Multiple Correspondence Analysis

Multiple Correspondence Analysis by Brigitte Le Roux. Download it Multiple Correspondence Analysis books also available in PDF, EPUB, and Mobi Format for read it on your Kindle device, PC, phones or tablets. 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.. Click Get Books for free books.

Multiple Correspondence Analysis

Multiple Correspondence Analysis
Author: Brigitte Le Roux
Publisher: SAGE
ISBN: 1412968976
Size: 68.42 MB
Format: PDF, Kindle
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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. Learn more about “The Little Green Book” - QASS Series! Click Here
Multiple Correspondence Analysis
Language: en
Pages: 115
Authors: Brigitte Le Roux, Henry Rouanet
Categories: Social Science
Type: BOOK - Published: 2010 - Publisher: SAGE
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
Multiple Correspondence Analysis and Related Methods
Language: en
Pages: 608
Authors: Michael Greenacre, Jorg Blasius
Categories: Mathematics
Type: BOOK - Published: 2006-06-23 - Publisher: CRC Press
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
Multiple Correspondence Analysis for the Social Sciences
Language: en
Pages: 118
Authors: Johs. Hjellbrekke
Categories: Social Science
Type: BOOK - Published: 2018-06-18 - Publisher: Routledge
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
A Multiple Correspondence Analysis Approach to the Measurement of Multidimensional Poverty in Morocco, 2001-2007
Language: en
Pages:
Authors: Johs. Hjellbrekke
Categories: Social Science
Type: BOOK - Published: 2012 - Publisher:
Books about A Multiple Correspondence Analysis Approach to the Measurement of Multidimensional Poverty in Morocco, 2001-2007
An Introduction to Correspondence Analysis
Language: en
Pages: 220
Authors: Beh
Categories: Social Science
Type: BOOK - Published: - Publisher: Wiley-Blackwell
Books about An Introduction to Correspondence Analysis
Theory and Applications of Correspondence Analysis
Language: en
Pages: 364
Authors: Michael J. Greenacre
Categories: Mathematics
Type: BOOK - Published: 1984 - Publisher:
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.
The Application of Fuzzy Coding and Horseshoes in Multiple Correspondence Analysis
Language: en
Pages: 272
Authors: Jan L. A. van Rijckevorsel
Categories: Correspondence analysis
Type: BOOK - Published: 1987 - Publisher:
Books about The Application of Fuzzy Coding and Horseshoes in Multiple Correspondence Analysis
Exploratory Multivariate Analysis by Example Using R
Language: en
Pages: 240
Authors: Francois Husson, Sebastien Le, Jérôme Pagès
Categories: Mathematics
Type: BOOK - Published: 2010-11-15 - Publisher: CRC Press
Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when
Mathematical Aspects of Multiple Correspondence Analysis for Ordinal Variables
Language: en
Pages: 136
Authors: Jan T. A. Koster
Categories: Correspondence analysis (Statistics)
Type: BOOK - Published: 1989 - Publisher:
Books about Mathematical Aspects of Multiple Correspondence Analysis for Ordinal Variables
Correspondence Analysis in Practice
Language: en
Pages: 296
Authors: Michael Greenacre
Categories: Mathematics
Type: BOOK - Published: 2007-05-07 - Publisher: CRC Press
Drawing on the author’s experience in social and environmental research, Correspondence Analysis in Practice, Second Edition shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide variety of situations. This completely revised, up-to-date edition features a didactic approach with self-contained chapters, extensive