Correspondence Analysis in the Social Sciences

Correspondence Analysis in the Social Sciences : Recent Developments and Applications

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Description

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.
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Product details

  • Hardback | 370 pages
  • 152.4 x 231.14 x 27.94mm | 680.39g
  • Academic Press Inc
  • San Diego, United States
  • English
  • 0121045706
  • 9780121045708

Back cover copy

Correspondence analysis is a multivariate method for exploring cross-tabular data by converting such tables into graphical displays, called 'maps', and related numerical statistics. Since cross-tabulations are so often produced in the course of social science research, correspondence analysis is valuable in understanding the information contained in these tables. This book fills the gap in the literature between the theory and practice of this method. 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. The first part of the book deals with basic concepts of correspondence analysis and related methods for analyzing cross-tabulations. It then looks at the multivariate case when there are several variables of interest, including the relationship to cluster analysis, factor analysis and reliability of measurement. Applications to longitudinal data: event history data, panel data and trend data are demonstrated. Finally, it examines further applications in the social sciences, including the analysis of textual data, lifestyle data and data on product descriptions in marketing research. Correspondence Analysis in the Social Sciences gives lecturers, researchers and students a detailed introduction to help them teach the method and apply it to their own research problems. Researchers in psychology, sociology, business, marketing and statistics will all find this book particularly useful.
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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.
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Review quote

"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
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About Jorg Blasius

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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