Cutoff criteria for overall model fit indexes in generalized structured component analysis
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 evalua...
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Veröffentlicht in: | Journal of marketing analytics 2020-12, Vol.8 (4), p.189-202 |
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Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 2050-3326 2050-3318 2050-3326 |
DOI: | 10.1057/s41270-020-00089-1 |