Equality Constraints in Multiple Correspondence Analysis

Equality Constraints in Multiple Correspondence Analysis.

The application of equality constraints on the categories of a variable is a simple but useful extension of multiple correspondence analysis. Equality can be used to incorporate prior knowledge about the relations between categories. Categories may belong to the same variable, to different variables, or both. The simplest form of equality specifies that all variables receive identical data tran...

Equality Constraints in Multiple Correspondence Analysis

The Choice of Constraints in Correspondence Analysis

The range of techniques variously known as optimal scaling, dual scaling, or multiple correspondence analysis, have been widely applied in a number of contexts including test item scoring and estimation of bone maturity. Nishisato (1980) and Greenacre (t984) present accounts and McDonald (1983) has contributed further results. De Leeuw (1984) describes various extensions known as the Girl syste...

Discriminant multiple correspondence analysis

The proposed approach leads to analyzing the associations between a set of quantitative variables and several qualitative variables measured on a same set of individuals. In a decision-making context, the proposed method can be considered as a generalization of discriminant analysis to the multiple groups’ variables case. It’s described as a principal component analysis of the centres of gravit...

Multiple Correspondence Analysis

Multiple correspondence analysis (MCA) is an extension of correspondence analysis (CA) which allows one to analyze the pattern of relationships of several categorical dependent variables. As such, it can also be seen as a generalization of principal component analysis when the variables to be analyzed are categorical instead of quantitative. Because MCA has been (re)discovered many times, equiv...