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Correspondence Analysis in Practice, Second Edition

• By Michael Greenacre

• Price: $83.95
• Binding: Hardback
• Pages: 296
• Published by: Chapman and Hall
• Publication Date: 7th May 2007
• ISBN: 978-1-58488-616-7

About the Book

Drawing on the author’s experience in social and environmental research, Correspondence Analysis in Practice, Second Edition shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide variety of situations. This completely revised, up-to-date edition features a didactic approach with self-contained chapters, extensive marginal notes, informative figure and table captions, and end-of-chapter summaries. 

New to the Second Edition

• Five new chapters on transition and regression relationships, stacked tables, subset correspondence analysis, analysis of square tables, and canonical correspondence analysis

• Substantially more figures and tables than the first edition

• A computational appendix that provides the R commands that correspond to most of the analyses featured throughout the book, making it easy for readers to reproduce the analyses

With 33 years of CA experience, the expert author demonstrates how to use uncomplicated, relatively nonmathematical techniques to translate complex tabular data into more readable graphical forms. CA and its variants multiple CA (MCA) and joint CA (JCA) are suitable for analyses in various fields, including marketing research, the social and environmental sciences, biochemistry, and more.

Table of Contents

Preface. Scatterplots and Maps. Profiles and the Profile Space. Masses and Centroids. Chi-Square Distance and Inertia. Plotting Chi-Square Distances. Reduction of Dimensionality. Optimal Scaling.
Symmetry of Row and Column Analyses. Two-Dimensional Maps. Three More Examples. Contributions to Inertia. Supplementary Points. Correspondence Analysis Biplots. Transition and Regression Relationships. Clustering Rows and Columns. Multiway Tables. Stacked Tables. Multiple Correspondence Analysis. Joint Correspondence Analysis. Scaling Properties of MCA. Subset Correspondence Analysis. Analysis of Square Tables. Data Recoding. Canonical Correspondence Analysis. Aspects of Stability and Inference. Appendices. Index.