Detection of interactions between a dichotomous moderator and a continuous predictor in moderated multiple regression with heterogeneous error variance

Behavior Research Methods

Volumn 41, Issue 1, 2009, Pages 61-74

  Shieh, Gwowen ^a  

^a NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMPUTER SIMULATION; HUMAN; INSTRUMENTATION; METHODOLOGY; PSYCHOLOGICAL MODEL; PSYCHOLOGY; REGRESSION ANALYSIS; STATISTICAL ANALYSIS; STATISTICS;

COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; MODELS, PSYCHOLOGICAL; PSYCHOLOGY; REGRESSION ANALYSIS;

EID: 65349131781     PISSN: 1554351X     EISSN: None     Source Type: Journal    
DOI: 10.3758/BRM.41.1.61     Document Type: Article

References (28)

1. Aguinis, H. (2004). Regression analysis for categorical moderators. New York: Guilford.
2. Aguinis, H., Petersen, S. A., & Pierce, C. A. (1999). Appraisal of the homogeneity of error variance assumption and alternatives for multiple regression for estimating moderated effects of categorical variables. Organizational Research Methods, 2, 315-339.
3. Aguinis, H., & Pierce, C. A. (1998). Heterogeneity of error variance and the assessment of moderating effects of categorical variables: A conceptual review. Organizational Research Methods, 1, 296-314.
4. Aguinis, H., & Stone-Romero, E. F. (1997). Methodological artifacts in moderated multiple regression and their effects on statistical power. Journal of Applied Psychology, 82, 192-206.
5. Alexander, R. A., & DeShon, R. P. (1994). The effect of error variance heterogeneity on the power of tests for regression slope differences. Psychological Bulletin, 115, 308-314.
6. Alexander, R. A., & Govern, D. M. (1994). A new and simpler approximation for ANOVA under variance heterogeneity. Journal of Educational Statistics, 19, 91-101.
7. Berenson, M. L., Krehbiel, T. C., & Levine, D. M. (2006). Basic business statistics: Concepts and applications (10th ed.). Upper Saddle River, NJ: Pearson Education.
8. Best, D. J., & Rayner, J. C. W. (1987). Welch's approximate solution for the Behrens-Fisher problem. Technometrics, 29, 205-210.
9. Davenport, J. M., & Webster, J. T. (1975). The Behrens-Fisher problem, an old solution revisited. Metrika, 22, 47-54.
10. DeShon, R. P., & Alexander, R. A. (1994). A generalization of James's second-order approximation to the test for regression slope equality. Educational & Psychological Measurement, 54, 328-335.
11. DeShon, R. P., & Alexander, R. A. (1996). Alternative procedures for testing regression slope homogeneity when group error variances are unequal. Psychological Methods, 1, 261-277.
12. Dretzke, B. J., Levin, J. R., & Serlin, R. C. (1982). Testing for regression homogeneity under variance heterogeneity. Psychological Bulletin, 91, 376-383.
13. Fenstad, G. U. (1983). A comparison between the U and V tests in the Behrens-Fisher problem. Biometrika, 70, 300-302.
14. 2, F and t distributions with applications. Journal of the Royal Statistical Society B, 35, 480-492.
15. Howell, D. C. (2007). Statistical methods for psychology (6th ed.). Pacific Grove, CA: Duxbury.
16. James, G. S. (1951). The comparison of several groups of observations when the ratios of the population variances are unknown. Biometrika, 38, 324-329.
17. Nel, D. G., van der Merwe, C. A., & Moser, B. K. (1990). The exact distribution of the univariate and multivariate Behrens-Fisher statistics with a comparison of several solutions in the univariate case. Communications in Statistics: Theory & Methods, 19, 279-298.
18. Neter, J., Kutner, M. H., Nachtsheim, C. J., & Li, W. (2005). Applied linear statistical models (5th ed.). Chicago: McGraw-Hill/Irwin.
19. Overton, R. C. (2001). Moderated multiple regression for interactions involving categorical variables: A statistical control for heterogeneous variance across two groups. Psychological Methods, 6, 218-233.
20. Paul, S. R., Best, D. J., & Rayner, J. C. W. (1992). Comment on Best and Rayner (1987). Technometrics, 34, 249-250.
21. R Development Core Team (2008). R: A language and environment for statistical computing [Computer software and manual]. Retrieved from www.r-project.org.
22. Rencher, A. C. (2000). Linear models in statistics. New York: Wiley.
23. SAS Institute (2008). SAS/STAT 9.2 user's guide. Cary, NC: SAS Institute Inc.
24. Scariano, S. M., & Davenport, J. M. (1986). A four-moment approach and other practical solutions to the Behrens-Fisher problem. Communications in Statistics: Theory & Methods, 15, 1467-1505.
25. Scheffe ́, H. (1970). Practical solutions of the Behrens-Fisher problem. Journal of the American Statistical Association, 65, 1501-1508.
26. Stone-Romero, E. F., Alliger, G. M., & Aguinis, H. (1994). Type II error problems in the use of moderated multiple regression for the detection of moderating effects of dichotomous variables. Journal of Management, 20, 167-178.
27. Welch, B. L. (1938). The significance of the difference between two means when the population variances are unequal. Biometrika, 29, 350-362.
28. Welch, B. L. (1951). On the comparison of several mean values: An alternative approach. Biometrika, 38, 330-336.