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Rating: 
Summary: update of very well written and popular text
Review: Hosmer and Lemeshow point to the massive growth in applications of logistic regression over a ten year period from the time of publication of the first edition of their text. They found over 1000 articles that used logistic regression during that time frame. There also have been many software advances that make it easier to apply logistic regression. The authors do their computing mostly in STATA. But they also acquaint the reader with many other useful standard packages for applying logistic regression. They also provide a web site from the publisher where data sets can be found.New topics include the use of exact methods in logistic regression, logistic models for multinomial, ordinal and multiple response data. Also included is the use of logistic regression in the analysis of complex survey sampling data and for the modeling of matched studies. The book is intended for a graduate course in logistic regression requiring the student to be familiar with linear regression and contingency tables. Similar in spirit and objectives to the first edition, this text also maintains the clarity of thought and presentation that these authors have a history of providing. This is an important update to the first edition and is worth having on the bookshelf in any biostatistics library. I have my own personal copy and I think many others would also benefit by having it as a reference.
Rating:
Summary: A valuable tool for the applied statistician.
Review: This book is widely considered the "bible" of logistic
regression analysis. It provides an accessible introduction
to the theory of logistic modeling, and gives in-depth
coverage of the proper use of the method, including
interpretation, diagnostics, and practical considerations.
Indispensable for anyone who uses logistic regression in
their work.
Rating:
Summary: highly regarded text on logistic regression
Review: This is a very popular and well written text on logistic regression. The topic is very useful to biostatisticians. Hosmer and Lemeshow have taught some short course out of the text which have been well received. The authors are knowledgeable and thorough. The book is very much oriented toward real applications and does not require advanced mathematics.
Rating:
Summary: Should suit the needs of most, especially analysts
Review: This is an excellent beginning and intermediate text on logistic regression analysis. Avoids the thorny details, but provides a wealth of references for those who are interested. Anyone who is serious about doing logistic regression analysis should have this book.
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