Abstract
Partial Least Squares (PLS) is a statistical technique that is widely used in the Information Systems discipline to estimate statistical models with structural equations and latent variables. While PLS does not provide a statistical test of model fit to data, its proponents have suggested a set of criteria that good PLS models should fulfill. Conversely, when a model does not satisfy these criteria, it would be judged a bad model. In this paper, we report on the results of a simulation study to examine to what extent the proposed model quality criteria are able to identify misspecified models.
Recommended Citation
Evermann, Joerg and Tate, Mary, "Testing Models or Fitting Models? Identifying Model Misspecification in PLS" (2010). ICIS 2010 Proceedings. 21.
https://aisel.aisnet.org/icis2010_submissions/21