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Survival Analysis

A Self-Learning Text

  • Textbook
  • Nov 2010


  • Second edition of the text originally published in 1996
  • New material has been added and the original six chapters have been modified
  • Includes supplementary material:

Part of the book series: Statistics for Biology and Health (SBH)

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About this book

This is the second edition of this text on survival analysis, originallypublishedin1996. Asinthe?rstedition,eachch- ter contains a presentation of its topic in “lecture-book” f- mat together with objectives, an outline, key formulae, pr- tice exercises, and a test. The “lecture-book” format has a sequence of illustrations and formulae in the left column of eachpageandascriptintherightcolumn. Thisformatallows youtoreadthescriptinconjunctionwiththeillustrationsand formulae that high-light the main points, formulae, or ex- ples being presented. This second edition has expanded the ?rst edition by adding three new chapters and a revised computer appendix. The three new chapters are: Chapter 7. Parametric Survival Models Chapter 8. Recurrent Event Survival Analysis Chapter 9. Competing Risks Survival Analysis Chapter 7 extends survival analysis methods to a class of s- vival models, called parametric models, in which the dist- bution of the outcome (i. e. , the time to event) is speci?ed intermsofunknownparameters. Manysuchparametricmodels are acceleration failure time models, which provide an alt- native measure to the hazard ratio called the “acceleration factor”. The general form of the likelihood for a parametric model that allows for left, right, or interval censored data is also described. The chapter concludes with an introduction to frailty models. Chapter8considerssurvivaleventsthatmayoccurmorethan once over the follow-up time for a given subject. Such events are called “recurrent events”.

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Table of contents (9 chapters)


"Imagine---a statistics textbook that actually explains things in English instead of explaining a topic by bombarding the reader with page-widthj 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)

From the reviews of the second edition:

"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

"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)

Authors and Affiliations

  • Department of Epidemiology Rollins School of Public Health, Emory University, Atlanta

    David G. Kleinbaum, Mitchel Klein

About the authors

David Kleinbaum is Professor of Epidemiology at the Rollins School of Public Health at Emory University, Atlanta, Georgia. Dr. Kleinbaum is internationally known for innovative textbooks and teaching on epidemiological methods, multiple linear regression, logistic regression, and survival analysis. He has provided extensive worldwide short-course training in over 150 short courses on statistical and epidemiological methods. He is also the author of ActivEpi (2002), an interactive computer-based instructional text on fundamentals of epidemiology, which has been used in a variety of educational environments including distance learning.

Mitchel Klein is Research Assistant Professor with a joint appointment in the Department of Environmental and Occupational Health (EOH) and the Department of Epidemiology, also at the Rollins School of Public Health at Emory University. Dr. Klein is also co-author with Dr. Kleinbaum of the second edition of Logistic Regression- A Self-LearningText (2002). He has regularly taught epidemiologic methods courses at Emory to graduate students in public health and in clinical medicine. He is responsible for the epidemiologic methods training of physicians enrolled in Emory’s Master of Science in Clinical Research Program, and has collaborated with Dr. Kleinbaum both nationally and internationally in teaching several short courses on various topics in epidemiologic methods.

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