Goodness-of-fit indices for partial least squares path modeling
Computational StatisticsPublished 4 March 2012Open access
Jörg Henseler, Marko Sarstedt
Citations1,774
SJR quartileQ2
SJR score0.75
SNIP1.28
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TL;DR
This paper discusses a recent development in partial least squares (PLS) path modeling, namely goodness-of-fit indices, and estimates PLS path models with simulated data, and contrasts their values with fit indices commonly used in covariance-based structural equation modeling.
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.
Keywords
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