Effects of score discreteness and estimating alternative model parameters on power estimation methods in structural equation modeling

Structural Equation Modeling

Volumn 11, Issue 1, 2004, Pages 20-44

  Lei, Pui Wa ^a   Dunbar, Stephen B ^b  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF IOWA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; CORRELATION METHODS; ERROR ANALYSIS; MATHEMATICAL MODELS; MATRIX ALGEBRA;

MODEL PARAMETERS; POWER ESTIMATION METHODS; SPECIFICATION ERRORS; STRUCTURAL EQUATION MODELS (SEM);

PARAMETER ESTIMATION;

EID: 2642551580     PISSN: 10705511     EISSN: None     Source Type: Journal    
DOI: 10.1207/S15328007SEM1101_2     Document Type: Article

References (15)

1. Bentler, P. M. (1995). EQS structural equations program manual. Encino, CA: Multivariate Software, Inc.
2. Bentler, P. M., & Wu, E. J. C. (1995). EQS for Window user's guide. Encino, CA: Multivariate Software, Inc.
3. Bollen, K. A. (1986). Sample size and Bentler and Bonett's nonnormed fit index. Psychometrika, 51, 375-377.
4. Kaplan, D. (1990). Evaluating and modifying covariance structure models: A review and recommendation. Multivariate Behavioral Research, 25, 137-155.
5. Kaplan, D., & Wenger, R. N. (1993). Asymptotic independence and separability in covariance structure models: Implications for specification error, power, and model modification. Multivariate Behavioral Research, 28, 467-482.
6. Matsueda, R. L., & Bielby, W. T. (1986). Statistical power in covariance structure models. In N. B. Tuma (Ed.), Sociological methodology 1986 (pp. 120-158). Washington, DC: American Sociological Association.
7. Olsson, U. H., Foss, T., Troye, S. V., & Howell, R. D. (2000). The performance of ML, GLS, and WLS estimation in structural equation modeling under conditions of misspecification and nonnormality. Structural Equation Modeling, 7, 557-595.
8. Saris, W. E., den Ronden, J., & Satorra, A. (1987). Testing structural equation models. In P. Cuttance & R. Ecob (Eds.), Structural modeling by example: Applications in educational, sociological, and behavioral research (pp. 202-220). New York: Cambridge University Press.
9. Saris, W. E., & Satorra, A. (1987). Characteristics of structural equation models which affect the power of the likelihood ratio test. In W. E. Saris & I. N. Gallhofer (Eds.), Sociometric research: Vol. 2 (pp. 220-236). London: Macmillan.
10. Saris, W. E., & Satorra, A. (1993). Power evaluations in structural equation models. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 181-204). Newbury Park, CA: Sage.
11. Saris, W. E., Satorra, A., & Sörbom, D. (1987). The detection and correction of specification errors in structural equation models. In C. C. Clogg (Ed.), Sociological methodology 1987 (pp. 105-129). San Francisco: Jossey-Bass.
12. SAS Institute Inc. (1990). SAS/STAT: Users guide, Version 6 (4th ed., Vol. 2). Cary, NC: Author.
13. Satorra, A., & Saris, W. E. (1985). Power of the likelihood ratio test in covariance structure analysis. Psychometrika, 50, 83-90.
14. Yung, Y.-F., & Bentler, P. M. (1996). Bootstrapping techniques in analysis of mean and covariance structures. In G. A. Marcoulides & R. E. Schumacker (Eds.), Advanced structural equation modeling: Issues and techniques (pp. 195-226). Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
15. Yung, Y.-F., & Chan, W. (1999). Statistical analyses using bootstrapping: Concepts and implementation. In R. H. Hoyle (Ed.), Statistical strategies for small sample research (pp. 81-105). Thousand Oaks, CA: Sage.