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Multiple Correspondence Analysis And Related Methods
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Book Synopsis Multiple Correspondence Analysis and Related Methods by : Michael Greenacre
Download or read book Multiple Correspondence Analysis and Related Methods written by Michael Greenacre and published by CRC Press. This book was released on 2006-06-23 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Multiple Correspondence Analysis by : Brigitte Le Roux
Download or read book Multiple Correspondence Analysis written by Brigitte Le Roux and published by SAGE. This book was released on 2010 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.
Book Synopsis Visualization and Verbalization of Data by : Jorg Blasius
Download or read book Visualization and Verbalization of Data written by Jorg Blasius and published by CRC Press. This book was released on 2014-04-10 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Multiple Correspondence Analysis for the Social Sciences by : Johs. Hjellbrekke
Download or read book Multiple Correspondence Analysis for the Social Sciences written by Johs. Hjellbrekke and published by Routledge. This book was released on 2018-06-18 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Biplots in Practice by : Michael J. Greenacre
Download or read book Biplots in Practice written by Michael J. Greenacre and published by Fundacion BBVA. This book was released on 2010 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Correspondence Analysis in Practice by : Michael Greenacre
Download or read book Correspondence Analysis in Practice written by Michael Greenacre and published by CRC Press. This book was released on 2017-01-20 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Exploratory Multivariate Analysis by Example Using R by : Francois Husson
Download or read book Exploratory Multivariate Analysis by Example Using R written by Francois Husson and published by CRC Press. This book was released on 2017-04-25 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Practical Guide To Principal Component Methods in R by : Alboukadel KASSAMBARA
Download or read book Practical Guide To Principal Component Methods in R written by Alboukadel KASSAMBARA and published by STHDA. This book was released on 2017-08-23 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Multiple Factor Analysis by Example Using R by : Jérôme Pagès
Download or read book Multiple Factor Analysis by Example Using R written by Jérôme Pagès and published by CRC Press. This book was released on 2014-11-20 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Applied Correspondence Analysis by : eric clausen sten
Download or read book Applied Correspondence Analysis written by eric clausen sten and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An R and S-Plus® Companion to Multivariate Analysis by : Brian Everitt
Download or read book An R and S-Plus® Companion to Multivariate Analysis written by Brian Everitt and published by Springer Science & Business Media. This book was released on 2005-03-17 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Multiple Correspondence Analysis by : Brigitte Le Roux
Download or read book Multiple Correspondence Analysis written by Brigitte Le Roux and published by . This book was released on 2010 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work provides a nontechnical introduction to multiple correspondence analysis as a method in its own right. The presentation is practically oriented and with the needs of research in mind: gathering relevant data, formulating questions of interest, and linking statistical interpretation to geometric representations.
Book Synopsis Correspondence Analysis and Data Coding with Java and R by : Fionn Murtagh
Download or read book Correspondence Analysis and Data Coding with Java and R written by Fionn Murtagh and published by CRC Press. This book was released on 2005-05-26 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Theory and Applications of Correspondence Analysis by : Michael J. Greenacre
Download or read book Theory and Applications of Correspondence Analysis written by Michael J. Greenacre and published by . This book was released on 1984 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Nonlinear Principal Component Analysis and Its Applications by : Yuichi Mori
Download or read book Nonlinear Principal Component Analysis and Its Applications written by Yuichi Mori and published by Springer. This book was released on 2016-12-09 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis by : Todd D. Little
Download or read book The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis written by Todd D. Little and published by Oxford University Press. This book was released on 2013-02-01 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, The Oxford Handbook of Quantitative Methods is the complete tool box to deliver the most valid and generalizable answers to todays complex research questions. It is a one-stop source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Comprising two volumes, this handbook covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the handbook then segway into the realm of statistical inference and modeling with chapters dedicated to classical approaches as well as modern latent variable approaches. Numerous chapters associated with longitudinal data and more specialized techniques round out this broad selection of topics. Comprehensive, authoritative, and user-friendly, this two-volume set will be an indispensable resource for serious researchers across the social, behavioral, and educational sciences.
Book Synopsis An Introduction to Categorical Data Analysis by : Alan Agresti
Download or read book An Introduction to Categorical Data Analysis written by Alan Agresti and published by John Wiley & Sons. This book was released on 2018-10-11 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.
