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"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."
—Short Book Reviews
"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."
—Journal of Quality Technology
"Alan Agresti has written another brilliant account of the analysis of categorical data."
The use of statistical methods for categorical data is ever increasing in today's world. An Introduction to Categorical Data Analysis, 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.
This Second Edition features:
Two new chapters on the methods for clustered data, with an emphasis on generalized estimating equations (GEE) and random effects 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 all methods
An entertaining historical perspective on the development of the methods
Specialized methods for ordinal data, small samples, multicategory data, and matched pairs
More than 100 analyses of real data sets and nearly 300 exercises
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.
An Introduction to Categorical Data Analysis, 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.
"Yes, I fully recommend the text as a basis for introductory course, for students, as well as non-specialists in statistics. The wealth of examples provided in the text is, from my point of view, a rich source of motivating ones own studies and work." (Biometrical Journal, December 2008)
"This text does a good job of achieving its state goal, and we enthusiastically recommend it." (Journal of the American Statistical Association, September 2008)
"This book is very well-written and it is obvious that the author knows the subject inside out." (Journal of Applied Statistics, April 2008)
"Provides an applied introduction to the most important methods for analyzing categorical data, such as chi-squared tests and logical regression." (Statistica 2008)
"This is an introductory book and as such it is marvelous...essential for a novice..." (MAA Reviews, June 26, 2007)
ALAN AGRESTI, PhD, is Distinguished Professor Emeritus in the Department of Statistics at the University of Florida. He has presented short courses on categorical data methods in thirty countries. Dr. Agresti was named "Statistician of the Year" by the Chicago chapter of the American Statistical Association in 2003. He is the author of two advanced texts, including the bestselling Categorical Data Analysis (Wiley) and is also the coauthor of Statistics: The Art and Science of Learning from Data and Statistical Methods for the Social Sciences.
This book adequately presents the material for a graduate level class I am currently taking on categorical analysis for non-math/stat majors. It is easier to read than many basic statistics books, but it relies on the reader to already understand a lot of that basic material.
This book has two irritating faults, high price and limited references. The subject index lacks several terms, or does not point to the first mention or definition of the terms it does include. The bibliography covers only two pages, and of course the only citation I tried to look up was not in the bibliography; however I did find over eight pages listing other textbooks offered by the publisher under the same series as this book, none of which included the previously mentioned citation from the text. A final gripe about reference shortcomings: even though z-scores are used, there is no look-up table; there is only one table: a single page for the Chi-square distribution from alpha = 0.250 to alpha = 0.001.
Thumbs up to the publisher for offering this textbook as an e-book, thumbs down for charging over 90% of the hardcover price for that e-book. Especially when that price is over $100.
This book is good enough, but get it used!!
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