An Introduction to Categorical Data Analysis - Rilegato

"This is a superb text from which to teach categorical dataanalysis, at a variety of levels. . . [t]his book can be veryhighly recommended."
—Short Book Reviews

"Of great interest to potential readers is the variety of fieldsthat are represented in the examples: health care, financial,government, product marketing, and sports, to name a few."
—Journal of Quality Technology

"Alan Agresti has written another brilliant account of theanalysis of categorical data."
—The Statistician

The use of statistical methods for categorical data is everincreasing in today's world. An Introduction to Categorical DataAnalysis, Second Edition provides an applied introduction tothe most important methods for analyzing categorical data. This newedition summarizes methods that have long played a prominent rolein data analysis, such as chi-squared tests, and also placesspecial emphasis on logistic regression and other modelingtechniques for univariate and correlated multivariate categoricalresponses.

This Second Edition features:

• Two new chapters on the methods for clustered data, with anemphasis on generalized estimating equations (GEE) and randomeffects models
• A unified perspective based on generalized linear models
• An emphasis on logistic regression modeling
• An appendix that demonstrates the use of SAS(r) for allmethods
• An entertaining historical perspective on the development ofthe methods
• Specialized methods for ordinal data, small samples,multicategory data, and matched pairs
• More than 100 analyses of real data sets and nearly 300exercises

Written in an applied, nontechnical style, the book illustratesmethods using a wide variety of real data, including medicalclinical trials, drug use by teenagers, basketball shooting,horseshoe crab mating, environmental opinions, correlates ofhappiness, and much more.

An Introduction to Categorical Data Analysis, SecondEdition is an invaluable tool for social, behavioral, andbiomedical scientists, as well as researchers in public health,marketing, education, biological and agricultural sciences, andindustrial quality control.