Visualization of Categorical Data - 1st Edition - ISBN: 9780122990458, 9780080543628

Visualization of Categorical Data

1st Edition

Authors: Jörg Blasius Michael Greenacre
Hardcover ISBN: 9780122990458
eBook ISBN: 9780080543628
Imprint: Academic Press
Published Date: 8th January 1998
Page Count: 594
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A unique and timely monograph, Visualization of Categorical Data contains a useful balance of theoretical and practical material on this important new area. Top researchers in the field present the books four main topics: visualization, correspondence analysis, biplots and multidimensional scaling, and contingency table models.

This volume discusses how surveys, which are employed in many different research areas, generate categorical data. It will be of great interest to anyone involved in collecting or analyzing categorical data.

Key Features

@bul:* Correspondence Analysis

  • Homogeneity Analysis
  • Loglinear and Association Models
  • Latent Class Analysis
  • Multidimensional Scaling
  • Cluster Analysis
  • Ideal Point Discriminant Analysis
  • Formal Concept Analysis
  • Graphical Models


Anyone who collects and organizes categorical data; researchers and students in the social sciences (i.e. sociology), marketing and political science.

Table of Contents

J. de Leeuw, Keynote Chapter: Heres Looking at Multivariables. Graphics for Visualization: M. Friendly, Conceptual Models for Visualizing Contingency Table Data. J.-H. Chauchat and A. Risson, BERTINs Graphics and Multidimensional Data Analysis Methods. B. Francis, M. Fuller, and J. Pritchard, The Use of Visualization in the Examination of Categorical Event Histories. T. Aluja-Banet and E. Nafroa, General Impurity and Data Diagnostics in Decision Trees. U. Frick, J. Rehm, K.E. Wolff, and M. Laschat, Obstetricians Attitudes on Perinatal Risk: The Role of Quantitative and Conceptual Scaling Procedures. K.E. Wolff and S. Gabler, Comparison of Visualizations in Formal Concept Analysisand Correspondence Analysis. V. Choulakian and J. Allard, The Z-Plot: A Graphical Procedure for Contingency Tables with an Ordered Response Variable. Correspondence Analysis: I. Partchev, Using Visualization Techniques to Explore Bulgarian Politics. B. Martens and J. Kastl, Visualization of Agenda Building Processes by Correspondence Analysis. L. Lebart, Visualizations of Textual Data. M.B. Bertaut Visualization of Open Questions: French Study of Pupils Attitudes to Mathematics. F. Fehlen, The Cloud of Candidates. Exploring the Political Field. C. Tarnai and U. Wuggenig, Normative Integration of the Avant-garde? Traditionalism in the Art Fields of Vienna, Hamburg, and Paris. S. Nishisato, Graphing is Believing: Interpretable Graphs for Dual Scaling. B. Le Roux and H. Rouanet, Interpreting the Axes in Multiple Correspondence Analysis: Method of the Contributions of Points and Deviations. M. Greenacre, Diagnostics for Joint Displays in Correspondence Analysis. V. Thiessen and J. Blasius, Using Multiple Correspondence Analysis to Distinguish between Substantive and Non-Substantive Responses. A. Carlier and P.M. Kroonenberg, The Case of the French Cantons: An Application of Three-Way Correspondence Analysis. J.J. Meulman and W.J. Heiser, Visual Display of Interaction in Multiway Contingency Tables by Homogeneity in Analysis: the 2 x 2 x 2 Case. S. Balbi, Graphical Displays in Non-Symmetric Correspondence Analysis. R.Siciliano and F. Mola, Ternary Classification Trees: A Factorial Approach. Multidimensional Scaling and Biplot: A. Kimball Ronney, C.C. Moore, and T.J. Brazill, Correspondence Analysis as A Multidimensional Scaling Technique for Non-Frequency Similarity Matrices. I. Borg and P.J.F. Groenen, Regional Interpretations in Multidimensional Scaling. C.M. Cuadras and J. Fortiana, Visualizing Categorical Data with Related Metric Scaling. M. Vuylsteke-Wauters, J. Billiet, H. De Witte,and F. Symons, Contrasting the Electorates of Eight Political Parties: A Visual Presentation Using the Biplot. K. Ruben Gabriel, M. Purificacion Galindo, and J.L. Vicente-Villardon, Use of Biplots to Diagnose Independence Models in Three-Way Contingency Tables. J.C. Gower and S.A. Harding, Prediction Regions for Categorical Variables. Visualization in Modeling: C.C. Clogg, T. Rudas, and S. Matthews, Analysis of Contingency Tables Using Graphical Displays Based on the Mixture Index of Fit. Y. Takane, Visualization in Ideal Point Discriminant Analysis. U. Bickenholt, Modeling Time-Dependent Preferences: Drifts in Ideal Points. A.L. McCutcheon, Correspondence Analysis Used Complementary to Latent Class Analysis in Comparative Social Research. L. Andries van der Ark and P.G.M. van der Heijden, Graphical Display of Latent Class Analysis, with Special Reference to Correspondence Analysis. J. Magidson, Using New General Ordinal Logit Displays to Visualizethe Effects in Categorical Outcome Data. A. de Falguerolles, Log-bilinear Biplots in Action. References. Index.


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© Academic Press 1998
Academic Press
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About the Author

Jörg Blasius

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.

Affiliations and Expertise

Zentralarchiv fur empirische Sozialforschung

Michael Greenacre

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).

Affiliations and Expertise

University of South Africa, Pretoria