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Cited by 148Psychometric Methodologies and TestingMental Health Research TopicsAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes

Are fit indices used to test psychopathology structure biased? A simulation study

Greene, Ashley L., Eaton, Nicholas R., Li, Kaiqiao, Forbes, Miriam K., Krueger, Robert F., Markon, Kristian E., Waldman, Irwin D., Cicero, David C. +11 more·2019·Journal of Abnormal Psychology
DOI 10.1037/abn0000434
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Abstract

Structural models of psychopathology provide dimensional alternatives to traditional categorical classification systems. Competing models, such as the bifactor and correlated factors models, are typically compared via statistical indices to assess how well each model fits the same data. However, simulation studies have found evidence for probifactor fit index bias in several psychological research domains. The present study sought to extend this research to models of psychopathology, wherein the bifactor model has received much attention, but its susceptibility to bias is not well characterized. We used Monte Carlo simulations to examine how various model misspecifications produced fit index bias for 2 commonly used estimators, WLSMV and MLR. We simulated binary indicators to represent psychiatric diagnoses and positively skewed continuous indicators to represent symptom counts. Across combinations of estimators, indicator distributions, and misspecifications, complex patterns of bias emerged, with fit indices more often than not failing to correctly identify the correlated factors model as the data-generating model. No fit index emerged as reliably unbiased across all misspecification scenarios. Although, tests of model equivalence indicated that in one instance fit indices were not biased-they favored the bifactor model, albeit not unfairly. Overall, results suggest that comparisons of bifactor models to alternatives using fit indices may be misleading and call into question the evidentiary meaning of previous studies that identified the bifactor model as superior based on fit. We highlight the importance of comparing models based on substantive interpretability and their utility for addressing study aims, the methodological significance of model equivalence, as well as the need for implementation of statistical metrics that evaluate model quality. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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  • Simulations show that bifactor models tend to be robust to misspecified factors and therefore always have fits superior to those of correlated factor models.

    “Simulations show that bifactor models tend to be robust to misspecified factors (57) and, therefore, always have fits superior to those of correlated factor models.”

    From Methods and challenges for assessing heterogeneity (2020) · cites this paper as [57]

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Authors
Greene, A. L., Eaton, N. R., Li, K., Forbes, M. K., Krueger, R. F., Markon, K. E., Waldman, I. D., Cicero, D. C., Conway, C. C., Docherty, A. R., Fried, E. I., Ivanova, M. Y., Jonas, K. G., Latzman, R. D., Patrick, C. J., Reininghaus, U., Tackett, J. L., Wright, A. G. C., & Kotov, R.
ORCID
Venue
Journal of Abnormal Psychology
Publisher
American Psychological Association (APA)
Published
2019-10
Volume
128
Issue
7
Pages
740-764
ISSN
  • 0021-843X (ISSN-L)
  • 1939-1846
DOI
10.1037/abn0000434
OpenAlex
W2942565475
Cited by
148
References
138
Citations by year
2026: 5 · 2025: 15 · 2024: 15 · 2023: 29 · 2022: 18 · 2021: 27 · 2020: 36 · 2019: 3
FWCI
15.03
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Abnormal Psychology (publishedVersion)
  • PubMed (publishedVersion)
  • Research Publications (Maastricht University) (publishedVersion)
  • OSF Preprints (OSF Preprints) (submittedVersion)
  • Research Publications (Maastricht University) (submittedVersion)
Funders
National Institute of Mental Health (K01MH109765)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Keywords
model fit indices, model misspecification, bifactor model, model equivalence, binary indicators, symptom count, dimensional models of psychopathology, model comparison
MeSH terms
Mental Disorders, Computer Simulation, Humans, Models, Psychological

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