Computational Statistics· 2012Q2
Goodness-of-fit indices for partial least squares path modeling
- 1,779citations
- Q2SCImago
- 2012year
Short summary
The goodness-of-fit (GoF) and relative goodness-of-fit (GoF rel) indices are not suitable for validating Partial Least Squares (PLS) path models, according to a simulation study.
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Key points
- GoF and GoF rel indices are not suitable for validating PLS path models.
- Simulation data was used to estimate PLS path models and compare GoF indices with covariance-based fit indices.
- GoF can be used to evaluate how well a PLS model explains different datasets.
AI-generated from the title and abstract; the full text is not read.
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.
The authors' abstract, as published at the source. Computational Statistics, 2012 · DOI ↗
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Field: Management Science and Operations Research
Management Science and Operations ResearchDecision Sciences