An Introduction to Categorical Data Analysis

<p><b>A valuable new edition of a standard reference</b></p> <p>The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. <i>An Introduction to Categorical Data Analysis, Third Edition</i> 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.</p> <p>Adding to the value in the new edition is:</p> <p>• Illustrations of the use of R software to perform all the analyses in the book</p> <p>• 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</p> <p>• New sections in many chapters introducing the Bayesian approach for the methods of that chapter</p> <p>• More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets</p> <p>• An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises</p> <p>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.</p> <p><i>An Introduction to Categorical Data Analysis, Third Edition</i> 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.</p>