The first edition of this text has sold over 19,600 copies. However, the use of statistical methods for categorical data has increased dramatically in recent years, particularly for applications in the biomedical and social sciences. A second edition of the introductory version of the book will suit it nicely. Wiley also published a second edition of Categorical Data Analysis, which is an advanced, more technical text, in 2003.
"synopsis" may belong to another edition of this title.
From the Publisher:
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.
From the Back Cover:
Praise for the First Edition
"This is a superb text from which to teach categorical data analysis, at a variety of levels. . . [t]his book can be very highly recommended."
―Short Book Reviews
"Of great interest to potential readers is the variety of fields that are represented in the examples: health care, financial, government, product
marketing, and sports, to name a few."
―Journal of Quality Technology
"Alan Agresti has written another brilliant account of the analysis of categorical data."
―The Statistician
The use of statistical methods for categorical data is ever increasing in today's world. An Introduction to Categorical Data Analysis, Second Edition provides an applied introduction to the most important methods for analyzing categorical data. This new edition summarizes methods that have long played a prominent role in data analysis, such as chi-squared tests, and also places special emphasis on logistic regression and other modeling techniques for univariate and correlated multivariate categorical responses.
This Second Edition features:
- Two new chapters on the methods for clustered data, with an emphasis on generalized estimating equations (GEE) and random effects models
- A unified perspective based on generalized linear models
- An emphasis on logistic regression modeling
- An appendix that demonstrates the use of SAS� for all methods
- An entertaining historical perspective on the development of the methods
- Specialized methods for ordinal data, small samples, multicategory data, and matched pairs
- More than 100 analyses of real data sets and nearly 300 exercises
Written in an applied, nontechnical style, the book illustrates methods using a wide variety of real data, including medical clinical trials, drug use by teenagers, basketball shooting, horseshoe crab mating, environmental opinions, correlates of happiness, and much more.
An Introduction to Categorical Data Analysis, Second Edition 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.
"About this title" may belong to another edition of this title.
Introduction to Categorical Data Analysis - 2nd edition
ISBN13: 9780471226185
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Summary
Praise for the First Edition ''This is a superb text from which to teach categorical data analysis, at a variety of levels. . . [t]his book can be very highly recommended.'' -- Short Book Reviews ''Of great interest to potential readers is the variety of fields that are represented in the examples: health care, financial, government, product marketing, and sports, to name a few.'' -- Journal of Quality Technology ''Alan Agresti has written another brilliant account of the analysis of categorical data.'' -- The Statistician The use of statistical methods for categorical data is ever increasing in today's world. An Introduction to Categorical Data Analysis, Second Edition provides an applied introduction to the most important methods for analyzing categorical data. This new edition summarizes methods that have long played a prominent role in data analysis, such as chi-squared tests, and also places special emphasis on logistic regression and other modeling techniques for univariate and correlated multivariate categorical responses. This Second Edition features: Two new chapters on the methods for clustered data, with an emphasis on generalized estimating equations (GEE) and random effects models A unified perspective based on generalized linear models An emphasis on logistic regression modeling An appendix that demonstrates the use of SAS(R) for all methods An entertaining historical perspective on the development of the methods Specialized methods for ordinal data, small samples, multicategory data, and matched pairs More than 100 analyses of real data sets and nearly 300 exercises Written in an applied, nontechnical style, the book illustratesmethods using a wide variety of real data, including medical clinical trials, drug use by teenagers, basketball shooting, horseshoe crab mating, environmental opinions, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Second Edition 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.
Table of Contents
1. Introduction.
2. Contingency Tables.
3. Generalized Linear Models.
4. Logistic Regression.
5. Building and Applying Logistic Regression Models.
6. Multicategory Logit Models.
7. Loglinear Models for Contingency Tables.
8. Models for Matched Pairs.
9. Modelling Correlated, Clustered Responses.
10. Random Effects: Generaizaed Linear Mixed Models.
11. A Historical Tour of Cataegorical Data Analysis.
Appendix: Software for Categorical Data Analysis.
Table of Chi-Squared Distribution Values.
Bibliography.
Index of Examples.
Subject Index.
Answers to Selected Odd-Numbered Exercises
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Summary
Praise for the First Edition ''This is a superb text from which to teach categorical data analysis, at a variety of levels. . . [t]his book can be very highly recommended.'' -- Short Book Reviews ''Of great interest to potential readers is the variety of fields that are represented in the examples: health care, financial, government, product marketing, and sports, to name a few.'' -- Journal of Quality Technology ''Alan Agresti has written another brilliant account of the analysis of categorical data.'' -- The Statistician The use of statistical methods for categorical data is ever increasing in today's world. An Introduction to Categorical Data Analysis, Second Edition provides an applied introduction to the most important methods for analyzing categorical data. This new edition summarizes methods that have long played a prominent role in data analysis, such as chi-squared tests, and also places special emphasis on logistic regression and other modeling techniques for univariate and correlated multivariate categorical responses. This Second Edition features: Two new chapters on the methods for clustered data, with an emphasis on generalized estimating equations (GEE) and random effects models A unified perspective based on generalized linear models An emphasis on logistic regression modeling An appendix that demonstrates the use of SAS(R) for all methods An entertaining historical perspective on the development of the methods Specialized methods for ordinal data, small samples, multicategory data, and matched pairs More than 100 analyses of real data sets and nearly 300 exercises Written in an applied, nontechnical style, the book illustratesmethods using a wide variety of real data, including medical clinical trials, drug use by teenagers, basketball shooting, horseshoe crab mating, environmental opinions, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Second Edition 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.
