Chapter 5. Correspondence analysis

Correspondence analysis provides visualizations of associations in a two-way contingency table in a small number of dimensions. Multiple correspondence analysis extends this technique to n-way tables. Other grahical methods, including mosaic matrices and biplots provide complementary views of loglinear models for two-way and n-way contingency tables.
5.1. Simple correspondence analysis
5.1.1. Notation and terminology
5.1.2. Geometric and statistical properties
5.1.3. The CORRESP Procedure
5.1.4. The CORRESP macro
5.1.5. Quasi-independence and structural zeros
5.2. Properties of category scores
5.2.1. Optimal category scores
5.2.2. Simultaneous linear regressions
5.3. Multi-way tables
5.3.1. Marginal tables and supplementary variables
5.4. Multiple correspondence analysis
5.4.1. Bivariate MCA
5.4.2. The Burt matrix
5.4.3. Multivariate MCA
5.5. Extended MCA: Showing interactions in 2Q tables
5.6. Biplots for contingency tables
5.6.1. Biplots for two-way tables
5.6.2. Biplots for three-way tables
5.7. Chapter summary