» Survival Analysis: A Self-Learning Text (Statistics for Biology and Health)
Rating: 4.0 / 5.00 (8 reviews)
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Survival Analysis: A Self-Learning Text (Statistics for Biology and Health) Details
Binding: HardcoverDewey Decimal Number: 610.72
EAN: 9780387239187
ISBN: 0387239189
Label: Springer
Manufacturer: Springer
Number Of Items: 1
Number Of Pages: 590
Publication Date: 2005-08-16
Publisher: Springer
Studio: Springer
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Survival Analysis: A Self-Learning Text (Statistics for Biology and Health) Reviews
Customer Rating:Summary: Great introduction book
Comment: 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.
Customer Rating:
Summary: Poorly Written, Poorly Conceived
Comment: 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.
Customer Rating:
Summary: Clarity at last!
Comment: 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.
Customer Rating:
Summary: useful book
Comment: 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.
Customer Rating:
Summary: The only survival analysis book you'll ever need
Comment: A very well written, step by step book on survival analysis, recommended for all, absolute beginners as well as experienced
biostatisticians.
The authors truly deserve praise.
More Reviews for Survival Analysis: A Self-Learning Text (Statistics for Biology and Health)
Editorial Review for Survival Analysis: A Self-Learning Text (Statistics for Biology and Health):
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.
