Survival Analysis: A Self-Learning Text (Statistics for Biology and Health) [Hardcover]

David Kleinbaum (Author), Mitchel Klein (Author)

Book Description

Publication Date: February 20, 1997 | ISBN-10: 0387945431 | ISBN-13: 978-0387945439 | Edition: Corrected

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. Readers can then extend their knowledge with a more thoroughgoing test. Answers to both are included. Beginning with the basic concepts of survival analysis-time to an event as a variable, censored data, and the hazard function-the author then introduces the Kaplan-Meier survival curves, the log-rank test, the Peto test, and the most widely used technique in survival analysis, the Cox proportional hazards model. Later chapters cover techniques for evaluating the proportional hazards assumptions, the stratified Cox procedure, and extending the Cox model to time-dependent variables. Readers will enjoy David Kleinbaum's style of presentation with numerous figures and diagrams illustrating each idea. As a result, this text makes an excellent introduction for all those coming to the subject for the first time.

Editorial Reviews

Review

"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) --This text refers to an out of print or unavailable edition of this title.

From the Back Cover

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 text refers to an out of print or unavailable edition of this title.

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Product Details

• Hardcover: 324 pages
• Publisher: Springer; Corrected edition (February 20, 1997)
• Language: English
• ISBN-10: 0387945431
• ISBN-13: 978-0387945439
• Product Dimensions: 9.6 x 8.3 x 0.8 inches
• Shipping Weight: 2 pounds
• Average Customer Review: 4.1 out of 5 stars  See all reviews (14 customer reviews)
• Amazon Best Sellers Rank: #1,507,532 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

36 of 37 people found the following review helpful:

5.0 out of 5 stars Excellent Introduction to Survival Analysis, August 5, 1999

By 

Michael Kim (Elk Grove, CA) - See all my reviews
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This review is from: Survival Analysis: A Self-Learning Text (Statistics for Biology and Health) (Hardcover)

Kleinbaum's Survival Analysis: A Self-Learning Text is an excellent nontechnical introduction to survival analysis. Survival analysis are statistical techniques that addresses the problem of how much time it takes for an event to occur. The techniques is widely used in medical research, and my interest in it comes from wanting to explore how long it will take for a person to refinance a loan. Kleinbaum explores the topic in a straightforward, and easy-to-follow manner. The topics are illustrated through numerous figures, diagrams, and analysis of real data sets. Kleinbaum uses a minimial amount of mathematics and carefully leads the reader through any math that is used. The book concentrates on the Cox Proportional Hazard model which is the most widely used technique in survival analysis. Given the introductory nature of the book one will not find materials covering other models. Someone with some mathematical knowledge, one semester of calculus, and a semester of statistics and a semester of undergraduate econometrics would get the most out of this book. If you are looking for an introduction to survival analysis this is a great place to start. I feel I have a strong foundation to start using survival analysis at my job and continue with a more technical exploration.

13 of 13 people found the following review helpful:

5.0 out of 5 stars Clarity at last!, August 31, 2006

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A Runner "mk" (Greeley, CO) - See all my reviews

This review is from: Survival Analysis: A Self-Learning Text (Statistics for Biology and Health) (Hardcover)

I'm ABD Economics and down to the dissertation. I have 10 titles on my shelf that deal directly with survival/event-history analysis. I've plowed though them all. Finally (!) I have one that is useful; and, this is the one. If you are not already familiar with this method and/or you are only going to get one book - this is the one to acquire. Far and away it beats everything else I've purchased. Don't be put off the by epidemiological examples - they're easy enough to read through. The authors' personal preference seems to be for STATA, but SAS and SPSS code are available in the appendix.

16 of 18 people found the following review helpful:

5.0 out of 5 stars Survival Analysis and you...., December 16, 1999

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Tomoko R. Sampson (Saint Louis, MO) - See all my reviews
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This review is from: Survival Analysis: A Self-Learning Text (Statistics for Biology and Health) (Hardcover)

I'm a graduate student in public health at Emory University and have had the opportunity to actually take the course in Epidemiologic Modeling with Dr. Kleinbaum. This book, as well as his self-learning text for logistic regression, are fabulous. Both books provide a good background to the methods needed to use each analytical technique. Survival Analysis: A Self-Learning Text, in particular, flows very well with good examples, diagrams, and explanations for the student who wishes to learn this technique. It also serves a great reference for those who use this analytical method.