Survival Analysis
A Self-Learning Text
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Beschreibung
This greatly expanded second edition of Survival Analysis- A Self-learning Text provides a highly readable description of state-of-the-art methods of analysis of survival/event-history data. This text is suitable for researchers and statisticians working in the medical and other life sciences as well as statisticians in academia who teach introductory and second-level courses on survival analysis. The second edition continues to use the unique "lecture-book" format of the first (1996) edition with the addition of three new chapters on advanced topics:
Chapter 7: Parametric Models
Chapter 8: Recurrent events
Chapter 9: Competing Risks.
Also, the Computer Appendix has been revised to provide step-by-step instructions for using the computer packages STATA (Version 7.0), SAS (Version 8.2), and SPSS (version 11.5) to carry out the procedures presented in the main text.
The original six chapters have been modified slightly
to expand and clarify aspects of survival analysis in response to suggestions by students, colleagues and reviewers, and
to add theoretical background, particularly regarding the formulation of the (partial) likelihood functions for proportional hazards, stratified, and extended Cox regression models
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-Learning Text (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.
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 in termsofunknownparameters. 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”.
Second edition of the text originally published in 1996
New material has been added and the original six chapters have been modified
This text on survival analysis provides a straightforward and easy-to-follow introduction to the main concepts and techniques of the subject. It is based on numerous courses given by the author to students and researchers in the health sciences and is written with such readers in mind.
Throughout, there is an emphasis on presenting each new topic motivated with real examples of a survival analysis investigation, and then presenting thorough analyses of real data sets. Each chapter concludes with practice exercises to help readers reinforce their understanding of the concepts covered in the chapter.
Autor*in
David G. Kleinbaum
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Excel Likelihood Logistic Regression SAS SPSS Survival Analysis linear regression
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"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)
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