Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/288877 
Erscheinungsjahr: 
2020
Quellenangabe: 
[Journal:] Journal of Marketing Analytics [ISSN:] 2050-3326 [Volume:] 8 [Issue:] 4 [Publisher:] Palgrave Macmillan UK [Place:] London [Year:] 2020 [Pages:] 189-202
Verlag: 
Palgrave Macmillan UK, London
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.
Schlagwörter: 
Component-based structural equation modeling
Generalized structured component analysis
Model fit
GFI
SRMR
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