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The Devil is Mainly in the Nuisance Parameters: Performance of Structural Fit Indices Under Misspecified Structural Models in SEM
| Content Provider | PsyArXiv |
|---|---|
| Author | Heene, Moritz Maraun, Michael Glushko, Nadine J. Pornprasertmanit, Sunthud |
| Abstract | To provide researchers with a means of assessing the fit of the structural component of structural equation models, structural fit indices- modifications of the composite fit indices, RMSEA, SRMR, and CFI- have recently been developed. We investigated the performance of four of these structural fit indices- RMSEA-P, RMSEA_S, SRMR_S, and CFI_S-, when paired with widely accepted cutoff values, in the service of detecting structural misspecification. In particular, by way of simulation study, for each of seven fit indices- 3 composite and 4 structural-, and the traditional chi-square test of perfect composite fit, we estimated the following rates: a) Type I error rate (i.e., the probability of (incorrect) rejection of a correctly specified structural component), under each of four degrees of misspecification in the measurement component; and b) Power (i.e., the probability of (correct) rejection of an incorrectly specified structural model), under each condition formed of the pairing of one of three degrees of structural misspecification with one of four degrees of measurement component misspecification. In addition to sample size, the impacts of two model features, incidental to model misspecification- number of manifest variables per latent variable and magnitude of factor loading- were investigated. The results suggested that, although the structural fit indices performed relatively better than the composite fit indices, none of the goodness-of-fit index with a fixed cutoff value pairings was capable of delivering an entirely satisfactory Type I error rate/Power balance, [RMSEA_S,.05] failing entirely in this regard. Of the remaining pairings; a) RMSEA-P and CFI_S suffered from a severely inflated Type I error rate; b) despite the fact that they were designed to pick up on structural features of candidate models, all pairings- and especially, RMSEA-P and CFI_S- manifested sensitivities to model features, incidental to structural misspecification; and c) although, in the main, behaving in a sensible fashion, SRMR_S was only sensitive to structural misspecification when it occurred at a relatively high degree. |
| DOI | 10.31234/osf.io/d8tuy |
| Language | English |
| Publisher Date | 2021-01-09 |
| Access Restriction | Open |
| Rights License | CC-By Attribution 4.0 International |
| Subject Keyword | Social and Behavioral Sciences;Quantitative Methods;Psychometrics;Statistical Methods Cutoff Values Fit Indices Goodness-of-fit Model Fit Model Misfit Model Test Sem Structural Equation Modeling Theory Testing |
| Content Type | Text |
| Resource Type | Preprint |
| Subject | Social Sciences Mathematics Psychiatry and Mental Health Psychology |
