Enter your mobile number below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
Getting the download link through email is temporarily not available. Please check back later.

  • Apple
  • Android
  • Windows Phone
  • Android

To get the free app, enter your mobile phone number.

Categorical Data Analysis (Wiley Series in Probability and Statistics) 2nd Edition

4.3 out of 5 stars 15 customer reviews
ISBN-13: 978-0471360933
ISBN-10: 0471360937
Why is ISBN important?
ISBN
This bar-code number lets you verify that you're getting exactly the right version or edition of a book. The 13-digit and 10-digit formats both work.
Scan an ISBN with your phone
Use the Amazon App to scan ISBNs and compare prices.
Have one to sell? Sell on Amazon
Buy used
$12.65
Condition: Used - Good
In Stock. Sold by dcgoodwill
Condition: Used: Good
Access codes and supplements are not guaranteed with used items.
36 Used from $12.63
+ $3.99 shipping
More Buying Choices
14 New from $34.86 36 Used from $12.63

There is a newer edition of this item:

Free Two-Day Shipping for College Students with Prime Student Free%20Two-Day%20Shipping%20for%20College%20Students%20with%20Amazon%20Student


The Amazon Book Review
The Amazon Book Review
Author interviews, book reviews, editors picks, and more. Read it now
click to open popover

Editorial Reviews

Review

“…the essential reference text for statisticians…comprehensive and readable…” (Statistical Methods in Medical Research, Vol. 14, 2005)

"...careful, thorough, up-to-date volume...the new content and emphases in the second edition are sufficient to justify its purchase even by someone who already owns the first edition." (Journal of the American Statistical Association, June 2004)

"I liked this revised edition and recommend it highly to statisticians and graduate students." (Journal of Statistical Computation & Simulation, March 2004)

"...a highly satisfactory text on methods for categorical response variables...more complete and technical [than the First Edition]..." (IIE Transactions on Quality and Reliability Engineering)

"If you own the 1E, you absolutely need to upgrade to the 2E. If you do any analysis of categorical data, this is an essential desktop reference..." (Technometrics, Vol. 45, No. 1, February 2003)

"...this classic book is substantially modified and expanded..." (International Journal of General Systems, Vol. 32, 2003)

"...it is a total delight reading this book, which should be considered as the current standard textbook for teaching analysis of categorical data." (Pharmaceutical Research, Vol. 20, No. 6, June 2003)

"...written in a highly scientific but vivid style, intelligible for all researchers in that field...simply expressed, grand..." (Zentralblatt Math, 2004)

From the Publisher

Summarizes methods used for the analysis of categorical data, including many recently developed techniques. The emphasis is on loglinear and logit modeling techniques, which share many features with linear model methods for continuous variables. Incorporated into the exposition is interesting historical information (and controversies) on the development of categorical data analysis. Chapters 1-7 cover bivariate categorical data and loglinear and logit model building; chapters 8-11 discuss applications and methods; chapters 12 and 13 address theoretical foundations. --This text refers to an out of print or unavailable edition of this title.
NO_CONTENT_IN_FEATURE

New York Times best sellers
Browse the New York Times best sellers in popular categories like Fiction, Nonfiction, Picture Books and more. See more

Product Details

  • Series: Wiley Series in Probability and Statistics (Book 359)
  • Hardcover: 734 pages
  • Publisher: Wiley-Interscience; 2 edition (July 22, 2002)
  • Language: English
  • ISBN-10: 0471360937
  • ISBN-13: 978-0471360933
  • Product Dimensions: 6.5 x 1.5 x 9.5 inches
  • Shipping Weight: 2.4 pounds
  • Average Customer Review: 4.3 out of 5 stars  See all reviews (15 customer reviews)
  • Amazon Best Sellers Rank: #1,075,505 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

By Michael R. Chernick on January 23, 2008
Format: Hardcover
When 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.
Comment 29 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse
Format: Hardcover
This is a very demanding, thorough, and clear description of just about everything anyone could want to know on the subject. The second edition is considerably more rigorous than the first. Agresti stresses that logistic models are one kind of generalized linear model. This offers solid connections to many other models, but places corresponding demands on the reader. In particular, Chapter 4 is difficult going, but might be skipped or skimmed on first reading.
Given the mathematical level and rigor, this is a remarkably clear book. Anyone who analyzes categorical data on a regular basis should read it and have it on his or her shelf.
Comment 32 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse
Format: Hardcover
In 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.
2 Comments 21 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse
Format: Hardcover Verified Purchase
This is an excellent book on categorical analysis. My advice to anyone planning to use this book is to study the first 4 chapters very carefully and very thoroughly. These chapters form the heart of the analysis, and describe the tests that follow in the most general setting. After the first 4 are done, go through chapters 5 and 6, and you will realize that logistic regression is a special case of the results you have already learned. The rest of the book is best used as a reference (in my opinion) and one can look into the relevant sections as needed.

The 2 important things reading this book has taught me to look for are (1) the role of cofounders in categorical analysis (see the example in section 2.3.2 for an illustration) and (2) effective groupings, when one of the entries in the contingency table is scarce
Comment Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse
Format: Hardcover
The 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.
Comment 2 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse
Format: Hardcover Verified Purchase
Please 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.
Comment 5 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse
Format: Hardcover
If 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)
Comment 3 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse
By tmb2118 on February 20, 2009
Format: Hardcover
This book is the standard for this material. It is clear, concise and comes with enough examples to assure the reader of the empirical importance of all the theory.
Comment One person found this helpful. Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse