Multiple Correspondence Analysis And Related Methods

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Multiple Correspondence Analysis and Related Methods

Michael Greenacre,Jorg Blasius
Multiple Correspondence Analysis and Related Methods Book PDF

Author : Michael Greenacre,Jorg Blasius
Publisher : CRC Press
Page : 607 pages
File Size : 44,7 Mb
Release : 2006-06-23
Category : Mathematics
ISBN : 9781420011319

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Multiple Correspondence Analysis and Related Methods by Michael Greenacre,Jorg Blasius Pdf

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

Visualization and Verbalization of Data

Jorg Blasius,Michael Greenacre
Visualization and Verbalization of Data Book PDF

Author : Jorg Blasius,Michael Greenacre
Publisher : CRC Press
Page : 392 pages
File Size : 53,5 Mb
Release : 2014-04-10
Category : Mathematics
ISBN : 9781466589810

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Visualization and Verbalization of Data by Jorg Blasius,Michael Greenacre Pdf

Visualization and Verbalization of Data shows how correspondence analysis and related techniques enable the display of data in graphical form, which results in the verbalization of the structures in data. Renowned researchers in the field trace the history of these techniques and cover their current applications. The first part of the book explains the historical origins of correspondence analysis and associated methods. The second part concentrates on the contributions made by the school of Jean-Paul Benzécri and related movements, such as social space and geometric data analysis. Although these topics are viewed from a French perspective, the book makes them understandable to an international audience. Throughout the text, well-known experts illustrate the use of the methods in practice. Examples include the spatial visualization of multivariate data, cluster analysis in computer science, the transformation of a textual data set into numerical data, the use of quantitative and qualitative variables in multiple factor analysis, different possibilities of recoding data prior to visualization, and the application of duality diagram theory to the analysis of a contingency table.

Multiple Correspondence Analysis

Brigitte Le Roux,Henry Rouanet
Multiple Correspondence Analysis Book PDF

Author : Brigitte Le Roux,Henry Rouanet
Publisher : SAGE
Page : 129 pages
File Size : 45,5 Mb
Release : 2010
Category : Mathematics
ISBN : 9781412968973

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Multiple Correspondence Analysis by Brigitte Le Roux,Henry Rouanet Pdf

"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.

Multiple Correspondence Analysis for the Social Sciences

Johs. Hjellbrekke
Multiple Correspondence Analysis for the Social Sciences Book PDF

Author : Johs. Hjellbrekke
Publisher : Routledge
Page : 118 pages
File Size : 52,8 Mb
Release : 2018-06-18
Category : Social Science
ISBN : 9781315516240

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Multiple Correspondence Analysis for the Social Sciences by Johs. Hjellbrekke Pdf

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.

Biplots in Practice

Michael J. Greenacre
Biplots in Practice Book PDF

Author : Michael J. Greenacre
Publisher : Fundacion BBVA
Page : 241 pages
File Size : 51,8 Mb
Release : 2010
Category : Fishes
ISBN : 9788492384686

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Biplots in Practice by Michael J. Greenacre Pdf

Este libro explica las aplicaciones específicas y las interpretaciones del biplot en muchas áreas del análisis multivariante. regresión, modelos lineales generalizados, análisis de componentes principales, análisis de correspondencias y análisis discriminante.

Correspondence Analysis in Practice, Third Edition

Michael Greenacre
Correspondence Analysis in Practice Third Edition Book PDF

Author : Michael Greenacre
Publisher : CRC Press
Page : 571 pages
File Size : 46,5 Mb
Release : 2017-01-20
Category : Mathematics
ISBN : 9781315352954

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Correspondence Analysis in Practice, Third Edition by Michael Greenacre Pdf

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.

