Regression Methods in Biostatistics

Introduction.- Exploratory and Descriptive Methods.- Basic Statistical Methods.- Linear Regression.- Logistic Regression.- Survival Analysis.- Repeated Measures Analysis.- Generalized Linear Models.- Strengthening Casual Inference.- Predictor Selection.- Complex Surveys.- Summary.

The authors are on the faculty in the Division of Biostatistics, Department of Epidemiology and Biostatistics, University of California, San Francisco, and are authors or co-authors of more than 200 methodological as well as applied papers in the biological and biomedical sciences. The senior author, Charles E. McCulloch, is head of the Division and author of Generalized Linear Mixed Models (2003), Generalized, Linear, and Mixed Models (2000), and Variance Components (1992).

From the reviews:

"This book provides a unified introduction to the regression methods listed in the title...The methods are well illustrated by data drawn from medical studies...A real strength of this book is the careful discussion of issues common to all of the multipredictor methods covered." Journal of Biopharmaceutical Statistics, 2005

"This book is not just for biostatisticians. It is, in fact, a very good, and relatively nonmathematical, overview of multipredictor regression models. Although the examples are biologically oriented, they are generally easy to understand and follow...I heartily recommend the book" Technometrics, February 2006

"Overall, the text provides an overview of regression methods that is particularly strong in its breadth of coverage and emphasis on insight in place of mathematical detail. As intended, this well-unified approach should appeal to students who learn conceptually and verbally." Journal of the American Statistical Association, March 2006

"This book is ... about regression methods, with examples and terminology from the biostatistics field. It should, however, also be useful for practitioners from other disciplines where regression methods can be applied. ... Most chapters end with a Problems section, and a section of further notes and references, making the book suitable as a text for a course on regression methods for Ph. D. students in medicine ... . Many of the analyses in the book are illustrated with output from the statistical package Stata." (Göran Broström, Zentralblatt MATH, Vol. 1069, 2005)

"The authors have written have written the book with the intention to provide an accessible introduction to multipredictor methods, emphasizing their proper use and interpretation. ... In summary it may be said that this book is excellently readable. Because of the ... detailed aspects of modeling, the applied tips as well as many medical examples, it can berecommended ... . In