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Survival Analysis for Epidemiologic and Medical Research (Practical Guides to Biostatistics and Epidemiology), by Steve Selvin
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This practical guide shows why the analytic methods work and how to effectively analyze and interpret epidemiologic and medical survival data with the help of modern computer systems. The introduction presents a review of a variety of statistical methods that are not only key elements of survival analysis but are also central to statistical analysis in general. Techniques such as statistical tests, transformations, confidence intervals, and analytic modeling are presented in the context of survival data but are, in fact, statistical tools that apply to understanding the analysis of many kinds of data. Similarly, discussions of such statistical concepts such as bias, confounding, independence, and interaction are presented in the context of survival analysis as well as the basic components of a broad range of applications.
- Sales Rank: #17089853 in Books
- Published on: 2010-02-03
- Original language: English
- Binding: Printed Access Code
Review
'... for students who know very little about statistics and mathematics this book is a welcome resource on the techniques used to analyse time-to-event data. These techniques are introduced in a non-technical way accompanied with many good examples. Also the included R-code gives a good introduction to the practical analysis.' Biometrical Journal
'This book provides an easy-to-read introduction to the fundamental concepts applicable to survival analysis without relying on mathematical prerequisites. ... [the] text gives a thorough introduction to the area of survival analysis for those with little prior statistical knowledge.' International Journal of Epidemiology
About the Author
Steve Selvin is Professor of Biostatistics and Epidemiology at the University of California, Berkeley. He has taught on the Berkeley campus for 35 years and has authored or co-authored more than 200 scientific articles in the areas of applied statistics and epidemiology. He has received two university teaching awards and is a member of the ASPH/Pfizer Public Health Academy of Distinguished Teachers.
Most helpful customer reviews
1 of 1 people found the following review helpful.
well written
By SD
The book provides a good introduction to survival analysis concepts. The author really goes out of his way to describe as clearly as possible but succinctly what the underlying principles are, both in word as in mathematical formula. All discussed concepts and formula's are accompanied by examples, which are presented in detail. Mathematical formula's are kept to the strictly necessary without making things simpler then they are (no easy feat but well balanced in this book).
However, what really makes this book stand out is it's enthusiastic but critical voice on the presented techniques and the frequently repeated warnings on checking assumptions. Also, the author often makes seemingly offhand comments on e.g. the subjectivity of certain aspects of analysis (e.g. evaluation of residuals or of model selection) which enriches the text enormously. These things are often missing from statistical text books.
I think this book can serve very well both as a textbook for a course as well as an introduction to survival analysis for people with a working knowledge of basic mathematics or statistics. It's a breeze if you're well versed in other domains of statistics and look for info on survival analysis. It's however not a cookbook with step by step recipes. A small tutorial in R is provided at the end but more as an appetizer. But that is simply not the scope of the book as the author clearly states.
At the end of the day, it's simply a well written book.
Note on Kindle edition: the conversion to kindle is one of the best I've seen for a technically oriented book (but maybe I haven't seen enough of them yet). Graphs and formulas are easily readable in the topaz format.
1 of 1 people found the following review helpful.
Not the right focus as a practical guide
By W. YIP
Compared with other books on survival analysis, this is just an okay book. I actually find it difficult to understand some of the passage probably because the author tries to write to people with "minimal" statistical knowledge. (e.g. p194 when he tries to explain confounding or p196-7 when he tries to explain the loss of statistical power) I am surprised to find the book contains a whole chapter on life table. On the positive side, it is a good description of what life table is and how to use it; on the negative side, it is not commonly used in survival analysis outside of actuarial analysis. It is not clear why the author chooses to include such a topic in an introductory book. Furthermore, the emphasis of the book is on parametric models (accelerated failure time models) such as exponential or Weibull with three chapters (5,6 and 8). In practice, most people use KM or Cox PH models. This may be the author's strength, but it seems to be the wrong focus for a practical guide. I would prefer the author to spend more time on Cox PH model. However, the book is well written and contains useful information.
0 of 0 people found the following review helpful.
Three Stars
By XY77
Nice.
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