Customer Reviews

Applied logistic regression (Wiley Series in probability and statistics)

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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.

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.

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.

I found this book to be an excellent account of logistic regression techniques. It was clear and used a minimum of mathematical detail , focusing instead on the understanding of the concepts presented. There were two small problems that I found with this book: (1) The subsections of the text were not adequately identified which made finding specific things occasionally difficult. (2) The mathematical notation was often different than other references that I own. Overall, a highly recommended purchase.

This text was intended to give practical, procedural, authoritative advice to practitioners on how to build models using logistic regression. It is not an introductory text. It is so concise that just about every sentence has a point to note. The reader should have some prior exposure to logistic regression and be fairly expert in modern linear regression model building using standard software, such as SAS, SPSS, STRATA or BMD.

Logistic regression is a very handy statistical tool. It does not demand much of the data (no need for variables to be normally distributed). Also, it can be used with dichotomous dependent variables. Multiple regression is often used for such purposes, but--technically--that might provide misleading results. This is one of the classic books outlining the use (and abuse) of logistic regression analysis.

There are some features of logistic regression that are unfamiliar to those who have never used the technique before. This book describes the Wald statistic, pseudo r-square (designed to be something of an analogue to explained variation in multiple regression), goodness of fit measures (such as the eponymous Hosmer-Lemeshow test and chi square), logistic regression with more than two categories of the dependent variable, accuracy of predictions, and so on.

This is one of the best works on the subject, and it has helped me make sense of the results when I use statistical software featuring logistic regression. If interested in the technique, this work will be a nice resource.

My SAS instructor introduced me to this book, while he was teaching how to use PROC LOGISTIC. It's a well accepted bible for practitioners who use logistic regression models to calculate the probability of a dichotomous event (e.g. probability of defaulting on a credit card).

I found some of the math difficult to understand and confusing, but I blame that on my lack of knowledge in matrix algebra and mathematical notation.

Great book for anyone taking biostatistics as a major or minor. It's a handy tool for any statistician and the book provides the necessary information along with in depth coverage all the necessary topics. A classic in its own right.

Logistic regression has taken a new life after new vision has developed all over the world to have efficent and effective risk management system. Since this topic is new for lot of people, this guide goes an extra mile to make people understand and practice the concepts in social sciences using SAS, STAT and / or SPSS. Must buy if you really want to taste the benefit of logistic regression. The guide explains the concepts and soloutions to the bestseller. Once again good book, but not to be read from cover to cover rather on need basis when encounter any problem.

A good book that certainly has practical application.

It details the rise in use of this particular technique, and where it is applicable.

Also details multiple varieties including multinomial and others.

This is definitely a mathematics text that is worth the time to take a look at.