The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Simulation Study on Fit Indexes in CFA Based on Data With Slightly Distorted Simple Structure
Abstract
Fit indexes were compared with respect to a specific type of model misspecification. Simple structure was violated with some secondary loadings that were present in the true models that were not specified in the estimated models. The c2 test, Comparative Fit Index, Goodness-of-Fit Index, Incremental Fit Index, Nonnormed Fit Index, root mean squared error of approximation, standardized root mean square residual, and the c2/df values were investigated. Simulated data sets with 3 sample sizes (250, 500, and 1,000 cases), 4 levels of main loadings (.40,. 50,. 60, and. 80), 2 numbers of factors (4, 8), and 2 types of association matrix (covariance, correlation) were the basis for maximum likelihood estimation of orthogonal and oblique factor models. Some correlations between fit indexes were low. Moreover, small distortions from simple structure did not lead to misfit in the RMSEA and SRMR, but they often led to misfit in the incremental fit indexes. This result may be of interest for research on personality traits, where small violations of simple structure are very common.
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Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
Structural Equations with Latent Variables.
Clogg, C. C., & Bollen, K. A. (1991) · Contemporary Sociology · doi:10.2307/2072165 · Cited by 17,442
Structural Equations with Latent Variables
Bollen, K. A. (1989) · Wiley series in probability and statistics · doi:10.1002/9781118619179 · Cited by 17,277
The Art of Computer Programming
Knuth, D. E. (1968) · Cited by 15,999
Hu, L.-T., & Bentler, P. M. (1998) · Psychological Methods · doi:10.1037/1082-989x.3.4.424 · Cited by 12,298
Journal of personality and social psychology
Armstrong, J. S. (1988) · International Journal of Forecasting · doi:10.1016/0169-2070(88)90126-4 · Cited by 10,485
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003) · Department of Psychology - University of Koblenz-Landau · doi:10.23668/psycharchives.12784 · Cited by 8,975
Testing Structural Equation Models.
Clogg, C. C., Bollen, K. A., & Long, J. S. (1995) · Social Forces · doi:10.2307/2580595 · Cited by 8,211
An alternative "description of personality": The Big-Five factor structure.
Goldberg, L. R. (1990) · Journal of Personality and Social Psychology · doi:10.1037//0022-3514.59.6.1216 · Cited by 6,652
Validation of the five-factor model of personality across instruments and observers.
McCrae, R. R., & Costa, P. T. (1987) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.52.1.81 · Cited by 6,404
Cited by
Structural equation modelling: Adjudging model fit
Barrett, P. (2007) · Personality and Individual Differences · doi:10.1016/j.paid.2006.09.018 · Cited by 2,611
Dumont, J., Shen, J., & Deng, X. (2017) · Human Resource Management · doi:10.1002/hrm.21792 · Cited by 1,535
Clarifying conditions and decision points for mediational type inferences in Organizational Behavior
Mathieu, J. E., & Taylor, S. R. (2006) · Journal of Organizational Behavior · doi:10.1002/job.406 · Cited by 961
Heene, M., Hilbert, S., Draxler, C., Ziegler, M., & Bühner, M. (2011) · Psychological Methods · doi:10.1037/a0024917 · Cited by 406
The Thorny Relation Between Measurement Quality and Fit Index Cutoffs in Latent Variable Models
McNeish, D., An, J., & Hancock, G. R. (2018) · Journal of Personality Assessment · doi:10.1080/00223891.2017.1281286 · Cited by 398
Metadata
- Authors
- Beauducel, A., & Wittmann, W. W.
- Venue
- Structural Equation Modeling: A Multidisciplinary Journal
- Publisher
- Informa UK Limited
- Published
- 2005-01
- Volume
- 12
- Issue
- 1
- Pages
- 41-75
- ISSN
- 1070-5511 (ISSN-L)
- 1532-8007
- OpenAlex
- W1971223956
- Cited by
- 591
- References
- 33
- FWCI
- 28.77
- Type
- journal article
- Language
- en
- Open access
- closed
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- Beauducel, A., & Wittmann, W. W. (2005). Simulation Study on Fit Indexes in CFA Based on Data With Slightly Distorted Simple Structure. Structural Equation Modeling: A Multidisciplinary Journal. https://doi.org/10.1207/s15328007sem1201_3
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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