An Introduction to Categorical Data Analysis, Second Edition

Agresti, Alan

ISBN 10: 0471226181 / ISBN 13: 9780471226185

Published by Wiley-Interscience, 2007

About this Item

Wiley-Interscience, 2007. New and unread in PERFECT condition. Square and tight. Sharp corners. NO owner's name or bookplate. NOT a remainder. Bookstore's electronic anti-theft device still attached to the rear pastedown endpaper. Pages are fresh, crisp, clean and unmarked -- obviously never read. This 2007 Second Edition is updated and expanded, including the addition of two new chapters dealing with the analysis of clustered correlated categorical data. Equations. Numerous tables. Two appendices. Bibliography. Index of examples. Subject index. Brief solutions to some odd-numbered problems. Bound in the original yellow and white laminated boards, printed in brown and white. . Second Edition, Updated and Expanded. Hardcover. NEW condition/No dust jacket, as issued. 8vo. xvii, 381pp. Great Packaging, Fast Shipping.

Seller Inventory # 031547

Bibliographic Details

• Title: An Introduction to Categorical Data Analysis, Second Edition
• Publisher: Wiley-Interscience
• Publication Date: 2007
• Language: English
• ISBN 10: 0471226181
• ISBN 13: 9780471226185
• Binding: Hardcover
• Edition: Second Edition, Updated and Expanded.
• Condition: NEW condition
• Dust Jacket Condition: No dust jacket, as issued
• Seller catalogs:
  • Mathematics
  • Science / Technology / Computers

About this title

Synopsis

Praise for the First Edition

"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 Statistician

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.

About the Author

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.