title: Dual scaling for the analysis of categorical data.
abstract: Dual scaling is a set of related techniques for the analysis of a wide assortment of categorical data types including contingency tables and multiple-choice, rank order, and paired comparison data. When applied to a contingency table, dual scaling also goes by the name "correspondence analysis," and when applied to multiple-choice data in which there are more than 2 items, "optimal scaling" and "multiple correspondence analysis. " Our aim of this article was to explain in nontechnical terms what dual scaling offers to an analysis of contingency table and multiple-choice data.
authors.affiliation: Department of Psychology, Simon Fraser University, Canada. maraun@sfu.ca
authors.forename: Michael D
authors.initials: MD
authors.lastname: Maraun
authors.forename: Kathleen
authors.initials: K
authors.lastname: Slaney
authors.forename: Jarkko
authors.initials: J
authors.lastname: Jalava
mesh_terms: D006801:Humans; D010552:Personality Assessment / Q000706:statistics & numerical data*; D011594:Psychometrics / Q000379:methods*; D014481:United States