Visualization of Categorical DataBy
- Jörg Blasius, Zentralarchiv fur empirische Sozialforschung
- Michael Greenacre, University of South Africa, Pretoria
Anyone who collects and organizes categorical data; researchers and students in the social sciences (i.e. sociology), marketing and political science.
Published: January 1998
Imprint: Academic Press
- 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.