The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Potential problems with "well fitting" models.
Abstract
The assessment of model fit is a more complex and indeterminate process than is commonly acknowledged by researchers who use structural equation modeling (SEM) techniques. Even models that are well fitting according to commonly used statistical tests and descriptive fit indices can have significant problems and ambiguities. The authors discuss 7 potential difficulties that can arise and that should temper researchers' conclusions: equivalent models, nonequivalent but well-fitting alternative models, omitted variables, problematic lower-order model components, the failure to parse composite models into meaningful partitions (e.g., measurement vs. structural), inattention to the multiple factors that affect the sensitivity of measures of fit to model misspecifications, and reliance on specification searches. In addition to providing examples of each of these problems, the authors offer recommendations for psychopathologists who conduct SEM analyses.
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Cites
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Alternative Ways of Assessing Model Fit
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Causality: Models, Reasoning, and Inference
Pearl, J. (2009) · doi:10.1017/cbo9780511803161 · Cited by 11,653
Principles and practice in reporting structural equation analyses.
McDonald, R. P., & Ho, M.-H. R. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.1.64 · Cited by 4,734 · cited 7×
“For example, correlated error terms can denote the omission of important constructs of substantive interest and the existence of meaningful alternative factor structures to those hypothesized (e.g., Gerbing & Anderson, 1984; McDonald & Ho, 2002; see also Figure 2).”
BackgroundMethodInfluentialCausation, Prediction, and Search
Spirtes, P., Glymour, C., & Scheines, R. (2001) · doi:10.7551/mitpress/1754.001.0001 · Cited by 4,521
Cole, D. A., & Maxwell, S. E. (2003) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.112.4.558 · Cited by 3,605
How to Use a Monte Carlo Study to Decide on Sample Size and Determine Power
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On the Meaning of within-Factor Correlated Measurement Errors
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“For example, correlated error terms can denote the omission of important constructs of substantive interest and the existence of meaningful alternative factor structures to those hypothesized (e.g., Gerbing & Anderson, 1984; McDonald & Ho, 2002; see also Figure 2).”
Background
Cited by
Structural Equation Modelling: Guidelines for Determining Model Fit
Hooper, D., Coughlan, J., & Mullen, M. R. (2008) · Dublin Institute of Technology · doi:10.21427/d7cf7r · Cited by 8,746
Cole, D. A., & Maxwell, S. E. (2003) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.112.4.558 · Cited by 3,605
Quinn, D. M., & Chaudoir, S. R. (2009) · Journal of Personality and Social Psychology · doi:10.1037/a0015815 · Cited by 932
Wood, A. M., Maltby, J., Gillett, R., Linley, P. A., & Joseph, S. (2008) · Journal of Research in Personality · doi:10.1016/j.jrp.2007.11.003 · Cited by 761
On the emancipation of PLS-SEM: a commentary on Rigdon (2012)
Sarstedt, M., Ringle, C. M., Henseler, J., & Hair, J. F. (2014) · Long Range Planning · doi:10.1016/j.lrp.2014.02.007 · Cited by 758
Metadata
- Authors
- Tomarken, A. J., & Waller, N. G.
- Venue
- Journal of Abnormal Psychology
- Published
- 2003-11
- Volume
- 112
- Issue
- 4
- Pages
- 578-598
- ISSN
- 0021-843X (ISSN-L)
- 1939-1846
- OpenAlex
- W2084720031
- Cited by
- 393
- References
- 10
- FWCI
- 12.06
- Type
- journal article
- Language
- en
- Open access
- closed
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