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A must-have tex on logistic regression
on July 5, 2009
LOGISTIC REGRESSION MODELS (2009, Chapman & Hall/CRC - 656 pages)
Joseph M Hilbe, Jet Propulsion Laboratory, CalTech and Arizona
Prof Hilbe and I have coauthored several journal articles together in the past and plan to write more together in the future on quasi-least squares regression. However, I was delighted to have the opportunity to read an almost completed version of "Logistic Regression Models" prior to its publication. When I concluded reading it, I came to the clear conclusion that it is a must-have text for those with an interest in logistic regression and related models. Whether the reader is just learning about the area, or is an experienced statistician, there is something for readers of every statistical background.
Some of the reasons I recommend this book with 5 stars are:
1) The text is a comprehensive coverage of the subject - It discusses more logistic-based models than any other single text.
2) Prof. Hilbe's writing style is aimed to make the concepts involved with logistic regression as clear and understandable as possible.
3) The text offers a host of fully worked out examples, demonstrating the background, construction, interpretation, and evaluation of each model discussed. Both real and simulated data is used, with instructions on how to create and appropriately use synthetic data and synthetic models.
4) The book presents clearly stated guidelines on how to decide between models.
5) Examples are provided that use Stata, but with discussion of the capabilities of other major software applications, and how they deal with particular models and options.
6) At the end of each chapter, R code is provided that duplicates the Stata examples used in the text, whenever possible.
7) Numerous end of chapter questions are provided, with an accompanying Solutions manual that contains fully worked out answers to all 237 questions. Qualified instructors will be given the 186 page Solutions Manual free of charge.
8) A full chapter is devoted to the construction and interpretation of interactions, as well as their graphical representation.
9) A full chapter is devoted to the nature of binomial over dispersion and how it is defined, identified, and handled. Comparisons with count model over dispersion are discussed at some length.
10) Controversial topics such as the interpretation of odds ratios as risk ratios, goodness of fit tests for panel models such as GEE and QLS and other similar subjects are fully discussed.
11) The book includes a 29 page tutorial on basic data management, functions, and logistic modeling using Stata for those readers who are not familiar with Stata. Sufficient background is provided in order to fully understand the examples used in the text.
12) Some 60 data sets used in the text for examples and for end-chapter questions are provided for download on the text's web site. Download sites are given for the data sets in the following formats: Stata, Excel, SAS, SPSS, R, Limdep. The three most used datasets are also formatted to ASCII comma delimited, JMP, Systat, Minitab, and Statistica. An appendix identifies the location in the text for the first use of all data sets.
13) Over 40 User/author written commands are also available for download. Many useful commands and functions have been created to assist readers and researchers in their modeling and evaluation tasks.
14) The price is excellent price for a textbook this large (656 pages), especially one that is published in Chapman & Hall/CRC's respected "Texts in Statistical Sciences" series.
15) The book is authored by a leading scholar and professor in the area. Prof Hilbe teaches the "Logistic Regression" and "Advanced Logistic Regression" courses for Statistics.com, the foremost web-based continuing education site for professional statisticians and researchers worldwide.