By Alan Agresti
- Publisher: Wiley-Interscience
- Number Of Pages: 734
- Publication Date: 2002-07-22
- ISBN-10 / ASIN: 0471360937
- ISBN-13 / EAN: 9780471360933
- Binding: Hardcover
Product Description:
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 classic Categorical 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 effects Stronger emphasis on logistic regression modeling of binary and multicategory data An appendix showing the use of SAS for conducting nearly all analyses in the book Prescriptions for how ordinal variables should be treated differently than nominal variables Discussion of exact small-sample procedures More than 100 analyses of real data sets to illustrate application of the methods, and more than 600 exercises Summary: The source to understand categorical data and moreRating: 5The text is comprehensive in covering categorical data. Other reviews make this clear so I wanted to focus on the following. I was able to understand more general topics in statistics because of Agresti's depth of coverage on CDA. For example, for repeated measurements, Agresti clearly explains marginal models, conditional models, and generalized estimating equations. When I needed to understand these topics, I used this text because I have not found clear explanations elsewhere. In addition, SAS code and R code is available for the examples presented. Summary: the masterpiece by the masterRating: 5When this book came out in 1990 it was the first book to provide a truely modern treatment of categorical data analysis for both ordinal and nominal data. It provides an excellent treatment of the asymptotic theory for binary and multinomial data. It is extremely well written and is still a favorite of statisticians and practitioners. Because of its popularity and continued value, it should soon be added to the Wiley Classic series. This is the first book to take the regression approach to categorical data analysis tieing the subject to the methods and theory of the generalized linear models. It also was one of the first to show the modern practicality of exact permutation methods. The only drawback of this book is that it is 11 years old and there have been many interesting and relevant research developments in computer-intensive methods, analysis of missing data and mixed effects linear models to make a revision useful. Some of the latest developments can be found in Lloyd's new book "Statistical Analysis of Categorical Data" that was recently published by Wiley. Agresti provides clear advice and also gives a nice historical perspective on the development of the subject. The book is authoritative and includes numerous relevant references. Each chapter contains many exercises and a wealth of practical examples for illustration of the techniques. This is a good text from both practical and theoretical perspectives. It is excellent for a graduate level course on categorical data analysis. Summary: Dense and comprehensiveRating: 4Please read this in addition to the other reviews! I agree with the other reviewers except on one aspect: I found the style of writing a little bit choppy at times. The author uses short sentences when a few connecting words like e.g. "because", "due to", would have made understanding a little easier. Also, examples are not integrated optimally into the text so that there seems to be a gap between abstract conceptual explanations and the examples. Summary: The one to haveRating: 5If you want one book on Categorical Data analysis, this is the one. But there are others that are easier to read, if your math is not great (including the same author's book with an almost identical title) Summary: Good reading, but how do I analyze my data?Rating: 2In the theoretical sense, this book provides a very thorough overview of categorical data analysis. However, this book should not be used as a reference for the scientist needing to do the occasional number crunching of categorical data. The examples are vague and the tests are not well explained. If you want to derive the tests, this book is for you. If you're not a statistician at heart and just want the answer, I suggest looking at Conover's "Practical Nonparametric Statistics" for a good explanation of which tests to use and how to use them.DOWNLOAD THIS BOOK
