Description
Requiring no prior knowledge of correspondence analysis, this text provides a nontechnical introduction to Multiple Correspondence Analysis (MCA) as a method in its own right. The authors, Brigitte LeRoux and Henry Rouanet, present thematerial in a practical manner, keeping the needs of researchers foremost in mind.
Key Features
- Readers learn how to construct geometric spaces from relevant data, formulate questions of interest, and link statistical interpretation to geometric representations.
- They also learn how to perform structured data analysis and to draw inferential conclusions from MCA.
- The text uses real examples to help explain concepts.
- The authors stress the distinctive capacity of MCA to handle full-scale research studies.
This supplementary text is appropriate for any graduate-level, intermediate, or advanced statistics course across the social and behavioral sciences, as well as for individual researchers.
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Table of Contents
About the Authors
Series Editor′s Introduction
Acknowledgments
1. Introduction
2. The Geometry of a Cloud of Points
3. The Method of Multiple Correspondence Analysis
4. Structured Data Analysis
5. Inductive Data Analysis
6. Full-Scale Research Studies
Appendix
References
Index
