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METHODS article
Front. Psychol.
Sec. Quantitative Psychology and Measurement
Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1562305
Corrected Goodness of Fit Index and Alternate Indices in Latent Variable Modeling Using Non-Parametric Bootstrapping
Provisionally accepted- 1 Harvard Medical School, Boston, United States
- 2 King Saud University, Riyadh, Riyadh, Saudi Arabia
Latent Variable Modeling (LVM) is a powerful tool for validating tools and measurements in the social sciences. A central challenge is the evaluation of model fit, traditionally assessed using omnibus inferential statistical criteria, descriptive fit indices and residual statistics all of which are to some extent affected by sample sizes and model complexity. In the present study an R function was created to assess fit indices after employing nonparametric bootstrapping. Furthermore, the newly proposed corrected Goodness of fit index (CGFI) is presented as a means to overcome the above-mentioned limitations. Using data from PISA 2022 and PIRLS 2021 and the measurement of instructional leadership and the construct of bullying results indicated differential decision making using the present function compared to using sample estimates only. It is suggested that the CGFIboot function may provide useful information towards improving our evaluative criteria in LVMs.
Keywords: Structural Equation Modeling, factor analysis, descriptive fit indices, model fit, Small sample sizes, bootstrapping, R function
Received: 17 Jan 2025; Accepted: 03 Mar 2025.
Copyright: © 2025 Sideridis and Alghamdi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Georgios Sideridis, Harvard Medical School, Boston, United States
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