Geometric data analysis: From correspondence analysis to structured data analysis

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Abstract

Geometric Data Analysis (GDA) is the name suggested by P. Suppes (Stanford University) to designate the approach to Multivariate Statistics initiated by Benzécri as Correspondence Analysis, an approach that has become more and more used and appreciated over the years. This book presents the full formalization of GDA in terms of linear algebra-the most original and far-reaching consequential feature of the approach-and shows also how to integrate the standard statistical tools such as Analysis of Variance, including Bayesian methods. Chapter 9, Research Case Studies, is nearly a book in itself; it presents the methodology in action on three extensive applications, one for medicine, one from political science, and one from education (data borrowed from the Stanford computer-based Educational Program for Gifted Youth ). Thus the readership of the book concerns both mathematicians interested in the applications of mathematics, and researchers willing to master an exceptionally powerful approach of statistical data analysis. © 2005 Springer Science + Business Media, Inc.

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Roux, B. L., & Rouanet, H. (2005). Geometric data analysis: From correspondence analysis to structured data analysis. Geometric Data Analysis: From Correspondence Analysis to Structured Data Analysis (pp. 1–475). Springer Netherlands. https://doi.org/10.1007/1-4020-2236-0

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