Concise, complete, nontechnical; the ideal introduction to an increasingly important topic In recent years, the use of statistical methods for categorical data has increased dramatically in a variety of areas and applications. This book provides an applied introduction to the most important methods for analyzing categorical data. It summarizes methods that have long played a prominent role, such as chi-squared tests, but places special emphasis on logistic regression and loglinear modeling techniques.
Special features of the book include:
Emphasis on logistic regression modeling of binary data and Poisson regression modeling of count data
A unified perspective, based on generalized linear models, that connects these methods with standard regression methods for normally-distributed data
An appendix showing the use of a new SAS procedure (GENMOD) for generalized linear modeling that can conduct nearly all methods presented in the book
An entertaining historical perspective of the development of the methods
Specialized methods for ordinal data, small samples, multicategory data, and matched pairs
More than 100 examples of real data sets and more than 200 exercises
Writing in an applied, nontechnical style, Alan Agresti illustrates methods using a wide variety of real data, including alcohol, cigarette, and marijuana use by teenagers; AZT use and delay of AIDS; space shuttle launches and O-ring failure; passive smoking and lung cancer; and much more. An Introduction to Categorical Data Analysis is an invaluable tool for social, behavioral, and biomedical scientists, as well as researchers in public health, marketing, education, biological and agricultural sciences, and industrial quality control.
An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
"synopsis" may belong to another edition of this title.
A non-technical introductory featuring the most important techniques for analyzing categorical data such as classical inferences for two-and-three way contingency tables, logistic regression, log linear models and matched-pairs data. Contains more than 200 exercises and more than 100 examples of authentic data sets. An appendix describes the use of computer packages to perform analyses in the text.About the Author:
ALAN AGRESTI is a professor in the Department of Statistics at the University of Florida. He has published extensively and has served on the editorial boards of several journals. He is the author of two advanced texts, including the bestselling Categorical Data Analysis, and the coauthor of Statistical Methods for the Social Sciences.
"About this title" may belong to another edition of this title.
Book Description Wiley-Interscience, 1996. Hardcover. Book Condition: New. 1. Bookseller Inventory # DADAX0471113387
Book Description Wiley-Interscience, 1996. Hardcover. Book Condition: New. Never used!. Bookseller Inventory # P110471113387
Book Description John Wiley & Sons Inc 1996, 1996. Book Condition: New. New hardback cover but cover is dented and edges bumped. Content fine and unread. Bookseller Inventory # A20346
Book Description Wiley-Interscience. Hardcover. Book Condition: New. 0471113387 New Condition. Bookseller Inventory # NEW7.0182450