Dual scaling for the analysis of categorical data.
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.
Maraun
Michael D
MD
Department of Psychology, Simon Fraser University, Canada. maraun@sfu.ca
Slaney
Kathleen
K
Jalava
Jarkko
J
D006801:Humans; D010552:Personality Assessment / Q000706:statistics & numerical data*; D011594:Psychometrics / Q000379:methods*; D014481:United States