Practical Guide to Logistic Regression

"The book presents many worked examples, and the choice of interesting data sets all of which are available to the reader is one of its greatest assets. Data availability makes it easy for readers to reproduce the examples from the book, and example code is available for R, SAS and Stata: R code is incorporated into the book chapters, and the end of each chapter gives SAS and Stata code."
-Ulrike Groemping, Beuth University of Applied Sciences Berlin, Journal of Statistical Software, July 2016

"... this book is written in an exceptionally clear style ... An additional selling point of this text is that it introduces new R functions, which can be applied in one's own work, as well as equivalent SAS and Stata code. ... the emphasis on understanding logistic regression modelling rather than on the mechanistic application of techniques is one of the great strengths of the book. Anyone who reads this book will therefore feel that they have a good understanding of this subject ..."
-Significance Magazine, February 2016

"Big Data is ascendant, but even the biggest data often boil down to a decision between two categories: survive or die, purchase or don't purchase, click or don't click, fraudulent or honest, default or pay. Logistic regression is the classic workhorse for this 0/1 data, and Joseph Hilbe's new book presents a guide for the practitioner, chock full of useful R, Stata, and SAS code. Hilbe has worked with practitioners and aspiring practitioners in virtually every field that uses statistics, including for over a decade via his courses at Statistics.com. His new book is truly, in his own words, 'a tutorial between you and me.'"
-Peter Bruce, Founder and President of the Institute for Statistics Education at Statistics.com