Multiple Correspondence Analysis: Vol 163

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.