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

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

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Authors: David G. Kleinbaum, Mitchel Klein
Publisher: Springer
Category: Book

List Price: $94.95
Buy New: $68.48
You Save: $26.47 (28%)



New (34) Used (11) from $65.04

Avg. Customer Rating: 4.0 out of 5 stars 9 reviews
Sales Rank: 200597

Media: Hardcover
Edition: 2nd
Number Of Items: 1
Pages: 590
Shipping Weight (lbs): 2.6
Dimensions (in): 9.3 x 7.2 x 1.3

ISBN: 0387239189
Dewey Decimal Number: 610.72
EAN: 9780387239187
ASIN: 0387239189

Publication Date: August 16, 2005
Availability: Usually ships in 1-2 business days
Shipping: Expedited shipping available
Shipping: International shipping available
Condition: New Book. International Shipping Available

Also Available In:

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

Accessories:

  • Oceans and Health:: Pathogens in the Marine Environment
  • Forecasting Product Liability Claims: Epidemiology and Modeling in the Manville Asbestos Case (Statistics for Biology and Health)
  • A Pocket Guide to Epidemiology

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  • The Little SAS Book: A Primer, Third Edition
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Editorial Reviews:

Product Description

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.




Customer Reviews:   Read 4 more reviews...

5 out of 5 stars Excellent, excellent resource!   October 17, 2008
Like other reviewers, I've scoured the bookstores looking for a good resource to provide a practical approach to conducting a survival analysis, and this book--hands down--is the best resource I have found yet. It is written in a very accessible style, and the formulas are written out in plain English so that you can intelligently communicate them to others. The chapters are well written, and each ends with practice questions that are extremely helpful.

My only criticism is that the authors do not address the issue of discrete-time survival analysis, which is often necessary when the underlying hazard rates in your unit of time (e.g., day, week, month) exceeds .20 or so at any point. If you find yourself in that situation, then I would recommend the text by Singer and Willett (2003) Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. However, the Willett and Singer book is much more dense and difficult. If you don't have to worry with discrete-time analysis, then "Survival Analysis: A Self-Learning Text" is as close to 'one-stop-shopping' you can get.



5 out of 5 stars Great introduction book   July 15, 2008
I am statistics major and I use this book to self-taught. This book clears the basic concepts. It is very easy to read and follow. If you are like me, I guess this the book that you need.


2 out of 5 stars Poorly Written, Poorly Conceived   December 20, 2007
 0 out of 1 found this review helpful

This book struck almost every single one of my biggest peeves about texts. Numbers written out as words: this is, essentially, a mathematics book. We don't like letters, we like numbers, and writing out "thirteen point five" is only outdone by the obnoxiousness of writing out whole equations in the text. Readers who need to be told that "X-3/ln(X+5)" means "x plus three divided by the natural log of x plus five" should probably not be using this text.

Second, the details of examples are sparsely filled, and examples don't go all the way through. Many of them are great for theoretical concepts, like how a statistic works, but give no hint as to how one might actually employ it. Page after page of SAS, STATA, and SPIDA output are useless without the accompanying code to create them.

The index is astoundingly cursory. It's really hard to find anything.

Frankly a worthless text, I'm glad I bought it used.



5 out of 5 stars Clarity at last!   August 31, 2006
 6 out of 6 found this review helpful

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.


4 out of 5 stars useful book   March 5, 2006
 2 out of 2 found this review helpful

this is a very useful book to introduce you to the concepts of survival analysis. It is better for those who already have basic knoweledge abour regression models but it can be used by beginners as well. Basic knowledge of statistics is strongly required.

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