Logistic Regression: From Introductory to Advanced Concepts and Applications by Scott Menard
In each chapter, the basic model is explained and illustrated with applied examples, with a focus on translating from the research problem to the implementation of the model, then interpreting the results back to English. While not dependent on any one software package, limitations to existing software packages, and ways of getting around those limitations, are examined. The book brings together material on logistic regression that is often covered in passing or in limited detail in treatments of other topics such as event history analysis or multilevel analysis, and includes material not elsewhere available on the use of logistic regression with path analysis, linear panel models, and multilevel change models. Mathematical notation is kept to a minimum, allowing readers with more limited backgrounds in statistics to follow the presentation, but the book includes advanced topics that will be of interest to more statistically sophisticated readers as well.