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An introduction to categorical data analysis. 3rd edition. (English) Zbl 1407.62001

Wiley Series in Probability and Statistics. Hoboken, NJ: John Wiley & Sons (ISBN 978-1-119-40526-9/hbk). xiii, 375 p. (2018).
Publisher’s description: The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. The book summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data.
Adding to the value in the new edition is:
Illustrations of the use of R software to perform all the analyses in the book
A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis
New sections in many chapters introducing the Bayesian approach for the methods of that chapter
More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets
An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises
Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more.
An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.
See the review of the first edition in [Zbl 0868.62008]. For the second edition see [Zbl 1266.62008].

MSC:

62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics
62J12 Generalized linear models (logistic models)
62H12 Estimation in multivariate analysis
62H30 Classification and discrimination; cluster analysis (statistical aspects)
62F15 Bayesian inference
62-07 Data analysis (statistics) (MSC2010)
62P10 Applications of statistics to biology and medical sciences; meta analysis

Software:

R; SAS; SPSS; Stata
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