Provides descriptions and motivations of the analysis methods as well as worked examples with R code
Highlights applications in a wide range of disciplines, including medicine, psychology, sports, and ecology
Uses R not only as a data analysis method but also as a learning tool
Discusses solutions to problems frequently mishandled in practice, such as how to incorporate diagnostic testing error into an analysis and how to analyze data from a complex survey sampling design
Includes an introduction to R for inexperienced users
Presents an extensive set of exercises at the end of each chapter
Offers data sets, R programs, and videos on the book's website
Solutions manual available upon qualifying course adoption

Summary

Learn How to Properly Analyze Categorical Data
Analysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and probability estimation. The authors give detailed advice and guidelines on which procedures to use and why to use them.

The Use of R as Both a Data Analysis Method and a Learning Tool
Requiring no prior experience with R, the text offers an introduction to the essential features and functions of R. It incorporates numerous examples from medicine, psychology, sports, ecology, and other areas, along with extensive R code and output. The authors use data simulation in R to help readers understand the underlying assumptions of a procedure and then to evaluate the procedure's performance. They also present many graphical demonstrations of the features and properties of various analysis methods.

Web Resource
The data sets and R programs from each example are available at www.chrisbilder.com/categorical. The programs include code used to create every plot and piece of output. Many of these programs contain code to demonstrate additional features or to perform more detailed analyses than what is in the text. Designed to be used in tandem with the book, the website also uniquely provides videos of the authors teaching a course on the subject. These videos include live, in-class recordings, which instructors may find useful in a blended or flipped classroom setting. The videos are also suitable as a substitute for a short course.

Table of Contents

Analyzing a Binary Response, Part 1: Introduction
One binary variable
Two binary variables

Analyzing a Binary Response, Part 2: Regression Models
Linear regression models
Logistic regression models
Generalized linear models

Analyzing a Multicategory Response
Multinomial probability distribution
I x J contingency tables and inference procedures
Nominal response regression models
Ordinal response regression models
Additional regression models

Analyzing a Count Response
Poisson model for count data
Poisson regression models for count responses
Poisson rate regression
Zero inflation

Model Selection and Evaluation
Variable selection
Tools to assess model fit
Overdispersion
Examples

Additional Topics
Binary responses and testing error
Exact inference
Categorical data analysis in complex survey designs
"Choose all that apply" data
Mixed models and estimating equations for correlated data
Bayesian methods for categorical data

Appendix A: An Introduction to R
Appendix B: Likelihood Methods

Bibliography

Index

Exercises appear at the end of each chapter.