Categorical Data Analysis

Website for CATEGORICAL DATA ANALYSIS, 3rd edition

For the third edition of Categorical Data Analysis by Alan Agresti (Wiley, 2013), this site contains (1) information on the use of other software (SAS, R and S-plus, Stata, SPSS, and others), (2) data sets for examples and many exercises (for many of which, only excerpts were shown in the text itself), (3) short answers for some of the exercises, (4) extra exercises that did not fit in the text itself, and (5) corrections of errors in early printings of the book. Also, there's (6) some old lectures that followed the first edition of the book, (7) a seminar on the history of CDA, and (8) a survey paper on Bayesian inference for CDA. Here is a link to the webpage for the Website for 2nd edition (2002) of Categorical Data Analysis, which is no longer being updated.

1. Software Appendix

In this appendix we provide details about how to use R, SAS, Stata, and SPSS statistical software for categorical data analysis, with examples in many cases showing how to perform analyses discussed in the text. This supplements the brief description found in Appendix A of the "Categorical Data Analysis" text, 3rd edition, Wiley (2013). For each package, the material is organized by chapter of presentation and refers to datasets analyzed in those chapters. The full data sets are available at datasets.

SAS

Go to SAS for a pdf file containing details about the use of SAS for CDA, with illustrations for data sets in the CDA text.

R and S-Plus

Go to R for a pdf file containing details about the use of R for CDA, and illustrations for data sets in the CDA text. This includes a link to the manual that Dr. Laura Thompson prepared on the use of R and S-Plus to conduct all the analyses in the 2nd edition of the CDA text.

Stata

Go to Stata for discussion of using Stata for CDA.

SPSS

Go to SPSS for discussion of using SPSS for CDA.

Other software

Go to other software for discussion of other software useful for CDA, such as StatXact and LogXact.

2. Primary datasets:

Here are datasets for many of the main examples in the text, and for some of the exercises.

3. Selected short solutions to exercises:

Here is a pdf file of short solutions for some of the exercises at the ends of the chapters. These are mainly the solutions that were provided for some of the odd-numbered exercises from the 2nd edition of the book. Please report errors to AA@STAT.UFL.EDU, so they can be corrected in future revisions of this site. The author regrets that he cannot provide solutions of exercises not in this file.

4. Additional exercises:

Here is a pdf file containing Extra exercises, mainly taken from the first two editions of the book.

5. Corrections:

6. Lectures on CDA:

I have converted old VHS videotapes to digital of a masters-level course on CDA that I taught at UF in 1994 and have posted the video files here. These follow the 1st edition of the book (1990) and are dated in various ways; e.g., there is much more emphasis on loglinear models and less on binary and multinomial logistic models than I'd give now, and the software used was mainly GLIM as this was before R, SAS GENMOD, etc. The picture quality is also poor in some of these. But, perhaps it's better to put them here than have them continue to collect dust on a shelf. These are for individual viewing. Please do not distribute or use them in any way without my permission (copyright 2013). Lectures on CDA

7. History of CDA:

The final chapter gives a historical tour of CDA. Here is a history of CDA seminar that I presented in September, 2009, to the Boston chapter of the American Statistical Association, with some discussion at the end of the talk on advances having a Boston connection. To watch this, enter your email address and click on Playback. (Scroll below toward the right and you'll see a highly discretized copy of my presentation.)

8. Bayes:

David Hitchcock (Statistics Dept., Univ. of South Carolina) and I wrote a survey paper about Bayesian inference for categorical data analysis that appeared in Statistical Methods and Applications, the Journal of the Italian Statistical Society, in 2005 (volume 14, pages 297-330). It was partly a by-product of a very nice summer that I spent in Florence, Italy. A somewhat longer version of this paper is a UF technical report in the Statistics Department at UF.