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Cutoff criteria for overall model fit indexes in generalized structured component analysis
Citation Link: https://doi.org/10.15480/882.2916
Publikationstyp
Journal Article
Date Issued
2020-09-20
Sprache
English
TORE-DOI
TORE-URI
Journal
Volume
8
Start Page
189
End Page
202
Citation
Journal of Marketing Analytics 8: 189-202 (2020-09-20)
Publisher DOI
Scopus ID
Publisher
Springer Nature
Generalized structured component analysis (GSCA) is a technically well-established approach to component-based structural equation modeling that allows for specifying and examining the relationships between observed variables and components thereof. GSCA provides overall fit indexes for model evaluation, including the goodness-of-fit index (GFI) and the standardized root mean square residual (SRMR). While these indexes have a solid standing in factor-based structural equation modeling, nothing is known about their performance in GSCA. Addressing this limitation, we present a simulation study’s results, which confirm that both GFI and SRMR indexes distinguish effectively between correct and misspecified models. Based on our findings, we propose rules-of-thumb cutoff criteria for each index in different sample sizes, which researchers could use to assess model fit in practice.
Subjects
Component-based structural equation modeling
Generalized structured component analysis
Model fit
GFI
SRMR
DDC Class
650: Management
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