IL: Scientific Software International.
13. Kaplan, D. (1989). A study of the sampling variability and z-values of parameter estimates from misspecified structural equation models. Multivariate Behavioral Research, 24, 41-57.
14. Lee, S., Poon, W., & Bentler, P. M. (1990). Full maximum likelihood analysis of structural equation models with polytomous variables. Statistics & Probability Letters, 9, 91-97.
15. Magnus, J. R., & Neudecker, H. (1999). Matrix differential calculus with applications in statistics and econometrics (2nd ed.). Hoboken, NJ: Wiley.
16. Muthén, B. O. (1984). A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicators. Psychometrika, 49, 115-132.
17. Muthén, B. O., du Toit, S., &Spisic, D. (1997). Robust inference using weighted least squares and quadratic estimating equations in latent variable modeling with categorical and continuous outcomes. Unpublished manuscript.
18. Muthén, B. O., & Kaplan, D. (1985). A comparison of some methodologies for the factor analysis of non-normal likert variables. British Journal of Mathematical & Statistical Psychology, 38, 171-189.
19. Muthén, B. O., & Kaplan, D. (1992). A comparison of some methodologies for the factor analysis of non-normal likert variables: A note on the size of the model. British Journal of Mathematical & Statistical Psychology, 45, 19-30.
20. Muthén, L. K., & Muthén, B. O. (1998). Mplus users guide. Los Angeles, CA: Muthén & Muthén.
21. Olsson, U. (1979). Maximum likelihood estimation of the polychoric correlation coefficient. Psychometrika, 44, 443- 460.
22. Potthast, M. J. (1993). Confirmatory factor analysis of ordered categorical variables with large models. British Journal of Mathematical & Statistical Psychology, 46, 273-286.
23. Satorra, A. (1989). Alternative test criteria in covariance structure analysis: A unified approach. Psychometrika, 54, 131-151.
24. Satorra, A. (2003). Power of chi-square goodness-of-fit test in structural equation models: The case of nonnormal data. In H. Yanai, A. Okada, K. Shigemasu, Y. Kano, & J. J. Meulman (Eds.), New developments of psychometrics (pp. 57-68). Springer Verlag, Tokyo.
25. Satorra, A., & Bentler, P. M. (1988). Scaling corrections for chi-square statistics in covariance structure analysis. In American Statistical Association, Proceedings of the Business and Economic Section, pp. 308-313.