© 2007 – Chapman and Hall/CRC
296 pages | 88 B/W Illus.
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.
"…this book is pleasant to read, accessible, and easy to digest. … the book provides the reader with all he or she needs for a proper use of CA and its main extensions. There is enough theory for a valid interpretation of the analysis, in particular what can and what cannot be read on a map. Learning is easy thanks to the pleasant style of the author, the choice of the various illustrative examples, and the appropriate format of the presentation. The book can be read at different levels depending on the reader’s background in mathematics. Therefore, it will be useful to a large number of users, researchers and professionals in all branches, especially in human sciences, ecology, linguistic, etc. It will also be of great interest for students in statistics and, of course, for teachers. I highly recommend this volume to a very wide readership."
—Computational Statistics & Data Analysis, Vol. 53, 2009
“…a brilliant book written by an experienced writer. It’s the second edition, quite completely rewritten and reorganized. …a smooth book to read. …this kind of insight is something that practically every book could have. I would truly recommend this book for everyone who is interested in analyzing and visualizing categorical data…will surely find lots of use for this book.”
—Kimmo Vehkalahti, University of Helsinki, Finland, International Statistical Review, 2008
"This is a nice book for all those who wish to acquaint themselves with the versatile methodology of correspondence analysis and the way it can be used for the analysis and visualization of data arriving typically from fields of social, environmental, and health sciences, marketing, and economics. Numerous examples provide a real flavour of the possibilities of the method."
"This second edition goes beyond the first by providing a very comprehensive account of correspondence analysis for visualizing categorical data . . . succeeds in introducing the method to a wider audience . . . provides a full picture about correspondence analysis, its extensions, as well as a series of applications where the method can be proven very useful . . . nicely written and I believe that its style introduces a totally novel approach for writing scientific books. This writer, a well-experienced researcher, makes complicated things seem easy and easily understood . . . I really enjoyed reading this book . . . I would recommend this book for everyone who works with categorical data and at least one time faced the problem of visualizing such data, especially those interested in correspondence analysis techniques will surely use this book as their standard reference."
– Dimitris Karlis, Athens University of Economics, Psychometrika, March 2009, Vol. 74, No. 1
"This second edition of this practice-oriented introduction is completely revised; it is an up-to-date version, with a large number of marginal notes, informative figures and tables, and also end-of-chapter summaries."
– Jörg Blasius, University of Bonn, Journal of the American Statistical Association, June 2009, Vol. 104, No. 486
Preface Scatterplots and Maps
Profiles and the Profile Space
Masses and Centroids
Chi-Square Distance and Inertia
Plotting Chi-Square Distances
Reduction of Dimensionality
Symmetry of Row and Column Analyses
Three More Examples
Contributions to Inertia
Correspondence Analysis Biplots
Transition and Regression Relationships
Clustering Rows and Columns
Multiple Correspondence Analysis
Joint Correspondence Analysis
Scaling Properties of MCA
Subset Correspondence Analysis
Analysis of Square Tables
Canonical Correspondence Analysis
Aspects of Stability and Inference
Appendix A: Theory of Correspondence Analysis
Appendix B: Computation of Correspondence Analysis
Appendix C: Bibliography of Correspondence Analysis
Appendix D: Glossary of Terms
Appendix E: Epilogue