Assessing goodness of fit: Simple rules of thumb simply do not work

Organizational Research Methods

Volumn 14, Issue 3, 2011, Pages 548-570

  Nye, Christopher D ^a   Drasgow, Fritz ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

confirmatory factor analysis; fit indices; model fit

Indexed keywords

EID: 79957817035     PISSN: 10944281     EISSN: 15527425     Source Type: Journal    
DOI: 10.1177/1094428110368562     Document Type: Article

References (64)

1. Anderson, J.C., & Gerbing, D.W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411-423.
2. Bandalos, D.L. (2006). The use of Monte Carlo studies in structural equation modeling research. In G. R. Hancock & R. D. Mueller (Eds.), Structural equation modeling: A second course (pp. 269-314). Greenwich, CT: Information Age Publishing.
3. Barrett, P. (2007). Structural equation modeling: Adjudging model fit. Personality and Individual Differences, 42, 815-824.
4. Bennett, R.J., & Robinson, S.L. (2000). Development of a measure of workplace deviance. Journal of Applied Psychology, 85, 349-360.
5. Bentler, P.M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238-246.
6. Bollen, K.A. (1989). Structural equations with latent variables. New York, NY: Wiley.
7. Byrne, B.M. (1998). Structural equation modeling in LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. Mahwah, NJ: Erlbaum.
8. Chau, S.L., Dahling, J.J., Levy, P.E., & Diefendorff, J.M. (2009). A predictive study of emotional labor and turnover. Journal of Organizational Behavior, 30, 1151-1163. doi: 10.1002/job.617.
9. Chen, F., Curran, P.J., Bollen, K.A., Kirby, J., & Paxton, P. (2008). An empirical evaluation of the use of fixed cutoff points in RMSEA test statistic in structural equation models. Sociological Research Methods, 36, 462-494.
10. Chou, C.-P., & Bentler, P.M. (1995). Estimation and tests in structural equation modeling. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and application (pp. 37-55). Thousand Oaks, CA: Sage.
11. Cortina, L.M., & Magley, V.J. (2003). Raising voice, risking retaliation: Events following interpersonal mistreatment in the workplace. Journal of Occupational Health Psychology, 8, 247-265.
12. Cortina, L.M., Magley, V.J., Williams, J.H., & Langhout, R.D. (2001). Incivility in the workplace: Incidence and impact. Journal of Occupational Health Psychology, 6, 64-80.
13. Culbertson, A., & Rodgers, W. (1997). Improving managerial effectiveness in the workplace: The case of sexual harassment of Navy women. Journal of Applied Social Psychology, 27, 1953-1971.
14. DeCoster, J., Iselin, A.-M.R., & Gallucci, M. (2009). A conceptual and empirical examination of justifications for dichotomization. Psychological Methods, 14, 349-366.
15. DiStefano, C. (2002). The impact of categorization with confirmatory factor analysis. Structural Equation Modeling, 9, 327-346.
16. 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 and Statistical Psychology, 47, 309-326.
17. Einarsen, S., Hoel, H., & Notelaers, G. (2009). Measuring exposure to bullying and harassment at work: Validity, factor structure, and psychometric properties of the Negative Acts Questionnaire-Revised. Work and Stress, 23, 24-44.
18. Fan, X., & Sivo, S.A. (2005). Sensitivity of fit indexes to misspecified structural or measurement model components: Rationale of two-index strategy revisited. Structural Equation Modeling, 12, 343-367.
19. Fan, X., & Sivo, S.A. (2007). Sensitivity of fit indices to model misspecification and model types. Multivariate Behavioral Research, 42, 509-529.
20. Finney, S.J., & DiStefano, C. (2006). Non-normal and categorical data in structural equation modeling. In G. R. Hancock & R. D. Mueller (Eds.), Structural equation modeling: A second course (pp. 269-314). Greenwich, CT: Information Age Publishing.
21. Fitzgerald, L.F., Magley, V.J., Drasgow, F., & Waldo, C.R. (1999). Measuring sexual harassment in the military: The sexual experiences questionnaire (SEQ-DoD). Military Psychology, 11, 329-343.
22. Fleishman, A.I. (1978). A method for simulating nonnormal distributions. Psychometrika, 43, 521-532.
23. 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.
24. Gelfand, M.J., Fitzgerald, L.F., & Drasgow, F. (1995). The structure of sexual harassment: A confirmatory factor analysis across cultures and settings. Journal of Vocational Behavior, 47, 164-177.
25. Glomb, T.M., & Liao, H. (2003). Interpersonal aggression in work groups: Social influence, reciprocal, and individual effects. Academy of Management Journal, 46, 486-496.
26. Harwell, M.R., Stone, C.A., Hsu, T.-C., & Kirisci, L. (1996). Monte Carlo studies in Item Response Theory. Applied Psychological Measurement, 20, 101-125.
27. Hoogland, J.J., & Boomsma, A. (1998). Robustness studies in covariance structure modeling: An overview and a meta-analysis. Sociological Methods & Research, 26, 329-367.
28. Hu, L., & Bentler, P.M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3, 424-453.
29. Hu, L., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 3, 424-453.
30. Hu, L., Bentler, P.M., & Kano, Y. (1992). Can test statistics in covariance structure analysis be trusted? Psychological Bulletin, 112, 351-362.
31. Hulin, C.L. (1991). Adaptation, persistence, and commitment in organizations. In M. D. Dunnette & L. M. Hough (Eds.), Handbook of industrial and organizational psychology (Vol. 2, pp. 446-505)). Palo Alto, CA: Consulting Psychologists Press.