Table of Contents
1.
Introduction.
2. Contingency Tables.
3. Generalized Linear Models.
4. Logistic Regression.
5. Building and Applying Logistic Regression Models.
6. Multicategory Logit Models.
7. Loglinear Models for Contingency Tables.
8. Models for Matched Pairs.
9. Modelling Correlated, Clustered Responses.
10. Random Effects: Generaizaed Linear Mixed Models.
11. A Historical Tour of Cataegorical Data Analysis.
Appendix: Software for Categorical Data
Analysis.
Table of Chi-Squared Distribution Values.
Bibliography.
Index of Examples.
Subject Index.
Answers to Selected Odd-Numbered Exercises
Digital Rights
eBook Requirements
VitalSource Bookshelf Reader
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- Windows 7/8, or Mac OS X 10.6 or above
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Here to access the VitalSource Bookshelf FAQ
Digital Rights
VitalSource
Copying: Allowed, 2 selections may be copied daily for 120 days
Printing: Allowed, 10 prints daily for 120 days
Expires: Yes, may be used for 120 days after activation
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Sharing: Not Allowed
Min.
Software Version: Online: No additional software required
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Publisher Info
Publisher: John Wiley & Sons, Inc.
Published: 2007
International: No
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Summary
Praise for the First Edition ''This is a superb text from which to teach categorical data analysis, at a variety of levels. . . [t]his book can be very highly recommended.'' -- Short Book Reviews ''Of great interest to potential readers is the variety of fields that are represented in the examples: health care, financial, government, product marketing, and sports, to name a few.'' -- Journal of Quality Technology ''Alan Agresti has written another brilliant account of the analysis of categorical data.'' -- The Statistician The use of statistical methods for categorical data is ever increasing in today's world. An Introduction to Categorical Data Analysis, Second Edition provides an applied introduction to the most important methods for analyzing categorical data. This new edition summarizes methods that have long played a prominent role in data analysis, such as chi-squared tests, and also places special emphasis on logistic regression and other modeling techniques for univariate and correlated multivariate categorical responses. This Second Edition features: Two new chapters on the methods for clustered data, with an emphasis on generalized estimating equations (GEE) and random effects models A unified perspective based on generalized linear models An emphasis on logistic regression modeling An appendix that demonstrates the use of SAS(R) for all methods An entertaining historical perspective on the development of the methods Specialized methods for ordinal data, small samples, multicategory data, and matched pairs More than 100 analyses of real data sets and nearly 300 exercises Written in an applied, nontechnical style, the book illustratesmethods using a wide variety of real data, including medical clinical trials, drug use by teenagers, basketball shooting, horseshoe crab mating, environmental opinions, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Second Edition 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.
Table of Contents
Table of Contents
1. Introduction.
2. Contingency Tables.
3. Generalized Linear Models.
4. Logistic Regression.
5. Building and Applying Logistic Regression Models.
6. Multicategory Logit Models.
7. Loglinear Models for Contingency Tables.
8. Models for Matched Pairs.
9. Modelling Correlated, Clustered Responses.
10. Random Effects: Generaizaed
Linear Mixed Models.
11. A Historical Tour of Cataegorical Data Analysis.
Appendix: Software for Categorical Data Analysis.
Table of Chi-Squared Distribution Values.
Bibliography.
Index of Examples.
Subject Index.
Answers to Selected Odd-Numbered Exercises
Digital Rights
eBook Requirements
VitalSource Bookshelf Reader
Minimum System Requirements:
- Windows 7/8, or Mac OS X 10.6 or above
Software Requirements:
eTextbooks and eChapters can be viewed by using the free reader listed below.
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Be sure to check the format of the eTextbook/eChapter you purchase to know which reader you will need. After purchasing your eTextbook or eChapter, you will be emailed instructions on where and how to download your free reader.
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Due to the size of eTextbooks, a high-speed Internet connection (cable modem, DSL, LAN) is required for download stability and speed. Your connection can be wired or wireless.
Being online is not required for reading an eTextbook after successfully downloading it. You must only be connected to the Internet during the download process.
User Help:
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Digital Rights
VitalSource
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Printing: Allowed, 10 prints daily for 120 days
Expires: Yes, may be used for 120 days after activation
Reading Aloud: Allowed
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Offline: VitalSource Bookshelf
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