Practical Guide: Logistic Regression

Hilbe, J. M. (2015) Practical Guide to Logistic Regression

This short book shows the reader how to model a binary response variable using basic logistic regression models – and despite its modest size, Joseph M. Hilbe manages to introduce the reader to logistic models with single or multiple predictors as well as to grouped and Bayesian logistic regression.

Hilbe suggests that the book would be appropriate for someone who has completed a basic course in statistics which includes linear regression. I would agree with this assessment, though I would also recommend working through an introductory tutorial on R. That said, this book is written in an exceptionally clear style which means that the reader can expect a treatment of the subject which is concise but comprehensible.

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 provision of complete code in the book and on a dedicated website will also be of benefit to readers who wish to spend more time learning about logistic regression models than hacking code.

Indeed, 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 which can be consolidated both by analysis of their own data and by further reading.

Review originally published in Reviews. Significance,13:2 45. doi: 10.1111/j.1740-9713.2016.00885.x