An Introduction to Categorical Data Analysis (Wiley Series in Probability and Statistics) by Alan Agresti offers a comprehensive guide to statistical methods for categorical data, making it an invaluable resource for students and professionals in the biomedical and social sciences. The third edition of this text continues to summarize these methodologies while demonstrating their practical application through the use of R software. A unified generalized linear models approach is presented, linking logistic regression and loglinear models for discrete data with normal regression for continuous data.

The new edition introduces several enhancements, including:

• A dedicated chapter on alternative methods for categorical data analysis, such as smoothing and regularization techniques (like the lasso), classification methods such as linear discriminant analysis and decision trees, and cluster analysis
• Additional sections in many chapters that introduce Bayesian approaches to the discussed methods
• More than 70 analyses of real data sets to illustrate the application of the methods, along with approximately 200 exercises, which include other data sets for practice

This book serves as both a textbook and a practical reference, equipping readers with the knowledge and tools necessary to effectively analyze categorical data in various fields.