Categorical Data Analysis

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John Wiley & Sons, Mar 31, 2003 - Mathematics - 734 pages
7 Reviews
Amstat News asked three review editors to rate their topfive favorite books in the September 2003 issue. CategoricalData Analysis was among those chosen.

A valuable new edition of a standard reference

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

The use of statistical methods for categorical data hasincreased dramatically, particularly for applications in thebiomedical and social sciences. Responding to new developments inthe field as well as to the needs of a new generation ofprofessionals and students, this new edition of the classicCategorical Data Analysis offers a comprehensiveintroduction to the most important methods for categorical dataanalysis.

Designed for statisticians and biostatisticians as well asscientists and graduate students practicing statistics,Categorical Data Analysis, Second Edition summarizes thelatest methods for univariate and correlated multivariatecategorical responses. Readers will find a unified generalizedlinear models approach that connects logistic regression andPoisson and negative binomial regression for discrete data withnormal regression for continuous data. Adding to the value in thenew edition is coverage of:

  • Three new chapters on methods for repeated measurement andother forms of clustered categorical data, including marginalmodels and associated generalized estimating equations (GEE)methods, and mixed models with random effects
  • Stronger emphasis on logistic regression modeling of binaryand multicategory data
  • An appendix showing the use of SAS for conducting nearly allanalyses in the book
  • Prescriptions for how ordinal variables should be treateddifferently than nominal variables
  • Discussion of exact small-sample procedures
  • More than 100 analyses of real data sets to illustrateapplication of the methods, and more than 600 exercises
  • An Instructor's Manual presenting detailed solutions to allthe problems in the book is available from the Wiley editorialdepartment.
 

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Great book!

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This book is absoultely brillant. It's a very well organized text, and concepts are presented about as clearly as I've ever seen a textbook present them. I would go as far as to call this book the bible of categorical data.
I'm working as a professional statistician for about a year, but I seem to refer back to this book for some use on at least a monthly basis.
 

Contents

1 Introduction Distributions and Inference for Categorical Data
1
2 Describing Contingency Tables
36
3 Inference for Contingency Tables
70
4 Introduction to Generalized Linear Models
115
5 Logistic Regression
165
6 Building and Applying Logistic Regression Models
211
7 Logit Models for Multinomial Responses
267
8 Loglinear Models for Contingency Tables
314
13 Other Mixture Models for Categorical Data
538
14 Asymptotic Theory for Parametric Models
576
15 Alternative Estimation Theory for Parametric Models
600
16 Historical Tour of Categorical Data Analysis
619
Appendix A Using Computer Software to Analyze Categorical Data
632
Appendix B ChiSquared Distribution Values
654
References
655
Examples Index
689

9 Building and Extending LoglinearLogit Models
357
10 Models for Matched Pairs
409
11 Analyzing Repeated Categorical Response Data
455
12 Random Effects Generalized Linear Mixed Models for Categorical Responses
491
Author Index
693
Subject Index
701
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About the author (2003)

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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