Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/288877 
Year of Publication: 
2020
Citation: 
[Journal:] Journal of Marketing Analytics [ISSN:] 2050-3326 [Volume:] 8 [Issue:] 4 [Publisher:] Palgrave Macmillan UK [Place:] London [Year:] 2020 [Pages:] 189-202
Publisher: 
Palgrave Macmillan UK, London
Abstract: 
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
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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