APA
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Greene, A., Eaton, N., Forbes, M., Fried, E., Watts, A. L., Kotov, R., & Krueger, R. (2022). Model fit is a fallible indicator of model quality in quantitative psychopathology research: A reply to Bader and Moshagen. Journal of Psychopathology and Clinical Science, 131(6), 696–703. https://doi.org/10.1037/abn0000770
Chicago/Turabian
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Greene, A., N. Eaton, M. Forbes, E. Fried, A. L. Watts, R. Kotov, and R. Krueger. “Model Fit Is a Fallible Indicator of Model Quality in Quantitative Psychopathology Research: A Reply to Bader and Moshagen.” Journal of Psychopathology and Clinical Science 131, no. 6 (2022): 696–703.
MLA
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Greene, A., et al. “Model Fit Is a Fallible Indicator of Model Quality in Quantitative Psychopathology Research: A Reply to Bader and Moshagen.” Journal of Psychopathology and Clinical Science, vol. 131, no. 6, 2022, pp. 696–703, doi:10.1037/abn0000770.
BibTeX Click to copy
@article{a2022a,
title = {Model fit is a fallible indicator of model quality in quantitative psychopathology research: A reply to Bader and Moshagen.},
year = {2022},
issue = {6},
journal = {Journal of Psychopathology and Clinical Science},
pages = {696–703},
volume = {131},
doi = {10.1037/abn0000770},
author = {Greene, A. and Eaton, N. and Forbes, M. and Fried, E. and Watts, A. L. and Kotov, R. and Krueger, R.}
}
As evidenced by our exchange with Bader and Moshagen (2022), the degree to which model fit indices can and should be used for the purpose of model selection remains a contentious topic. Here, we make three core points. First, we discuss the common misconception about fit statistics' abilities to identify the "best model," arguing that mechanical application of model fit indices contributes to faulty inferences in the field of quantitative psychopathology. We illustrate the consequences of this practice through examples in the literature. Second, we highlight the parsimony-adjacent concept of fitting propensity, which is not accounted for by commonly used fit statistics. Finally, we present specific strategies to overcome interpretative bias and increase generalizability of study results and stress the importance of carefully balancing substantive and statistical criteria in model selection scenarios. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
