Multiple Correspondence Analysis

Multiple Correspondence Analysis

Author: Brigitte Le Roux

Publisher: SAGE

Published: 2010

Total Pages: 129

ISBN-13: 1412968976

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"Requiring no prior knowledge of correspondence analysis, this text provides anontechnical introduction to Multiple Correspondence Analysis (MCA) as a method in its own right. The authors, Brigitte Le Roux and Henry Rouanet, present the material in a practical manner, keeping the needs of researchers foremost in mind." "This supplementary text isappropriate for any graduate-level, intermediate, or advanced statistics course across the social and behavioral sciences, as well as forindividual researchers." --Book Jacket.


Applied Correspondence Analysis

Applied Correspondence Analysis

Author: Sten-Erik Clausen

Publisher: SAGE

Published: 1998-06

Total Pages: 230

ISBN-13: 9780761911159

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This volume provides readers with a simple, non-technical introduction to correspondence analysis (CA), a technique for summarily describing the relationships among categorical variables in large tables. It begins with the history and logic of CA. The author shows readers the steps to the analysis: category profiles and masses are computed, the distances between these points calculated and the best-fitting space of n-dimensions located. There are glossaries on appropriate programs from SAS and SPSS for doing CA and the book concludes with a comparison of CA and log-linear models.


Correspondence Analysis Handbook

Correspondence Analysis Handbook

Author: Benzecri

Publisher: CRC Press

Published: 1992-01-22

Total Pages: 684

ISBN-13: 058536303X

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This practical reference/text presents a complete introduction to the practice of data analysis - clarifying the geometrical language used, explaining the formulae, reviewing linear algebra and multidimensional Euclidean geometry, and including proofs of results. It is intended as either a self-study guide for professionals involved in experimental


Correspondence Analysis and Data Coding with Java and R

Correspondence Analysis and Data Coding with Java and R

Author: Fionn Murtagh

Publisher: CRC Press

Published: 2005-05-26

Total Pages: 253

ISBN-13: 1420034944

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Developed by Jean-Paul Benzerci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of correspondence analysis continue, and with the tremendous computing power now available and new fields of application emerging, its significance is greater


Correspondence Analysis in Practice

Correspondence Analysis in Practice

Author: Michael Greenacre

Publisher: CRC Press

Published: 2017-01-20

Total Pages: 327

ISBN-13: 1498731783

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Drawing on the author’s 45 years of experience in multivariate analysis, Correspondence Analysis in Practice, Third Edition, shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide variety of situations. CA and its variants, subset CA, multiple CA and joint CA, translate two-way and multi-way tables into more readable graphical forms — ideal for applications in the social, environmental and health sciences, as well as marketing, economics, linguistics, archaeology, and more. Michael Greenacre is Professor of Statistics at the Universitat Pompeu Fabra, Barcelona, Spain, where he teaches a course, amongst others, on Data Visualization. He has authored and co-edited nine books and 80 journal articles and book chapters, mostly on correspondence analysis, the latest being Visualization and Verbalization of Data in 2015. He has given short courses in fifteen countries to environmental scientists, sociologists, data scientists and marketing professionals, and has specialized in statistics in ecology and social science.


Multiple Correspondence Analysis and Related Methods

Multiple Correspondence Analysis and Related Methods

Author: Michael Greenacre

Publisher: CRC Press

Published: 2006-06-23

Total Pages: 607

ISBN-13: 1420011316

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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 su


Correspondence Analysis in the Social Sciences

Correspondence Analysis in the Social Sciences

Author: Michael Greenacre

Publisher: Academic Press

Published: 1994-09-21

Total Pages: 400

ISBN-13:

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The first part of the book deals with basic concepts of correspondence analysis and related methods for analyzing cross-tabulations. It then looks at the multivariate case when there are several variables of interest, including the relationship to cluster analysis, factor analysis and reliability of measurement. Applications to longitudinal data: event history data, panel data and trend data are demonstrated.


Multiple Correspondence Analysis for the Social Sciences

Multiple Correspondence Analysis for the Social Sciences

Author: Johs. Hjellbrekke

Publisher: Routledge

Published: 2018-06-18

Total Pages: 118

ISBN-13: 1315516241

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Multiple correspondence analysis (MCA) is a statistical technique that first and foremost has become known through the work of the late Pierre Bourdieu (1930–2002). This book will introduce readers to the fundamental properties, procedures and rules of interpretation of the most commonly used forms of correspondence analysis. The book is written as a non-technical introduction, intended for the advanced undergraduate level and onwards. MCA represents and models data sets as clouds of points in a multidimensional Euclidean space. The interpretation of the data is based on these clouds of points. In seven chapters, this non-technical book will provide the reader with a comprehensive introduction and the needed knowledge to do analyses on his/her own: CA, MCA, specific MCA, the integration of MCA and variance analysis, of MCA and ascending hierarchical cluster analysis and class-specific MCA on subgroups. Special attention will be given to the construction of social spaces, to the construction of typologies and to group internal oppositions. This is a book on data analysis for the social sciences rather than a book on statistics. The main emphasis is on how to apply MCA to the analysis of practical research questions. It does not require a solid understanding of statistics and/or mathematics, and provides the reader with the needed knowledge to do analyses on his/her own.


Theory and Applications of Correspondence Analysis

Theory and Applications of Correspondence Analysis

Author: Michael J. Greenacre

Publisher:

Published: 1984

Total Pages: 386

ISBN-13:

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Geometric concepts in multidimensional space; Simple illustrations of correspondence analysis; Theory of correspondence analysis and equivalent approaches; Multiple correspondence analysis; Correspondence analysis of ratings and preferences; Use of correspondence analysis in discriminant analysis, classification, regression and cluster analysis; Special topics; Applications of correspondence analysis.