Multiple Correspondence Analysis

Author: Brigitte Le Roux
Publisher: SAGE
ISBN: 1412968976
Category : Mathematics
Languages : en
Pages : 129

Book Description
"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 and Related Methods

Author: Michael Greenacre
Publisher: CRC Press
ISBN: 1420011316
Category : Mathematics
Languages : en
Pages : 607

Book Description
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

Multiple Correspondence Analysis for the Social Sciences

Author: Johs. Hjellbrekke
Publisher: Routledge
ISBN: 1315516241
Category : Social Science
Languages : en
Pages : 118

Book Description
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.

Visualization and Verbalization of Data

Author: Jorg Blasius
Publisher: CRC Press
ISBN: 1466589817
Category : Mathematics
Languages : en
Pages : 382

Book Description
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

Practical Guide To Principal Component Methods in R

Author: Alboukadel KASSAMBARA
Publisher: STHDA
ISBN: 1975721136
Category : Education
Languages : en
Pages : 171

Book Description
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.

Correspondence Analysis in Practice

Author: Michael Greenacre
Publisher: CRC Press
ISBN: 1498731783
Category : Mathematics
Languages : en
Pages : 327

Book Description
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.

Biplots in Practice

Author: Michael J. Greenacre
Publisher: Fundacion BBVA
ISBN: 8492384689
Category : Fishes
Languages : en
Pages : 241

Book Description
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.

Multiple Factor Analysis by Example Using R

Author: Jérôme Pagès
Publisher: CRC Press
ISBN: 1482205483
Category : Mathematics
Languages : en
Pages : 272

Book Description
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

Exploratory Multivariate Analysis by Example Using R

Author: Francois Husson
Publisher: CRC Press
ISBN: 1315301865
Category : Mathematics
Languages : en
Pages : 263

Book Description
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

Quantitative Approaches to Multidimensional Poverty Measurement

Author: N. Kakwani
Publisher: Springer
ISBN: 0230582354
Category : Business & Economics
Languages : en
Pages : 290

Book Description
This book is written in light of the latest developments in the field of multidimensional poverty measurement. It includes clear presentations of more than a dozen different quantitative techniques and provides empirical illustrations based on data sources from developed or developing countries.