Categorical Data Analysis,

by Alan Agresti

Categorical Data Analysis describes the most important methods, offering a unified presentation of modeling using generalized linear models and emphasizing loglinear and logit modeling techniques. Contributions of noted statisticians (Pearson, Yule, Fisher, Neyman, Cochran), whose pioneering efforts set the pace for the evolution of modern methods, are examined as well. Special features of the book Categorical Data Analysis also contains an appendix that describes the use of computer software currently available for performing the analyses presented in the book. A comprehensive bibliography and notes and the end of each chapter round out the work, making it a complete, invaluable reference for statisticians, biostatisticians and professional researchers.

Genres: Mathematics, Science, Academic

576 pages, Hardcover

First published January 1, 1990

Reviews

[Oleksandr Nikitin · Rating 3 out of 5]

accidentally read a book :) chapter structure could be better, but if you have some experience structuring heaps of articles yourself - it would provide a nice overview of the field.

[Terran M · Rating 3 out of 5]

Comprehensive reference for methods in categorical data analysis. I found it was not a fun book to actually read large parts of; it felt like rapid-fire lists of techniques, with neither derivation nor narrative. Overall, I preferred reading Bilder and Loughlin, which covers less material but does a better job of what it covers.

[Goo · Rating 2 out of 5]

Textbook used for a course.

Okay as a collection of results, but not a great book to learn from.

[Jim Sullivan]

Very helpful; however, the reader will need a background in nonparametric statistics before pursuing this work or you may not get too much out of it.