Modelling Binary Data: 56 (Chapman & Hall/CRC Texts in Statistical Science) - Softcover

Praise for the first edition: "A merit of the book, considerably enhancing its practical value, is the detailed discussion of computational issues and software. Overall the book provides an accessible and effective presentation of the topic. I recommend it." -Journal of Applied Statistics "In summary, this book draws together material on many practical aspects of the analysis of binary data, which was unavailable before in a single book. Applied statisticians, at any level, will learn something from it." -The Statistician "well written, contains good examples, and ideas and concepts are developed and explained logically and clearlyI can strongly recommend this book as a handy reference for applied statisticians and other researchers with a good background in statistical methods I also appreciated having a book that seems to have very few errors of any kind!" -Biometrics

Since the original publication of the bestselling Modelling Binary Data, a number of important methodological and computational developments have emerged, accompanied by the steady growth of statistical computing. Mixed models for binary data analysis and procedures that lead to an exact version of logistic regression form valuable additions to the statistician's toolbox, and author Dave Collett has fully updated his popular treatise to incorporate these important advances.

Modelling Binary Data, Second Edition now provides an even more comprehensive and practical guide to statistical methods for analyzing binary data. Along with thorough revisions to the original material-now independent of any particular software package- it includes a new chapter introducing mixed models for binary data analysis and another on exact methods for modelling binary data. The author has also added material on modelling ordered categorical data and provides a summary of the leading software packages.

All of the data sets used in the book are available for download from the Internet, and the appendices include additional data sets useful as exercises.