An Introduction To Correspondence Analysis
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An Introduction To Correspondence Analysis
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Author : Eric J. Beh
language : en
Publisher: John Wiley & Sons
Release Date : 2021-04-09
An Introduction To Correspondence Analysis written by Eric J. Beh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-09 with Mathematics categories.
Master the fundamentals of correspondence analysis with this illuminating resource An Introduction to Correspondence Analysis assists researchers in improving their familiarity with the concepts, terminology, and application of several variants of correspondence analysis. The accomplished academics and authors deliver a comprehensive and insightful treatment of the fundamentals of correspondence analysis, including the statistical and visual aspects of the subject. Written in three parts, the book begins by offering readers a description of two variants of correspondence analysis that can be applied to two-way contingency tables for nominal categories of variables. Part Two shifts the discussion to categories of ordinal variables and demonstrates how the ordered structure of these variables can be incorporated into a correspondence analysis. Part Three describes the analysis of multiple nominal categorical variables, including both multiple correspondence analysis and multi-way correspondence analysis. Readers will benefit from explanations of a wide variety of specific topics, for example: Simple correspondence analysis, including how to reduce multidimensional space, measuring symmetric associations with the Pearson Ratio, constructing low-dimensional displays, and detecting statistically significant points Non-symmetrical correspondence analysis, including quantifying asymmetric associations Simple ordinal correspondence analysis, including how to decompose the Pearson Residual for ordinal variables Multiple correspondence analysis, including crisp coding and the indicator matrix, the Burt Matrix, and stacking Multi-way correspondence analysis, including symmetric multi-way analysis Perfect for researchers who seek to improve their understanding of key concepts in the graphical analysis of categorical data, An Introduction to Correspondence Analysis will also assist readers already familiar with correspondence analysis who wish to review the theoretical and foundational underpinnings of crucial concepts.
Multiple Correspondence Analysis
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Author : Brigitte Le Roux
language : en
Publisher: SAGE
Release Date : 2010
Multiple Correspondence Analysis written by Brigitte Le Roux and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Social Science categories.
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 And Related Methods
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Author : Michael Greenacre
language : en
Publisher: CRC Press
Release Date : 2006-06-23
Multiple Correspondence Analysis And Related Methods written by Michael Greenacre and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06-23 with Mathematics categories.
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 And Data Coding With Java And R
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Author : Fionn Murtagh
language : en
Publisher: CRC Press
Release Date : 2005-05-26
Correspondence Analysis And Data Coding With Java And R written by Fionn Murtagh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-05-26 with Mathematics categories.
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 Handbook
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Author : Benzecri
language : en
Publisher: CRC Press
Release Date : 1992-01-22
Correspondence Analysis Handbook written by Benzecri and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-01-22 with Mathematics categories.
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 research, or as a text for graduate level courses in multidimensional statistics.;The book features fully worked-out exercises, without the help of a computer, illustrating the constructions of correspondence analysis. It gives details of how to prepare, read and interpret computer results, including a complete FORTRAN program listing of the basic algorithms of factor analysis and classification. Sixteen case studies from medicine and biology, economics and the humanities, demonstrate a selection of data and interpretation of results. A foundation for agglomerative hierarchical clustering is provided.
Applied Correspondence Analysis
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Author : Sten-Erik Clausen
language : en
Publisher: SAGE
Release Date : 1998-06
Applied Correspondence Analysis written by Sten-Erik Clausen and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-06 with Mathematics categories.
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.
Geometric Data Analysis
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Author : Brigitte Le Roux
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-01-16
Geometric Data Analysis written by Brigitte Le Roux and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-16 with Mathematics categories.
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.
Metric Scaling
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Author : Susan C. Weller
language : en
Publisher: SAGE
Release Date : 1990
Metric Scaling written by Susan C. Weller and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Psychology categories.
Presents a set of closely related techniques that facilitate the exploration and display of a wide variety of multivariate data, both categorical and continuous. Three methods of metric scaling, correspondence analysis, principal components analysis, and multiple dimensional preference scaling are explored in detail for strengths and weaknesses over a wide range of data types and research situations. "The introduction illustrates the methods with a small dataset. This approach is effective--in a few minutes, with no mathematical requirement, the reader can understand the capabilities, similarities, and differences of the methods. . . . Numerical examples facilitate learning. The authors use several examples with small datasets that illustrate very well the links and the differences between the methods. . . . we find this text very good and recommend it for graduate students and social science researchers, especially those who are interested in applying some of these methods and in knowing the relationship among them." --Journal of Marketing Research "Illustrate[s] the service Sage provides by making high-quality works on research methods available at modest prices. . . . The authors use several interesting examples of practical applications on data sets, ranging from contraception preferences, to pottery shards from archeological digs, to durable consumer goods from market research. These examples indicate the broad range of possible applications of the method to social science data." --Contemporary Sociology "The book is a bargain; it is clearly written." --Journal of Classification
Theory And Applications Of Correspondence Analysis
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Author : Michael J. Greenacre
language : en
Publisher:
Release Date : 1984
Theory And Applications Of Correspondence Analysis written by Michael J. Greenacre and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Mathematics categories.
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.
Correspondence Analysis In Practice
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Author : Michael Greenacre
language : en
Publisher: CRC Press
Release Date : 2017-01-20
Correspondence Analysis In Practice written by Michael Greenacre and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-20 with Mathematics categories.
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.