Categorical Data Analysis (Wiley Series in Probability and Statistics)
 
 
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Categorical Data Analysis (Wiley Series in Probability and Statistics) [Hardcover]

Alan Agresti
4.3 out of 5 stars  See all reviews (11 customer reviews)


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Editorial Reviews

Review

“…the essential reference text for statisticians…comprehensive and readable…” (Statistical Methods in Medical Research, Vol. 14, 2005)

"...careful, thorough, up-to-date volume...the new content and emphases in the second edition are sufficient to justify its purchase even by someone who already owns the first edition." (Journal of the American Statistical Association, June 2004)

"I liked this revised edition and recommend it highly to statisticians and graduate students." (Journal of Statistical Computation & Simulation, March 2004)

"...a highly satisfactory text on methods for categorical response variables...more complete and technical [than the First Edition]..." (IIE Transactions on Quality and Reliability Engineering)

"If you own the 1E, you absolutely need to upgrade to the 2E. If you do any analysis of categorical data, this is an essential desktop reference..." (Technometrics, Vol. 45, No. 1, February 2003)

"...this classic book is substantially modified and expanded..." (International Journal of General Systems, Vol. 32, 2003)

"...it is a total delight reading this book, which should be considered as the current standard textbook for teaching analysis of categorical data." (Pharmaceutical Research, Vol. 20, No. 6, June 2003)

"...written in a highly scientific but vivid style, intelligible for all researchers in that field...simply expressed, grand..." (Zentralblatt Math, 2004)

From the Publisher

Summarizes methods used for the analysis of categorical data, including many recently developed techniques. The emphasis is on loglinear and logit modeling techniques, which share many features with linear model methods for continuous variables. Incorporated into the exposition is interesting historical information (and controversies) on the development of categorical data analysis. Chapters 1-7 cover bivariate categorical data and loglinear and logit model building; chapters 8-11 discuss applications and methods; chapters 12 and 13 address theoretical foundations. --This text refers to an out of print or unavailable edition of this title.

From the Inside Flap

The past quarter-century has seen an explosion in the development of methods for analyzing categorical data. These methods have influenced—and been influenced by—the increasing availability of multivariate data sets with categorical responses in the social, behavioral, and biomedical sciences, as well as in public health, ecology, education, marketing, food science, and industrial quality control. Categorical Data Analysis describes the most important new methods, offering a unified presentation of modeling using generalized linear models and emphasizing loglinear and logit modeling techniques. Contributions of noted statisticians (Pearson, Yule, Fisher, Neyman, Cochran), whose pioneering efforts set the pace for the evolution of modern methods, are examined as well. Special features of the book include:
  • Coverage of methods for repeated measurement data, which have become increasingly important in biomedical applications
  • Prescriptions for how ordinal variables should be treated differently than nominal variables
  • Derivations of basic asymptotic and fixed-sample-size inferential methods
  • Discussion of exact small sample procedures
  • More than 40 examples of analyses of "real" data sets, including: aspirin use and heart disease; job satisfaction and income; seat belt use and injuries in auto accidents; and predicting outcomes of baseball games
  • More than 400 exercises to facilitate interpretation and application of methods
Categorical Data Analysis also contains an appendix that describes the use of computer software currently available for performing the analyses presented in the book. A comprehensive bibliography and notes at the end of each chapter round out the work, making it a complete, invaluable reference for statisticians, biostatisticians, and professional researchers. --This text refers to an out of print or unavailable edition of this title.

From the Back Cover

A valuable new edition of a standard reference

"A 'must-have' book for anyone expecting to do research and/or applications in categorical data analysis."
Statistics in Medicine on Categorical Data Analysis, First Edition

The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. Responding to new developments in the field as well as to the needs of a new generation of professionals and students, this new edition of the classic Categorical Data Analysis offers a comprehensive introduction to the most important methods for categorical data analysis.

Designed for statisticians and biostatisticians as well as scientists and graduate students practicing statistics, Categorical Data Analysis, Second Edition summarizes the latest methods for univariate and correlated multivariate categorical responses. Readers will find a unified generalized linear models approach that connects logistic regression and Poisson and negative binomial regression for discrete data with normal regression for continuous data. Adding to the value in the new edition is coverage of:

  • Three new chapters on methods for repeated measurement and other forms of clustered categorical data, including marginal models and associated generalized estimating equations (GEE) methods, and mixed models with random effects
  • Stronger emphasis on logistic regression modeling of binary and multicategory data
  • An appendix showing the use of SAS for conducting nearly all analyses in the book
  • Prescriptions for how ordinal variables should be treated differently than nominal variables
  • Discussion of exact small-sample procedures
  • More than 100 analyses of real data sets to illustrate application of the methods, and more than 600 exercises

About the Author

ALAN AGRESTI, PhD, is Distinguished Professor in the Department of Statistics at the University of Florida. He has published extensively on categorical data methods and has presented courses on the topic for universities, companies, and professional organizations worldwide. A Fellow of the American Statistical Association, he is also the author of two other Wiley texts on categorical data analysis and coauthor of Statistical Methods for the Social Sciences.
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