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Goodness-of-fit indices for partial least squares path modeling

Open access
Henseler, Jörg, Sarstedt, Marko·2013·Computational Statistics
DOI 10.1007/s00180-012-0317-1
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Abstract

This paper discusses a recent development in partial least squares (PLS) path modeling, namely goodness-of-fit indices. In order to illustrate the behavior of the goodness-of-fit index (GoF) and the relative goodness-of-fit index (GoF rel ), we estimate PLS path models with simulated data, and contrast their values with fit indices commonly used in covariance-based structural equation modeling. The simulation shows that the GoF and the GoF rel are not suitable for model validation. However, the GoF can be useful to assess how well a PLS path model can explain different sets of data.

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Metadata

Authors
Henseler, J., & Sarstedt, M.
Venue
Computational Statistics
Publisher
Springer Science and Business Media LLC
Published
2012-03-04
Volume
28
Issue
2
Pages
565-580
ISSN
  • 0943-4062 (ISSN-L)
  • 1613-9658
DOI
10.1007/s00180-012-0317-1
OpenAlex
W2108401663
Cited by
1,842
References
13
FWCI
38.20
Type
journal article
Language
en
Open access
hybrid

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Henseler, J., & Sarstedt, M. (2013). Goodness-of-fit indices for partial least squares path modeling. Computational Statistics. https://doi.org/10.1007/s00180-012-0317-1

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