Description
Book SynopsisThis very popular textbook, now in its third edition, offers an accessible description of fundamental and more advanced concepts and methods of logistic regression. This edition includes three new chapters and an expanded section about modeling guidelines.
Trade ReviewFrom the book reviews:
“The authors present fundamental and basic ideas and methods of analysis of survival/event-history data from both applications and methodological points of view. … This book is clearly written and well structured for a graduate course as well as for practitioners and consulting statisticians. … There are many good examples in this edition, and more importantly, this new edition offers additional exercises, making it a good candidate for adoption as a textbook.” (Technometrics, August, 2012)
"This text is … an elementary introduction to survival analysis. It is primarily intended for self-study, but it has also proven useful as a basic text in a standard classroom course … . Each chapter starts with an Introduction, an Abbreviated outline, and Objectives, and ends with self tests, exercises and a detailed outline. Solutions to tests and exercises are also provided." (Göran Broström, Zentralblatt MATH, Vol. 1093 (19), 2006)
"The most meaningful accolade that I can give to this text is that it admirably lives up to its title." Journal of the American Statistical Association, September 2006
"Imagine---a statistics textbook that actually explains things in English instead of explaining a topic by bombarding the reader with page-width equations requiring an advanced degree in Math just to read the book. If it weren't for this book, I would be really stuck." (David Britz)
Table of ContentsIntroduction to Survival Analysis.- Kaplan-Meier Survival Curves and the Log-Rank Test.- The Cox Proportional Hazards Model and Its Characteristics.- Evaluating the Proportional Hazards Assumption.- The Stratified Cox Procedure.- Extension of the Cox Proportional Hazards Model for Time-Dependent Variables.- Parametric Survival Models.- Recurrent Events Survival Analysis.- Competing Risks Survival Analysis.
