PDF Ebook Categorical Data Analysis, (Wiley Series in Probability and Mathematical Statistics, Applied Probability and Statistics), by Alan Agresti
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Categorical Data Analysis, (Wiley Series in Probability and Mathematical Statistics, Applied Probability and Statistics), by Alan Agresti
PDF Ebook Categorical Data Analysis, (Wiley Series in Probability and Mathematical Statistics, Applied Probability and Statistics), by Alan Agresti
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Categorical Data Analysis describes the most important methods, offering a unified presentation of modeling using generalized linear models and emphasizing loglinear and logit modeling techniques. Contributions of noted statisticians (Pearson, Yule, Fisher, Neyman, Cochran), whose pioneering efforts set the pace for the evolution of modern methods, are examined as well.
Special features of the book include:
- Coverage of methods for repeated measurement data, which have become increasingly important in biomedical applications
- Prescriptions for how ordinal variables should be treated differently than nominal variables
- Derivations of basic asymptotic and fixed-sample-size inferential methods
- Discussion of exact small sample procedures
- More than 40 examples of analyses of "real" data sets, including: aspirin use and heart disease; job satisfaction and income; seat belt use and injuries in auto accidents; and predicting outcomes of baseball games
- More than 400 exercises to facilitate interpretation and application of methods
Categorical Data Analysis also contains an appendix that describes the use of computer software currently available for performing the analyses presented in the book. A comprehensive bibliography and notes and the end of each chapter round out the work, making it a complete, invaluable reference for statisticians, biostatisticians and professional researchers.
- Sales Rank: #829616 in Books
- Published on: 1990-03
- Original language: English
- Number of items: 1
- Dimensions: 9.33" h x 1.29" w x 6.24" l, .0 pounds
- Binding: Hardcover
- 576 pages
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.
From the Inside Flap
The past quarter-century has seen an explosion in the development of methods for analyzing categorical data. These methods have influenced—and been influenced by—the increasing availability of multivariate data sets with categorical responses in the social, behavioral, and biomedical sciences, as well as in public health, ecology, education, marketing, food science, and industrial quality control. Categorical Data Analysis describes the most important new methods, offering a unified presentation of modeling using generalized linear models and emphasizing loglinear and logit modeling techniques. Contributions of noted statisticians (Pearson, Yule, Fisher, Neyman, Cochran), whose pioneering efforts set the pace for the evolution of modern methods, are examined as well. Special features of the book include:
- Coverage of methods for repeated measurement data, which have become increasingly important in biomedical applications
- Prescriptions for how ordinal variables should be treated differently than nominal variables
- Derivations of basic asymptotic and fixed-sample-size inferential methods
- Discussion of exact small sample procedures
- More than 40 examples of analyses of "real" data sets, including: aspirin use and heart disease; job satisfaction and income; seat belt use and injuries in auto accidents; and predicting outcomes of baseball games
- More than 400 exercises to facilitate interpretation and application of methods
Most helpful customer reviews
29 of 29 people found the following review helpful.
the masterpiece by the master
By Michael R. Chernick
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.
32 of 33 people found the following review helpful.
A classic, made even better
By Peter Flom
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.
7 of 7 people found the following review helpful.
DON'T BUY THIS BOOK
By Grad Student
A friend of mine bought this book under the false impression that it was the full edition of Agrestis Intro. Categorical Data Analysis book. This was mostly Amazon's fault, as when you clicked on the 'look inside' link for the book, the pages displayed were actually from Agresti's book and not the study guide. Also the reviews were for Agresti's book - NOT the study guide. Now to the 'book' - I think it's a stretch to even call it a book - itself. It consists of a list of definitions of terms used in Agresti's book, and 30 pages of 'scratch' paper. As far as I can see, the definitions (some of which are wrong, circular and many are badly typeset) do nothing to elucidate the material in Agresti's book. To me, it looks like somebody who knew nothing about statistics highlighed some words in Agresti's book and told a math major to define these terms. That is the content of this 'book'.
Don't waste your money. If I could give this book 0 stars I would. It seems a money-making scheme if you ask me.
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