Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue.Categorical Data Analysis was among those chosen.

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 classicCategorical 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 effectsStronger emphasis on logistic regression modeling of binary and multicategory dataAn appendix showing the use of SAS for conducting nearly all analyses in the bookPrescriptions for how ordinal variables should be treated differently than nominal variablesDiscussion of exact small-sample proceduresMore than 100 analyses of real data sets to illustrate application of the methods, and more than 600 exercisesAn Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

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.

Preface. 1. Introduction: Distributions and Inference for Categorical Data. 2. Describing Contingency Tables. 3. Inference for Contingency Tables. 4. Introduction to Generalized Linear Models. 5. Logistic Regression. 6. Building and Applying Logistic Regression Models. 7. Logit Models for Multinomial Responses. 8. Loglinear Models for Contingency Tables. 9. Building and Extending Loglinear/Logit Models. 10. Models for Matched Pairs. 11. Analyzing Repeated Categorical Response Data. 12. Random Effects: Generalized Linear Mixed Models for Categorical Responses. 13. Other Mixture Models for Categorical Data*. 14. Asymptotic Theory for Parametric Models. 15. Alternative Estimation Theory for Parametric Models. 16. Historical Tour of Categorical Data Analysis*. Appendix A. Using Computer Software to Analyze Categorical Data. Appendix B. Chi-Squared Distribution Values. References. Examples Index. Author Index. Subject Index.