Cutoff criteria for overall model fit indexes in generalized structured component analysis

Gyeongcheol Cho (), Heungsun Hwang (), Marko Sarstedt and Christian M. Ringle
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Gyeongcheol Cho: McGill University
Heungsun Hwang: McGill University
Marko Sarstedt: Otto-Von-Guericke-University Magdeburg
Christian M. Ringle: Hamburg University of Technology

Journal of Marketing Analytics, 2020, vol. 8, issue 4, No 2, 189-202

Abstract: 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.

Keywords: Component-based structural equation modeling; Generalized structured component analysis; Model fit; GFI; SRMR (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (17)

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DOI: 10.1057/s41270-020-00089-1

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