Abstract
The aim of this study was to demonstrate how personality test data can be plotted with a multivariate method known as Partial Least Squares of Latent Structures (PLS). The basic methodology behind PLS modeling is presented and the example demonstrates how a PLS model of personality test data can be used for diagnostic prediction. Principles for validating the models are also presented. The conclusion is that PLS modeling appears to be a powerful method for extracting clinically relevant information from complex personality test data matrixes. It could be used as a complement to more hard modeling methods in the process of examining a new area of interest.
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