An introduction to categorical data analysis 2nd edition

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

  • eBOOK
    $42.00

You Save $162.00 (79%)

$42.00

List price: $204.00

Instant access, flexible term options, and deep discounts up to 60% on digital content! Happy you, happy us.

Delivered via email within 1 hour

Expires after 120 days

Easy 30-Day Returns

Non-activated eBooks can be returned for site credit within 30 days of purchase. Access codes are non-refundable once revealed or redeemed.

Please note: eBooks do not come with access codes, CDs/DVDs, workbooks, and other supplemental items.


Well, that's no good. Unfortunately, this edition is currently out of stock. Please check back soon.

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

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.

  • VitalSource Bookshelf eTextbook Reader

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.

Download Requirements:

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:

Click 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
Reading Aloud: Allowed
Sharing: Not Allowed
Min. Software Version: Online: No additional software required
Offline: VitalSource Bookshelf

Suitable Devices: PCs, Tablet PCs, Macs, Laptops


Digital Rights Management (DRM) Key

Copying - Books that cannot be copied will show "Not Allowed." Otherwise, this will detail the number of times it can be copied, or "Allowed with no limits."

Printing - Books that cannot be printed will show "Not Allowed." Otherwise, this will detail the number of times it can be printed, or "Allowed with no limits."

Expires - Books that have no expiration (the date upon which you will no longer be able to access your eBook) will read "No Expiration." Otherwise it will state the number of days from activation (the first time you actually read it).

Reading Aloud - Books enabled with the "text-to-speech" feature so that they can be read aloud will show "Allowed."

Sharing - Books that cannot be shared with other computers will show "Not Allowed."

Min. Software Version - This is the minimum software version needed to read this book.

Suitable Devices - Hardware known to be compatible with this book. Note: Reader software still needs to be installed.

Other Editions of Introduction to Categorical Data Analysis


Shop Us With Confidence

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

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.

  • VitalSource Bookshelf eTextbook Reader

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.

Download Requirements:

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:

Click 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
Reading Aloud: Allowed
Sharing: Not Allowed
Min. Software Version: Online: No additional software required
Offline: VitalSource Bookshelf

Suitable Devices: PCs, Tablet PCs, Macs, Laptops


Digital Rights Management (DRM) Key

Copying - Books that cannot be copied will show "Not Allowed." Otherwise, this will detail the number of times it can be copied, or "Allowed with no limits."

Printing - Books that cannot be printed will show "Not Allowed." Otherwise, this will detail the number of times it can be printed, or "Allowed with no limits."

Expires - Books that have no expiration (the date upon which you will no longer be able to access your eBook) will read "No Expiration." Otherwise it will state the number of days from activation (the first time you actually read it).

Reading Aloud - Books enabled with the "text-to-speech" feature so that they can be read aloud will show "Allowed."

Sharing - Books that cannot be shared with other computers will show "Not Allowed."

Min. Software Version - This is the minimum software version needed to read this book.

Suitable Devices - Hardware known to be compatible with this book. Note: Reader software still needs to be installed.

Publisher Info

Publisher: John Wiley & Sons, Inc.
Published: 2007
International: No

  • Summary
  • Author bio
  • Table of contents
  • Digital rights

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.

  • VitalSource Bookshelf eTextbook Reader

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.

Download Requirements:

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:

Click 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
Reading Aloud: Allowed
Sharing: Not Allowed
Min. Software Version: Online: No additional software required
Offline: VitalSource Bookshelf

Suitable Devices: PCs, Tablet PCs, Macs, Laptops


Digital Rights Management (DRM) Key

Copying - Books that cannot be copied will show "Not Allowed." Otherwise, this will detail the number of times it can be copied, or "Allowed with no limits."

Printing - Books that cannot be printed will show "Not Allowed." Otherwise, this will detail the number of times it can be printed, or "Allowed with no limits."

Expires - Books that have no expiration (the date upon which you will no longer be able to access your eBook) will read "No Expiration." Otherwise it will state the number of days from activation (the first time you actually read it).

Reading Aloud - Books enabled with the "text-to-speech" feature so that they can be read aloud will show "Allowed."

Sharing - Books that cannot be shared with other computers will show "Not Allowed."

Min. Software Version - This is the minimum software version needed to read this book.

Suitable Devices - Hardware known to be compatible with this book. Note: Reader software still needs to be installed.

What is categorical data in data analysis?

Definition. Categorical data analysis is the analysis of data where the response variable has been grouped into a set of mutually exclusive ordered (such as age group) or unordered (such as eye color) categories.

How do you analyze categorical data in Excel?

Analyzing Categorical Data in Excel with Pivot Tables First, click on any cell within the data set. Then press Atl +N+V. This will open the Create Pivot Table dialogue box. Next, select a table or range of data that is to be included in the pivot table.

What techniques of statistical analysis are used for categorical data?

General tests.
Bowker's test of symmetry..
Categorical distribution, general model..
Chi-squared test..
Cochran–Armitage test for trend..
Cochran–Mantel–Haenszel statistics..
Correspondence analysis..
Cronbach's alpha..
Diagnostic odds ratio..

What is categorical data used for?

Categorical data is used to gather information from both online and offline surveys or questionnaires as the case may be. The type of categorical data used may differ depending on the aim of data collection.

Toplist

Latest post

TAGs