Peer-reviewed article

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

Cho, G. · Hwang, H. · Sarstedt, M. · Ringle, C. M.

Methodology
Structural Equation Modeling

2020 · Journal of Marketing Analytics · 8, 189–202

Journal DOI: 10.1057/s41270-020-00089-1 Open access

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.

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Cite this work

Cho, G., Hwang, H., Sarstedt, M., Ringle, C. M. (2020). Cutoff criteria for overall model fit indexes in generalized structured component analysis. Journal of Marketing Analytics, 8, 189–202. https://doi.org/10.1057/s41270-020-00089-1