Discriminating between measurement scales using nonnested tests and 2SLS: Monte Carlo evidence

Structural Equation Modeling

Volumn 9, Issue 1, 2002, Pages 103-125

  Oczkowski, Edward ^a  

^a CHARLES STURT UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0037849794     PISSN: 10705511     EISSN: None     Source Type: Journal    
DOI: 10.1207/S15328007SEM0901_6     Document Type: Article

References (35)

1. Balasubramanian, S. K., & Jain, D.C. (1994). Simple approaches to evaluate competing non-nested models in marketing, International Journal of Research in Marketing, 11, 53-72.
2. Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588-606.
3. Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.
4. Bollen, K. A. (1996). An alternative two stage least squares (2SLS) estimator for latent variable equations. Psychometrika, 61, 109-121.
5. Bollen, K. A., & Paxton, P. (1998). Two-stage least squares estimation of interaction effects. Structural Equation Modeling, 5, 267-293.
6. Breckler, S. J. (1990). Applications of covariance structure modeling in psychology: Cause for concern. Psychological Bulletin, 107, 260-273.
7. Brent, R. P. (1974). Algorithm 488: A Gaussian pseudo-random number generator. Communications of the ACM, 17, 704-706.
8. Browne, M.W., & Cudeck, R. (1993) Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136-162) Newbury Park, CA: Sage.
9. Collins, J. M., & Muchinsky, P. M. (1993). An assessment of the construct validity of three job evaluation methods: A field experiment. Academy of Management Journal, 36, 895-904.
10. Connery, S., Katz, D., Kaufman, A. S., & Kaufman, N. L. (1996). Correlations between two short cognitive tests and a WISC-III short form using a sample of adolescent inpatients. Psychological Reports, 78, 1373-1378.
11. Davidson, R., & MacKinnon, J. G. (1981). Several tests for model specification in the presence of alternative hypotheses. Econometrica, 49, 781-793.
12. Davidson, R., & MacKinnon, J. G. (1993). Estimation and inference in econometrics. New York: Oxford University Press.
13. DeVellis, R. F. (1991). Scale development: Theory and applications. Newbury Park, CA: Sage.
14. Ding, L., Velicer, W. F., & Harlow, L. L. (1995). Effects of estimation methods, number of indicators per factor, and improper solutions on structural equation modeling fit indices. Structural Equation Modeling, 2, 119-143.
15. Fornell, C., & Larker, D. F. (1981) Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39-50.
16. Futrell, C. M. (1979). Measurement of salespeople's job satisfaction: Convergent and discriminate validity of corresponding INDSALES and job descriptive index scales. Journal of Marketing Research, 16, 594-597.
17. Godfrey, L. G. (1998). Tests of non-nested regression models: Some results on small sample behaviour and the bootstrap. Journal of Econometrics, 84, 59-74.
18. Godfrey, L. G., McAleer, M., & McKenzie, C. R. (1988). Variable addition and lagrange multiplier tests for linear and logarithmic regression models. Review of Economics and Statistics, 70, 492-503.
19. Gourieroux, C., & Monfort, A. (1994). Testing non-nested hypotheses. In R. F. Engle & D. L. McFadden (Eds.), Handbook of econometrics (Vol. IV, pp. 2583-2637). Amsterdam: Elsevier Science.
20. Jöreskog, K. G. (1993). Testing structural equation models. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 294-316). Newbury Park, CA: Sage.
21. Jöreskog, K. G. (1998). Interaction and nonlinear modeling: Issues and approaches. In R. E. Schumacker & G. A. Marcoulides (Eds.), Interaction and nonlinear effects in structural equation modeling (pp. 239-250). Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
22. Maddala, G. S. (1992). Introduction to econometrics. 2nd ed. New York: Macmillan.
23. McAleer, M. (1987). Specification tests for separate models: A survey. In M. King & D. E. A. Giles (Eds.), Specification analysis in the linear model (pp. 145-196). London: Routledge and Kegan Paul.
24. McAleer, M. (1995). The significance of testing empirical non-nested models. Journal of Econometrics, 67, 149-171.
25. Mizon, G. E., & Richard, J. F. (1986). The encompassing principle and its application to testing non-nested hypotheses. Econometrica, 54, 657-678.
26. Mone, M. A. (1994). Comparative validity of two measures of self-efficacy in predicting academic goals and performance. Educational and Psychological Measurement, 54, 516-529.
27. Muchinsky, P. M. (1996). The correction of attenuation. Educational and Psychological Measurement, 56, 63-75.
28. Nilsson, J. E. (1995). The GRE and the GMAT: A comparison of their correlations to GGPA. Educational and Psychological Measurement, 55, 637-640.
29. Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.
30. Oczkowski, E., & Farrell, M. A. (1998). Discriminating between measurement scales using non-nested tests and two-stage least squares estimators: The case of market orientation. International Journal of Research in Marketing, 15, 349-366.
31. Pesaran, M. H., & Taylor, L.W. (1999). Diagnostics for IV regressions. Oxford Bulletin of Economics and Statistics, 61, 255-281.
32. Rust, R. T., Lee, C., & Valente, E., Jr. (1995). Comparing covariance structure models: A general methodology. International Journal of Research in Marketing, 12, 279-291.
33. SHAZAM. (1997). User's reference manual version 8.0. New York: McGraw-Hill.
34. Smith, R. J. (1992). Non-nested tests for competing models estimated by generalized method of moments. Econometrica, 60, 973-980.
35. Tanaka, J. S. (1993). Multifaceted conceptions of fit in structural equation models. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 10-39). Newbury Park, CA: Sage.