title: PLS model building: a multivariate approach to personality test data.
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.
authors.affiliation: Department of Psychology, Umeå University, Sweden. mikael.henningsson@psy.umu.se
authors.forename: M
authors.initials: M
authors.lastname: Henningsson
authors.forename: E
authors.initials: E
authors.lastname: Sundbom
authors.forename: B A
authors.initials: BA
authors.lastname: Armelius
authors.forename: P
authors.initials: P
authors.lastname: Erdberg
mesh_terms: D006801:Humans; D016018:Least-Squares Analysis; D015233:Models, Statistical; D015999:Multivariate Analysis; D010556:Personality Tests / Q000706:statistics & numerical data*