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

Jörg Henseler, Marko Sarstedt

Computational Statistics · 2012 · 1.8K citations · 30 references

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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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