A framework of statistical tests for comparing mean and covariance structure models

Multivariate Behavioral Research

Volumn 42, Issue 1, 2007, Pages 33-66

  Levy, Roy ^a   Hancock, Gregory R ^b  

^a ARIZONA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 34547448618     PISSN: 00273171     EISSN: None     Source Type: Journal    
DOI: 10.1080/00273170701329112     Document Type: Article

References (33)

1. Akaike, H. (1987). Factor analysis and AIC. Psychometrika, 52, 317-332.
2. Bagozzi, R. P., & Yi, Y. (1990). Assessing method variance in multitrait-multimethod matrices: The case of self-reported affect and perceptions at work. Journal of Applied Psychology, 75, 547-560.
3. Bentler, P. M. (2004). EQS 6 structural equations program manual. Encino, CA: Multivariate Software.
4. Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.
5. Bollen, K. A., & Armginer, G. (1991). Observational residuals in factor analysis and structural equation models. Sociological Methodology, 21, 235-262.
6. Bozdogan, H. (1987). Model-selection and Akaike's information criterion (AIC): The general theory and its analytical extensions. Psychometrika, 52, 345-370.
7. Byrne, B. M., & Goffin, R. D. (1993). Modeling MTMM data from additive and multiplicative covariance structures: An audit of construct validity concordance. Multivariate Behavioral Re-search, 28, 67-96.
8. Clarke, K. (2001). Testing nonnested models of international relations: Reevaluating realism. Amer-ican Journal of Political Science, 45, 724-744.
9. Cliff, N. (1983). Some cautions concerning the application of causal modeling methods. Multivariate Behavioral Research, 18, 115-126,
10. Cox, D. R. (1961). Tests of separate families of hypotheses. In J. Neyman (Ed.), Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, 1, (pp. 105-123). Berkeley: University of California Press.
11. Cox, D. R. ( 1962). Further results on tests of separate families of hypotheses. Journal of the Royal Statistical Society, B, 24, 406-424.
12. Duncan, T E., Duncan, S. C., Alpert, A., Hops, H., Stoolmiller, M., & Muthén, B. (1997). Latent variable modeling of longitudinal and multilevel substance use data. Multivariate Behavioral Research, 32, 275-318.
13. Fornell, C., & Rust, R. T. (1989). Incorporating prior theory in covariance structure analysis: A Bayesian approach. Psychometrika, 54, 249-259.
14. Golden, R. M. (2000). Statistical tests for comparing possibly misspecified and non-nested models. Journal of Mathematical Psychology, 44, 153-170,
15. Golden, R. M., (2003). Discrepancy risk model selection test theory for comparing possibly mis-specified or nonnested models. Psychometrika, 68, 229-249.
16. Gourieroux, C. & Monfort, A. (1994), Testing non-nested hypotheses. In R. F. Engle & D. L. McFadden (Eds). Handbook of Econometrics, vol. 4 (pp. 2583-2637). New York: Elsevier Science.
17. Lee., S., & Hershberger, S. L. (1990). A simple rule for generating equivalent models in covariance structure modeling. Multivariate Behavioral Research, 25, 313-334.
18. McDonald, R. P. (2002). What can we learn from the path equations?: Identifiability, constraints, equivalence. Psychometrika, 36, 225-249.
19. McDonald, R. P., & Mok, M. M.-C. (1995). Goodness of fit in item response models. Multivariate Behavioral Research, 30, 23-40.
20. Mizon, G., & Richard, J. F. (1986). The encompassing principle and its application to non-nested hypotheses. Econometrica, 54, 657-678.
21. Pearl, J. (2000). Causality: Models, reasoning, and inference. New York: Cambridge University Press.
22. Raykov, T. (2001), Approximate confidence interval for difference in fit of structural equation models. Structural Equation Modeling, 8, 458-469.
23. Raykov, T., & Marcoulides, G. A. (2001). Can there be infinitely many models equivalent to a given covariance structure model? Structural Equation Modeling: A Multidisciplinary Journal, 8, 142-149.
24. Raykov, T., & Penev, S. (1999). On structural equation model equivalence. Multivariate Behavioral Research, 34, 199-244.
25. Reise, S. P., & Widaman, K. F. (1999). Assessing the fit of measurement models at the individual level: A comparison of item response theory and covariance structure approaches. Psychological Methods, 4, 3-21.
26. Rust, R. T., Lee, C., & Valente, Jr., E. (1995). Comparing covariance structure models: A general methodology. International Journal of Research in Marketing, 12, 279-291.
27. Rust, R. T., & Schmittlein, D. C. (1985). A Bayesian cross-validated likelihood method for comparing alternative specifications of quantitative models. Marketing Science, 4, 20-40.
28. Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461-464.
29. Steiger, J. H., & Lind, J.C. (1980, May). Statistically-based tests for the number of common factors. Paper presented at the annual meeting of the Psychometric Society, Iowa City, IA, 1980.
30. Stelzl, I. (1986). Changing a causal hypothesis without changing the fit: Some rules for generating equivalent path models. Multivariate Behavioral Research, 21, 309-331.
31. Vuong, Q. H. (1989). Likelihood ratio tests for model selection and nonnested hypotheses. Econometrica, 57, 307-333.
32. White, H. (1982). Maximum likelihood estimation of misspecified models. Econometrica, 50, 1-26.
33. Widaman, K. F. (1985). Hierarchically tested covariance structure models for multitrait-multimethod data. Applied Psychological Measurement, 9, 1-26.