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.
Item Type: | Journal article |
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Form of publication: | Publisher's Version |
Keywords: | Generalized structured component analysis (GSCA) |
Faculties: | Munich School of Management > Institute for Marketing |
Subjects: | 300 Social sciences > 330 Economics |
URN: | urn:nbn:de:bvb:19-epub-96069-1 |
ISSN: | 2050-3318 |
Language: | English |
Item ID: | 96069 |
Date Deposited: | 03. May 2023, 07:48 |
Last Modified: | 03. May 2023, 07:48 |