Analyzing contingency tables -- Generalized linear models -- Logistic regression -- Building and applying binary regression models -- Multicategory logit models -- Loglinear models for contingency tables and counts -- Models for matched pairs -- Marginal modeling of correlated, clustered responses -- Random effects : generalized linear mixed models -- Classification and smoothing -- A historical tour of categorical data analysis.
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"A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data"--Publisher's description.