Negative Binomial Regression 2nd Edition by Joseph M. Hilbe (PDF)

Description

This second edition of Hilbe’s Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and distributional background of each model is discussed, together with examples of their construction, application, interpretation and evaluation. Complete Stata and R codes are provided throughout the text, with additional code (plus SAS), derivations and data provided on the book’s website. Written for the practising researcher, the text begins with an examination of risk and rate ratios, and of the estimating algorithms used to model count data. The book then gives an in-depth analysis of Poisson regression and an evaluation of the meaning and nature of overdispersion, followed by a comprehensive analysis of the negative binomial distribution and of its parameterizations into various models for evaluating count data.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐If you work professionally with count or count-like data, as I do, this is a book you’ll want to add to you library and treat as a major reference. You may have had courses in regression or categorical analysis which introduced you to Poisson or even negative binomial models for count data, but this is the book which will fill-in the gaps, tell you what assumptions really need checked, and how to validate and interpret the results. This book starts with Poisson models, expands to negative binomial models, and generalizes to zero-truncated, zero-inflated, hurdle models, and beyond. Hilbe manages to cover all of this with very readable — even conversational — prose. If you need deep theory, it is here (though you can skip it), and if you want to be able generate synthetic data to explore and validate your models, that’s covered too. This book has joined perhaps a half-dozen books in my library that I consider among the more valuable references. Based upon my experience with this book, I subsequently bought Hilbe’s book on Logistic Regression Models — which seems likewise well-done.EDIT: Amazon is associating the review with the Kindle edition; actually it applies to the print edition.

⭐The formula for the derivative of the log likelihood w.r.t alpha (8.14) has an error. The signs preceding each digamma are flipped. They should be -digamma(y_i + 1/alpha) + digamma(1/alpha).

⭐This is a very well written book on the specific topic of negative binomial distribution and its cousin/related extensions of (Poisson, zero inflation models, etc). Describes parameter estimation methods, derives both Poisson and NB distribution in full, discusses over dispersion, test of fit to model, etc. Also includes SATA and R code to help you recreate examples in book. Very good reference on this topic.

⭐I love a book that gives me some good theoretical foundation, yet provides some solid examples in language that I can actually follow. I have a foundation in regression, but poisson regression is not something that has been covered in my statistical courses up to this point. This book was a great introduction.

⭐I own the hardcopy of this book and it has been an invaluable reference. However the kindle version is horrible. The mathematical equations and expressions are alternately very small or very huge! And the tabular output is all out of whack, making many of the contingency tables impossible to read.

⭐This is a great book that combines theoretical information with practical examples! It is understandable and yet still provides in depth information necessary to understand the why behind the statistics. It was just what I needed!

⭐Not a page turner, but it’s a stats book …

⭐great book.

⭐This book is a great reference guide to building models using this statistical distribution – with plenty of examples in Stata and R to aid understanding.

⭐This is an excellent book which places negative binomial models in context. Explains what they are, when they are useful and how to use them.

⭐Very thorough description of Model group, useful for all as long as you know some basics of Regression modelling. No complaints at all! I highly recommend this product!

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