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Multiple Correspondence Analysis
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Multiple Correspondence Analysis

Volume: 163
December 2009 | 128 pages | SAGE Publications, Inc
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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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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

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