<b>Praise for the First Edition</b> <p> <p> "This is a superb text from which to teach categorical data analysis, at a variety of levels. . . [t]his book can be very highly recommended."<br> &#8212;<i>Short Book Reviews</i> <p> "Of great interest to potential readers is the variety of fields that are represented in the examples: health care, financial, government, product marketing, and sports, to name a few."<br> &#8212;<i>Journal of Quality Technology</i> <p> "Alan Agresti has written another brilliant account of the analysis of categorical data."<br> &#8212;<i>The Statistician</i> <p> The use of statistical methods for categorical data is ever increasing in today's world. <i>An Introduction to Categorical Data Analysis</i>, Second Edition provides an applied introduction to the most important methods for analyzing categorical data. This new edition summarizes methods that have long played a prominent role in data analysis, such as chi-squared tests, and also places special emphasis on logistic regression and other modeling techniques for univariate and correlated multivariate categorical responses. <p> <b>This Second Edition features:</b> <ul> <li>Two new chapters on the methods for clustered data, with an emphasis on generalized estimating equations (GEE) and random effects models <li>A unified perspective based on generalized linear models <li>An emphasis on logistic regression modeling <li>An appendix that demonstrates the use of SAS&#174; for all methods <li>An entertaining historical perspective on the development of the methods <li>Specialized methods for ordinal data, small samples, multicategory data, and matched pairs <li>More than 100 analyses of real data sets and nearly 300 exercises </ul> <p> Written in an applied, nontechnical style, the book illustrates methods using a wide variety of real data, including medical clinical trials, drug use by teenagers, basketball shooting, horseshoe crab mating, environmental opinions, correlates of happiness, and much more. <p> <i>An Introduction to Categorical Data Analysis</i>, Second Edition is an invaluable tool for social, behavioral, and biomedical scientists, as well as researchers in public health, marketing, education, biological and agricultural sciences, and industrial quality control.