Updates to the code examples in the book will be posted here.

  • ca package: There are now several enhancements for graphics for correspondence analysis (Chapter 6) in the ca package, v. 0.64. All examples in the book still work, but some can be simplified.

    • The ca package now includes cacoords() extracting coordinate from CA/MCA solutions with various scaling options.
    • A multilines() function facilitates drawing CA/MCA solutions connecting factor levels with lines.
    • The vcdExtra package, v. 0.7, now includes a function mcaplot() for MCA plots in the style used in the book.
  • ggplot2 changes: In the latest major release, ggplot2_2.0.0, calls to stat_smooth(method="glm") now require the family argument to be specified as, for example, method.args = list(family = binomial) rather than family = binomial. This affects numerous figures in Chapter 7, starting with Figure 7.2 in Example 7.3.


Readers are invited to send an email related to typos or errors in the book to friendly AT yorku DOT ca. Please give specific section, page, figure or equation references, and use DDAR: errata in the subject line.

Additional vignettes and case studies

Several examples and topics did not make it into the printed book


"This is an excellent book, nearly encyclopedic in its coverage. I personally find it very useful and expect that many other readers will as well. The book can certainly serve as a reference. It could also serve as a supplementary text in a course on categorical data analysis that uses R for computation or, because so much statistical detail is provided, even as the main text for a course on the topic that emphasizes graphical methods." John Fox, McMaster University

"For many years, Prof. Friendly has been the most effective promoter in Statistics of graphical methods for categorical data. We owe thanks to Friendly and Meyer for promoting graphical methods and showing how easy it is to implement them in R. This impressive book is a very worthy addition to the library of anyone who spends much time analyzing categorical data." Alan Agresti, Biometrics, June, 2016


If you use this book or the materials contained on this web site in research papers, you can cite that use as follows with BibTeX:

   title    = {Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data},
   year     = {2016},
   author   = {Friendly, Michael and Meyer, David},
   publisher    = {Chapman \& Hall/CRC},
   address  = {Boca Raton, FL},
   isbn     = {978-1-4987-2583-5},

A text version of this citation is:

Friendly, M. & Meyer, D. (2016). Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data. Boca Raton, FL: Chapman & Hall/CRC.