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This book is about the analysis of categorical data with special emphasis on applications in economics, political science and the social sciences. The book gives a brief theoretical introduction to log-linear modeling of categorical data, then gives an up-to-date account of models and methods for the statistical analysis of categorical data, including recent developments in logistic regression models, correspondence analysis and latent structure analysis. Also treated are the RC association models brought to prominence in recent years by Leo Goodman. New statistical features like the use of association graphs, residuals and regression diagnostics are carefully explained, and the theory and methods are extensively illustrated by real-life data. The book introduces readers to the latest developments in categorical data analysis, and are shown how real life data can be analysed, how conclusions are drawn and how models are modified.
Categorical Data
Preliminaries
Statistical Inference
Two-way Contingency Tables
Three-way Contingency Tables
Multi-dimensional Contingency Tables
Incomplete Tables, Separability and Collapsibility
The Logit Model
Logistic Regression Analysis
Models for the Interactions
Correspondance Analysis
Latent Structure Analysis