Correspondence analysis of an artificial binary cylinder data

Abstract

In applying correspondence analysis to a given data set, there are two ways to deal with it; free-choice type and item-category type (binary data). It is shown that circular data by Iwatsubo (1984) and cylinder data by Okamoto (1994b) presented so far for the free-choice type are solvable analytically for the item-category type too and that score vectors are similar for the both data types.Binary data Circular data Correspondence analysis Cylinder data Free-choice type Guttman effect Item-category type