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Applied logistic regression. 3rd ed. (English) Zbl 1276.62050

Wiley Series in Probability and Statistics. Hoboken, NJ: John Wiley & Sons (ISBN 978-0-470-58247-3/hbk; 978-1-118-54835-6/ebook). xvi, 500 p. (2013).
This is the third edition of ‘Applied logistic regression.’, 13 years apart from the second edition from 2000, see the review Zbl 0967.62045. As was the case in the first two editions, the authors’ primary objective of the third edition is still to provide an introduction to the underlying theory of logistic regression models, with a major focus on the applications, using real data sets, of the available methods to explore the relationships between a categorical outcome variable and a set of covariates. In this new edition, the authors’ have added a number of key topics, which include:
An expanded presentation of numerous new techniques for model-building, including methods for determining the scale of continuous covariates and assessing model performance.
An expanded presentation of regression modeling of complex sample survey data.
An expanded development of the use of logistic regression modeling in matched studies, as well as with multinomial and ordinal scaled responses.
A new chapter 8 dealing with models and methods for correlated categorical response data.
A new chapter 9 developing a number of important applications either missing or expanded from the previous editions. These include propensity score methods, exact methods for logistic regression, sample size issues, Bayesian logistic regression, and other link functions for binary outcome regression models. This chapter concludes with sections dealing with the epidemiologic concepts of mediation and additive interactions.
Note that the new chapters 8 and 9 were expanded from two sections in Chapter 8 of the second edition and the new chapter 10 is a revised chapter 8 of that edition. As before, all of the data sets used in the text are available at a web site of Wiley and Sons, and each chapter ends with exercises.
This book has been used to teach parts of graduate level survey courses, quarter- or semester-long courses, as well as has been focused on short courses to working professionals. It is assumed that readers have a solid foundation in linear regression methodology and contingency table analysis.

MSC:

62J12 Generalized linear models (logistic models)
62-02 Research exposition (monographs, survey articles) pertaining to statistics
62J99 Linear inference, regression
62H17 Contingency tables
62Pxx Applications of statistics

Citations:

Zbl 0967.62045

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