Visualizing Categorical Data with SAS and R

• the Statistical Consulting Service at York University
• the GESIS Spring Seminar Series, Cologne, Germany, Mar 16-20, 2009

General Resources

Lecture notes and workshop files

Topics & lecture notes	SAS files	R files
1. Introduction & overview  1.1 Overview: Categorical data & graphics  1.2 Discrete distributions  1.3 Testing association	discrete.sas berkeley-freq.sas sexfun-cmh.sas	discrete.R berkeley-freq.R sexfun-chisq.R []
2. Two-way and n-way tables  2.1 2 x 2 tables  2.2 Two-way tables  2.3 Observer agreement  2.4 Correspondence analysis	berk-4fold.sas vision-sieve.sas msdiag-agree.sas mental-ca.sas	berk-4fold.R [] vision-sieve.R [] msdiag-agree.R [] mental-ca.R []
3. Mosaic displays & loglinear models  3.1 n-way tables: Models & graphs  3.2 Mosaics software  3.3 Structured tables	berkeley-glm.sas titanic-loglin.sas mentgen2.sas vision-quasi.sas	berkeley-glm.R [] titanic-loglin.R [] mental-glm.R [] vision-quasi.R []
4. Logit models & logistic regression  4.1 Logit models  4.2 Logistic regression models  4.3 Effect plots  4.4 Influence & diagnostic plots	berkeley-logit.sas arthritis-logistic.sas cowles-logistic.sas Arrests-logistic.sas cowles-effect.sas Arrests-effect.sas berkeley-diag.sas berkeley-diag-ods.sas	berkeley-logit.R [] arthritis-logistic.R [] cowles-logistic.R [] Arrests-logistic.R [] cowles-effect.R [] Arrests-effects.R [] berkeley-diag.R [] arthritis-diag.R []
5. Polytomous response models  5.1 Proportional odds models  5.2 Nested dichotomies  5.3 Generalized logits	arthritis-propodds.sas arthritis-propodds-ods.sas wlf-nested.sas wlf-glogit.sas	arthritis-propodds.R [] wlf-nested.R [] wlf-glogit.R []

Further reading

The main source for these materials is my new book, Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data. The web site for the book contains all the R-code from the chapters.
For SAS users, I recommend my older book Visualizing Categorical Data, covering similar ground.

If you want to learn more about categorical data analysis, there are several books and other resources I recommend:

• Agresti, A. (1990). Categorical Data Analysis. NY: Wiley. There is also a manual for R and S-plus users to accompany this text.
• Christensen, R. (1990). Log-Linear Models and Logistic Regression. Springer-Verlag.
• Everitt, B. S. (1992). The Analysis of Contingency Tables, London: Chapman & Hall (Monograph 45).
• Stokes, M.E., Davis, C.S., and Koch, G.S. (2012). Categorical Data Analysis Using SAS, Third Ed.. Cary, NC: SAS Institute. A practical guide to these topics using SAS, though without much emphasis on graphical methods.
• Robert Hanneman's Generalized Linear Models
• Fox, John. Applied Regression Analysis and Generalized Linear Models, 3rd Ed. Sage, 2015. An excellent treatment of Generalized Linear Models.
• Fox & Weisberg An R Companion to Applied Regression, 2nd Ed., Sage, 2011. There is also a web page for the book, containing data files, R scripts and a collection of web appendices on other topics.