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

2012-03-04articleComputational Statistics1,852 citationshybrid

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Psychometric Methodologies and Testing Statistical Methods and Applications Advanced Statistical Methods and Models

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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