An INDSCAL-Based Approach to Multiple Correspondence Analysis

Abstract

Current methods of multiple correspondence analysis (MCA) provide configurations that are expressed in terms of principal axes. These solutions are not invariant over rotations. The authors propose an approach to MCA that entails an INDSCAL analysis of normalized Burt matrices (as commonly obtained from MCA). The resulting configuration is uniquely oriented and dimension weights also are obtained for each contributory data set. The method is applied to survey data describing relationships among respondent demographic characteristics and recent car purchases.