Multiple Correspondence Analysis

1. Auflage 2009
ISBN: 978-1-4129-6897-3
Verlag: Sage Publications

Buch, Englisch, Band 163, 128 Seiten, Format (B × H): 141 mm x 217 mm, Gewicht: 151 g

Reihe: Quantitative Applications in the Social Sciences

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.

Autoren/Hrsg.

Le Roux, Brigitte

Rouanet, Henry

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung

Inhaltsverzeichnis

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

Über Autor(innen)

Le Roux, Brigitte
<span lang="en" id="result_box"><span class="hps">Brigitte</span> <span class="hps">Le Roux</span> <span class="hps">has a doctorate in</span> <span class="hps">mathematics</span> <span class="hps atn">(</span><span>specialty</span> <span class="hps">Statistics</span><span class="atn">) (</span><span>Faculty</span> <span class="hps">of Sciences in Paris</span><span>,</span> <span class="hps">1970)</span> <span class="hps">and holds</span> <span class="hps">an</span> <span class="hps">HDR</span> <span class="hps">in Applied Mathematics</span> <span class="hps atn">(</span><span>University of Paris</span> <span class="hps">Dauphine</span><span>,</span> <span class="hps">2000)</span><span>.</span> <span class="hps">She is a member</span> <span class="hps">of the laboratory</span> <span class="hps">MAP5</span> <span class="hps atn">(</span><span>Applied Mathematics</span> <span class="hps">Paris</span> <span class="hps">5)</span> <span class="hps">of the University</span> <span class="hps">Paris</span> <span class="hps">Descartes</span><span>.</span> <span class="hps">His research focuses on</span> <span class="hps">the</span> <span class="hps">geometric data analysis</span> <span class="hps">and</span> <span class="hps">its applications</span> <span class="hps">in social sciences and</span> <span class="hps">in particular</span> <span class="hps">to the analysis of</span> <span class="hps">questionnaires</span><span>.</span>

<span class="hps">Brigitte</span> <span class="hps">Le Roux</span> <span class="hps">is a member</span> <span class="hps">of the editorial board</span> <span class="hps">of the journal</span> <span class="hps">Mathematics</span> <span class="hps">and Humanities</span> <span class="hps">and</span> <span class="hps">the</span> <span class="hps">Acts</span> <span class="hps">of</span> <span class="hps">Research</span> <span class="hps">in Social Sciences</span><span>.</span></span>