Practical Guide To Principal Component Methods in R

Alboukadel KASSAMBARA
Practical Guide To Principal Component Methods in R Book PDF

Author : Alboukadel KASSAMBARA
Publisher : STHDA
Page : 169 pages
File Size : 49,5 Mb
Release : 2017-08-23
Category : Electronic
ISBN : 9781975721138

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Practical Guide To Principal Component Methods in R by Alboukadel KASSAMBARA Pdf

Although there are several good books on principal component methods (PCMs) and related topics, we felt that many of them are either too theoretical or too advanced. This book provides a solid practical guidance to summarize, visualize and interpret the most important information in a large multivariate data sets, using principal component methods in R. The visualization is based on the factoextra R package that we developed for creating easily beautiful ggplot2-based graphs from the output of PCMs. This book contains 4 parts. Part I provides a quick introduction to R and presents the key features of FactoMineR and factoextra. Part II describes classical principal component methods to analyze data sets containing, predominantly, either continuous or categorical variables. These methods include: Principal Component Analysis (PCA, for continuous variables), simple correspondence analysis (CA, for large contingency tables formed by two categorical variables) and Multiple CA (MCA, for a data set with more than 2 categorical variables). In Part III, you'll learn advanced methods for analyzing a data set containing a mix of variables (continuous and categorical) structured or not into groups: Factor Analysis of Mixed Data (FAMD) and Multiple Factor Analysis (MFA). Part IV covers hierarchical clustering on principal components (HCPC), which is useful for performing clustering with a data set containing only categorical variables or with a mixed data of categorical and continuous variables.

Exploratory Multivariate Analysis by Example Using R

Francois Husson,Sebastien Le,Jérôme Pagès
Exploratory Multivariate Analysis by Example Using R Book PDF

Author : Francois Husson,Sebastien Le,Jérôme Pagès
Publisher : CRC Press
Page : 263 pages
File Size : 45,7 Mb
Release : 2017-04-25
Category : Mathematics
ISBN : 9781315301860

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Exploratory Multivariate Analysis by Example Using R by Francois Husson,Sebastien Le,Jérôme Pagès Pdf

Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition 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) a

Multiple Factor Analysis by Example Using R

Jérôme Pagès
Multiple Factor Analysis by Example Using R Book PDF

Author : Jérôme Pagès
Publisher : CRC Press
Page : 272 pages
File Size : 43,5 Mb
Release : 2014-11-20
Category : Mathematics
ISBN : 9781482205480

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Multiple Factor Analysis by Example Using R by Jérôme Pagès Pdf

Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also inc

Metric Scaling

Susan C. Weller,A. Kimball Romney
Metric Scaling Book PDF

Author : Susan C. Weller,A. Kimball Romney
Publisher : SAGE
Page : 100 pages
File Size : 45,5 Mb
Release : 1990
Category : Psychology
ISBN : 0803937504

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Metric Scaling by Susan C. Weller,A. Kimball Romney Pdf

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

Michael J. Greenacre
Theory and Applications of Correspondence Analysis Book PDF

Author : Michael J. Greenacre
Publisher : Unknown
Page : 386 pages
File Size : 51,8 Mb
Release : 1984
Category : Mathematics
ISBN : UOM:39015079304922

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Theory and Applications of Correspondence Analysis by Michael J. Greenacre Pdf

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.

Nonlinear Principal Component Analysis and Its Applications

Yuichi Mori,Masahiro Kuroda,Naomichi Makino
Nonlinear Principal Component Analysis and Its Applications Book PDF

Author : Yuichi Mori,Masahiro Kuroda,Naomichi Makino
Publisher : Springer
Page : 80 pages
File Size : 50,7 Mb
Release : 2016-12-09
Category : Mathematics
ISBN : 9789811001598

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Nonlinear Principal Component Analysis and Its Applications by Yuichi Mori,Masahiro Kuroda,Naomichi Makino Pdf

This book expounds the principle and related applications of nonlinear principal component analysis (PCA), which is useful method to analyze mixed measurement levels data. In the part dealing with the principle, after a brief introduction of ordinary PCA, a PCA for categorical data (nominal and ordinal) is introduced as nonlinear PCA, in which an optimal scaling technique is used to quantify the categorical variables. The alternating least squares (ALS) is the main algorithm in the method. Multiple correspondence analysis (MCA), a special case of nonlinear PCA, is also introduced. All formulations in these methods are integrated in the same manner as matrix operations. Because any measurement levels data can be treated consistently as numerical data and ALS is a very powerful tool for estimations, the methods can be utilized in a variety of fields such as biometrics, econometrics, psychometrics, and sociology. In the applications part of the book, four applications are introduced: variable selection for mixed measurement levels data, sparse MCA, joint dimension reduction and clustering methods for categorical data, and acceleration of ALS computation. The variable selection methods in PCA that originally were developed for numerical data can be applied to any types of measurement levels by using nonlinear PCA. Sparseness and joint dimension reduction and clustering for nonlinear data, the results of recent studies, are extensions obtained by the same matrix operations in nonlinear PCA. Finally, an acceleration algorithm is proposed to reduce the problem of computational cost in the ALS iteration in nonlinear multivariate methods. This book thus presents the usefulness of nonlinear PCA which can be applied to different measurement levels data in diverse fields. As well, it covers the latest topics including the extension of the traditional statistical method, newly proposed nonlinear methods, and computational efficiency in the methods.