32. Hutchinson, S.R., & Olmos, A. (1998). Behavior of descriptive fit indexes in confirmatory factor analysis using ordered categorical data. Structural Equations Modeling, 5, 344-364.
33. Jaros, S.J., Jermier, J.M., Koehler, J.W., & Sincich, T. (1993). Effects of continuance, affective, and moral commitment on the withdrawal process: An evaluation of eight structural equation models. Academy of Management Journal, 36, 951-995.
34. Jöreskog, K., & Sörbom, D. (1996). User's reference guide. Chicago, IL: Scientific Software International.
35. Kendall, M.G., & Stuart, A. (1961). The advanced theory of statistics (Vols. 2and3). Oxford, NY: Hafner.
36. Kline, R.B. (2005). Principles and practices of structural equation modeling. New York, NY: Guilford Press.
37. La Du, T.J., & Tanaka, J.S. (1995). Incremental fit indexes for nested structural equation models. Multivariate Behavioral Research, 30, 289-316.
38. Lei, M., & Lomax, R.G. (2005). The effects of varying degrees of nonnormality in structural equation modeling. Structural Equation Modeling, 12, 1-27.
39. Lim, S., Cortina, L.M., & Magley, V.J. (2008). Personal and workgroup incivility: Impact on work and health outcomes. Journal of Applied Psychology, 93, 95-107.
40. Lord, F.M., & Novick, M.R. (1968). Statistical theories of mental test scores. Greenwich, CT: Information Age Publishing.
41. MacCallum, R.C., Zhang, S., Preacher, K.J., & Rucker, D.D. (2002). On the practice of dichotomization of quantitative variables. Psychological Methods, 7, 19-40.
42. Marsh, H.W., & Grayson, D. (1995). Latent variable models of multitrait-multimethod data. In R. H. Hoyle (Ed.), Structural equation modeling: Issues, concepts, and applications (pp. 56-75). Newbury Park, CA: Sage.
43. Marsh, H.W., Hau, K.-T., & Wen, Z. (2004). In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler's (1999) findings. Structural Equation Modeling, 11, 320-341.
44. Maydeu-Olivares, A., & Böckenholt, U. (2005). Structural equation modeling of paired-comparison and ranking data. Psychological Methods, 10, 285-304.
45. McIntyre, R.M., Bartle, S.A., Landis, D., & Dansby, M.R. (2002). The effects of equal opportunity fairness attitudes on job satisfaction, organizational commitment, and perceived work group efficacy. Military Psychology, 14, 299-319.
46. Micceri, T. (1989). The unicorn, the normal curve, and other improbable creatures. Psychological Bulletin, 105, 156-166.
47. Mitchell, M.S., & Ambrose, M.L. (2007). Abusive supervision and workplace deviance and the moderating effects of negative reciprocity beliefs. Journal of Applied Psychology, 92, 1159-1168.
48. Muthén, B.O. (1993). Goodness of fit with categorical and other non-normal variables. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 205-234). Newbury Park, CA: Sage.
49. Muthén, B.O., & Satorra, A. (1995). Technical aspects of Muthén's LISCOMP approach to estimation of latent variable relations with a comprehensive measurement model. Psychometrika, 60, 489-503.
50. Muthén, L.K., & Muthén, B.O. (1998). Mplus user's guide. Los Angeles, CA: Author.
51. Ormerod, A.J., Lawson, A.K., Sims, C.S., Lytell, M.C., Wadlington, P.L., Yaeger, D., Cohorn, C.A. (2003). 2002 Status of the armed forces survey-workplace and gender relations: Report on Scales and Measures (DMDC Rep. No. 2002-031). Champaign: University of Illinois, Work Experiences Lab.
52. Potthast, M.J. (1993). Confirmatory factor analysis of ordered categorical variables with large models. British Journal of Mathematical and Statistical Psychology, 46, 273-286.
53. Powell, D.A., & Schafer, W.D. (2001). The robustness of the likelihood ratio chi-square test for structural equation models: A meta-analysis. Journal of Educational and Behavioral Statistics, 26, 105-132.
54. Rigdon, E.E., & Ferguson, C.E. (1991). The performance of the polychoric correlation coefficient and selected fitting functions in confirmatory factor analysis with ordinal data. Journal of Marketing Research, 28, 491-497.
55. Satterthwaite, F.E. (1941). Synthesis of variance. Psychometrika, 6, 309-316.
56. Sattora, A., & Bentler, P.M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for developmental research (pp. 399-419). Thousand Oaks, CA: Sage.
57. Schermelleh-Engel, K., Moosbrugger, H., & Muller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research, 8, 23-74.
58. Schumacker, R.E., & Lomax, R.G. (2004). A beginner's guide to structural equation modeling. Mahwah, NJ: Erlbaum.
59. Tepper, B.J. (2000). Consequences of abusive supervision. Academy of Management Journal, 43, 178-190.
60. Vandenberg, R.J., Self, R.M., & Seo, J.H. (1994). A critical examination of the internalization, identification, and compliance commitment measures. Journal of Management, 20, 123-140.
61. Vandenberghe, C., Bentein, K., & Stinglhamber, F. (2004). Affective commitment to the organization, supervisor, and work group: Antecedents and outcomes. Journal of Vocational Behavior, 64, 47-71.
62. Vernon, T., & Eysenck, S. (Eds.). (2007). Special issue on structural equation modeling [Special issue]. Personality and Individual Differences, 42, 811-898.
63. West, S.G., Finch, J.F., & Curran, P.J. (1995). Structural equation models with nonnormal variables: Problems and remedies. In R. H. Hoyle (Ed.), Structural equation modeling: Issues, concepts, and applications (pp. 56-75). Newbury Park, CA: Sage.
64. Yuan, K. (2005). Fit indices versus test statistics. Multivariate Behavioral Research, 40, 115-148.