Overview

Correspondence Analysis in the Social Sciences gives a comprehensive description of this method of data visualization as well as numerous applications to a wide range of social science data. Various theoretical aspects are presented in a language accessible to both social scientists and statisticians and a wide variety of applications are given which demonstrate the versatility of the method to interpret tabular data in a unique graphical way.

Full Product Details

Author:   Michael Greenacre (University of South Africa, Pretoria) ,  Jörg Blasius (Zentralarchiv fur empirische Sozialforschung)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Academic Press Inc
Dimensions:   Width: 15.20cm , Height: 2.30cm , Length: 22.90cm
Weight:   0.700kg
ISBN:  

9780121045708

ISBN 10:   0121045706
Pages:   370
Publication Date:   04 August 1994
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Out of Print
Availability:   Out of print, replaced by POD  
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Table of Contents

General Introduction: M. Greenacre, Correspondence Analysis and its Interpretation. J. Blasius, Correspondence Analysis in Social Science Research. J. Blasius and M. Greenacre, Computation of Correspondence Analysis. P.G.M. van der Heijden, A. Mooijaart, and Y. Takane, Correspondence Analysis and Contingency Table Models. U. Bickenholt and Y. Takane, Linear Constraints in Correspondence Analysis. The BMS (K.M. van Meter, M.-A. Schiltz, P. Cibois, and L. Mounier), Correspondence Analysis: A History and French Sociological Perspective. Generalizations to Multivariate Data: M. Greenacre, Multiple and Joint Correspondence Analysis. L. Lebart, Complementary Use of Correspondence Analysis and Cluster Analysis. W.J. Heiser and J.J. Meulman, Homogeneity Analysis: Exploring the Distribution of Variables and their Nonlinear Relationships. J. Rovan, Visualizing Solutions in more than Two Dimensions. Analysis of Longitudinal Data: B. Martens, Analyzing Event History Data by Cluster Analysis and Multiple Correspondence Analysis: An example using data about work and occupations of scientists and engineers. V. Thiessen, H. Rohlinger, and J. Blasius, The Significance of Minor Changes in Panel Data: A correspondence analysis of the division of household tasks. T. Muller-Schneider, The Visualization of Structural Change by Means of Correspondence Analysis. Further Applications of Correspondence Analysis in Social Science Research: H. Giegler and H. Klein, Correspondence Analysis of Textual Data from Personal Advertisements. U. Wuggenig and P. Mnich, Explorations in Social Spaces: Gender, Age, Class Fractions and Photographical Choices of Objects. H.M.J.J. (Dirk) Snelders and M.J.W. Stokmans, Product Perception and Preference in Consumer Decision-making. References. Index.

Reviews

""This volume is particularly noteworthy for the chapters stressing computations and historical perspectives. There are many interesting data sets as well as detailed analyses."" --JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

This volume is particularly noteworthy for the chapters stressing computations and historical perspectives. There are many interesting data sets as well as detailed analyses. --JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

This volume is particularly noteworthy for the chapters stressing computations and historical perspectives. There are many interesting data sets as well as detailed analyses. --JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Author Information

Michael J. Greenacre is Professor of Statistics at the University of South Africa. He has been involved with the theoretical development and practical applications of correspondence analysis in the USA, UK, South Africa and Germany. Previous publications include Theory and Applications of Correspondence Analysis (Academic Press, 1984) and Correspondence Analysis in Practice (Academic Press, 1993). Jorg Blasius is Researcher at the Zentralarchiv fur empirische Sozialforschung at the University of Cologne. His primary research interests are multivariate exploratory analysis, urban research, life-styles and methods of empirical social research.

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