Multiple Correspondence Analysis and Related Methods

Michael Greenacre, Jorg Blasius

June 23, 2006 by Chapman and Hall/CRC
Reference - 608 Pages - 133 B/W Illustrations
ISBN 9781584886280 - CAT# C6285
Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

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Features

  • Provides the first comprehensive overview of the theory and applications of MCA
  • Begins with two chapters that gently introduce the method to those with less experience in the field
  • Adopts a practical approach with many worked examples
  • Includes applications in survey research, social sciences, marketing, health economics, and biomedical research
  • Features software notes in each chapter, an appendix with computational details, and R programs for applying methods
  • Summary

    As a generalization of simple correspondence analysis, multiple correspondence analysis (MCA) is a powerful technique for handling larger, more complex datasets, including the high-dimensional categorical data often encountered in the social sciences, marketing, health economics, and biomedical research. Until now, however, the literature on the subject has been scattered, leaving many in these fields no comprehensive resource from which to learn its theory, applications, and implementation.

    Multiple Correspondence Analysis and Related Methods gives a state-of-the-art description of this new field in an accessible, self-contained, textbook format. Explaining the methodology step-by-step, it offers an exhaustive survey of the different approaches taken by researchers from different statistical "schools" and explores a wide variety of application areas. Each chapter includes empirical examples that provide a practical understanding of the method and its interpretation, and most chapters end with a "Software Note" that discusses software and computational aspects. An appendix at the end of the book gives further computing details along with code written in the R language for performing MCA and related techniques. The code and the datasets used in the book are available for download from a supporting Web page.

    Providing a unique, multidisciplinary perspective, experts in MCA from both statistics and the social sciences contributed chapters to the book. The editors unified the notation and coordinated and cross-referenced the theory across all of the chapters, making the book read seamlessly. Practical, accessible, and thorough, Multiple Correspondence Analysis and Related Methods brings the theory and applications of MCA under one cover and provides a valuable addition to your statistical toolbox.

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