Multivariate Analysis of Ecological Data

Michael Greenacre,Raul Primicerio
Multivariate Analysis of Ecological Data Book PDF

Author : Michael Greenacre,Raul Primicerio
Publisher : Fundacion BBVA
Page : 336 pages
File Size : 46,9 Mb
Release : 2014-01-09
Category : Ecology
ISBN : 9788492937509

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Multivariate Analysis of Ecological Data by Michael Greenacre,Raul Primicerio Pdf

La diversidad biológica es fruto de la interacción entre numerosas especies, ya sean marinas, vegetales o animales, a la par que de los muchos factores limitantes que caracterizan el medio que habitan. El análisis multivariante utiliza las relaciones entre diferentes variables para ordenar los objetos de estudio según sus propiedades colectivas y luego clasificarlos; es decir, agrupar especies o ecosistemas en distintas clases compuestas cada una por entidades con propiedades parecidas. El fin último es relacionar la variabilidad biológica observada con las correspondientes características medioambientales. Multivariate Analysis of Ecological Data explica de manera completa y estructurada cómo analizar e interpretar los datos ecológicos observados sobre múltiples variables, tanto biológicos como medioambientales. Tras una introducción general a los datos ecológicos multivariantes y la metodología estadística, se abordan en capítulos específicos, métodos como aglomeración (clustering), regresión, biplots, escalado multidimensional, análisis de correspondencias (simple y canónico) y análisis log-ratio, con atención también a sus problemas de modelado y aspectos inferenciales. El libro plantea una serie de aplicaciones a datos reales derivados de investigaciones ecológicas, además de dos casos detallados que llevan al lector a apreciar los retos de análisis, interpretación y comunicación inherentes a los estudios a gran escala y los diseños complejos.

An R and S-Plus® Companion to Multivariate Analysis

Brian Everitt
An R and S Plus Companion to Multivariate Analysis Book PDF

Author : Brian Everitt
Publisher : Springer Science & Business Media
Page : 231 pages
File Size : 55,8 Mb
Release : 2005-03-17
Category : Computers
ISBN : 9781852338824

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An R and S-Plus® Companion to Multivariate Analysis by Brian Everitt Pdf

Applied statisticians often need to perform analyses of multivariate data; for these they will typically use one of the statistical software packages, S-Plus or R. This book sets out how to use these packages for these analyses in a concise and easy-to-use way, and will save users having to buy two books for the job. The author is well-known for this kind of book, and so buyers will trust that he’s got it right.

Assessing the Quality of Survey Data

Jörg Blasius,Victor Thiessen
Assessing the Quality of Survey Data Book PDF

Author : Jörg Blasius,Victor Thiessen
Publisher : SAGE
Page : 193 pages
File Size : 42,8 Mb
Release : 2012-02-21
Category : Social Science
ISBN : 9781446258729

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Assessing the Quality of Survey Data by Jörg Blasius,Victor Thiessen Pdf

This is a book for any researcher using any kind of survey data. It introduces the latest methods of assessing the quality and validity of such data by providing new ways of interpreting variation and measuring error. By practically and accessibly demonstrating these techniques, especially those derived from Multiple Correspondence Analysis, the authors develop screening procedures to search for variation in observed responses that do not correspond with actual differences between respondents. Using well-known international data sets, the authors exemplify how to detect all manner of non-substantive variation having sources such as a variety of response styles including acquiescence, respondents′ failure to understand questions, inadequate field work standards, interview fatigue, and even the manufacture of (partly) faked interviews.