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

Author

Listed:
  • Gyeongcheol Cho

    (McGill University)

  • Heungsun Hwang

    (McGill University)

  • Marko Sarstedt

    (Otto-Von-Guericke-University Magdeburg
    Monash University Malaysia)

  • Christian M. Ringle

    (Hamburg University of Technology
    University of Waikato)

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.

Suggested Citation

  • Gyeongcheol Cho & Heungsun Hwang & Marko Sarstedt & Christian M. Ringle, 2020. "Cutoff criteria for overall model fit indexes in generalized structured component analysis," Journal of Marketing Analytics, Palgrave Macmillan, vol. 8(4), pages 189-202, December.
    • Handle: RePEc:pal:jmarka:v:8:y:2020:i:4:d:10.1057_s41270-020-00089-1
    DOI: 10.1057/s41270-020-00089-1
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