Analysis of Categorical Data with R

Analysis of Categorical Data with R

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Hardback
$89.95
ISBN 9781439855676
Cat# K12597
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Features

  • Provides a modern introduction to analyzing categorical data
  • Integrates R code as learning tool
  • Includes many examples with R code and data
  • Covers topics not addressed in other books, such as Bayesian methods and survey data
  • Offers exercises to aid with self study

Summary

Written for students and researchers in statistics and biostatistics, this book presents a modern introduction to categorical data analysis, with R integrated into the text as a data analysis method and a learning tool. The book includes many detailed worked examples to illustrate methods, with R code and data available for all of them. It also includes many exercises throughout the text and is supplemented by a solutions manual and website with code, data, and video lectures. Unlike other books on the subject, this one covers topics such as survey data and Bayesian methods.

Table of Contents

Analyzing a binary response
Analyzing a count response
Analyzing a multinomial response
Model building
Additional topics

Editorial Reviews

"Bilder and Loughin have worked as a dynamic duo for a number of years, and they clearly are blending their knowledge, talents, experience, and teamwork to create this valuable book. Analyzing categorical data correctly and in-depth is not as simple as it appears in many courses and textbooks. As a result, many people can get the wrong idea about what could and should be done with categorical data, and hence their results can be inconclusive or incorrect. This book gives users the full scoop when it comes to analyzing categorical data of all types, and it does so in an easy-to-understand way, giving confidence to the reader to go ahead and apply the ideas in practice. The use of R for analyzing data is becoming a worldwide phenomenon and a staple for data analysts on every level. As its popularity grows, it becomes critical for beginners to become comfortable with understanding and using R to analyze their data. Through the special attention paid to teaching the basics of R, as well as providing step-by-step particulars in using R in each separate analysis, Bilder and Loughin help establish and promote a group of confident, comfortable users of this software that can seem a mystery to many. I highly and happily recommend this book to anyone who plans to analyze categorical data in their careers—which includes most all of us!"
—Deborah J. Rumsey, PhD, Auxiliary Professor and Statistics Education Specialist, Department of Statistics, The Ohio State University

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