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Multiple Correspondence Analysis (Quantitative Applications in the Social Sciences), by Brigitte Le Roux, Henry Rouanet
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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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- Sales Rank: #1554159 in Books
- Published on: 2009-12-16
- Original language: English
- Number of items: 1
- Dimensions: 8.50" h x 5.00" w x .25" l, .35 pounds
- Binding: Paperback
- 128 pages
About the Author
Brigitte Le Roux has a doctorate in mathematics (specialty Statistics) (Faculty of Sciences in Paris, 1970) and holds an HDR in Applied Mathematics (University of Paris Dauphine, 2000). She is a member of the laboratory MAP5 (Applied Mathematics Paris 5) of the University Paris Descartes. His research focuses on the geometric data analysis and its applications in social sciences and in particular to the analysis of questionnaires.
Brigitte Le Roux is a member of the editorial board of the journal Mathematics and Humanities and the Acts of Research in Social Sciences.
Most helpful customer reviews
1 of 1 people found the following review helpful.
great introduction to cultural analytics
By Santiago Ortiz
This beautiful book also serves the purpose of being a great introduction to cultural analytics through a specific methodology. MCA is versatile, rich in variations and alternative or complementary paths. It basically requires a table of categories (that could be built out of variables that are not categorical, the book explains how). MCA is also quite easy to understand: how it's built and why it makes sense. Yes, the book contains some detailed mathematical definitions and demonstrations, specially regarding the variance and how the method is super-elegant and preserves many of the statistical properties one would wish. I believe mathematical equations can be overlooked without any harm of comprehension (I did it in part, and plan to re-read the book to touch those details when using the method in actual projects).
Finally, this is also a book about sociology and specially about part of Pierre Bourdieu's work. Along the book a table based on an actual survey about taste (essential concept in Bordieu's studies) is being used as the example of the different analyses and visualizations.
1 of 1 people found the following review helpful.
Extremely useful for social scientists!
By Marilia Moscou
I had been trying to learn multiple correspondence analysis for a while when Professor Lebaron, from Université d'Amiens/Picardie Jules Verne, told me about this book. It helped me trace a study program - from reviewing basic stistics, to learning how to use MCA softwares, to aplying the techniques - and interpreting data for my MA research. It's clear and pratical, like a guide or manual to this technique. Even social scientists who are not so familiar with statistics may use it pretty well.
1 of 1 people found the following review helpful.
Much-awaited handbook on MCA
By Pierre Pénet
This is truly a great book, for what it is, a 100- or so page book on MCA. Le roux and Rouanet are as didactic as Greenacre with the full-scale research studies at the end of the book. MCA is a powerful tool which should receive greater attention from American scholars interested in quantification.
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