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Product Description
Review
"It is well suited for teaching a graduate-level course in medical statistics, and the data sets used in the book are available online." (Biometrical Journal, August 2009)
"This is a superb resource - a practical guide with up-to-date applications. The authors are excellent teachers of the mathematics and application of survival data regression modeling." (Doodys, August 2009)
"The extensive and detailed coverage of the process of survival model fitting, as well as the applied exercises, make this textbook an excellent choice for an applied survival analysis course." (Journal of Biopharmaceutical Statistics, Volume 18, Issue 6, 2008)
International Journal of Epidemiology, Volume 30 No 2 2001
...ideal textbook for people with knowledge of regression analysis who want to become acquainted with the methods of survival analysis.
--This text refers to an alternate
Hardcover
edition.
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Most helpful customer reviews
5.0 out of 5 stars
nice introduction,
By A Customer
This review is from: Applied Survival Analysis: Regression Modeling of Time to Event Data (Hardcover)
This book provides a good, clear, concise explanation of Cox's proportional hazards models. For someone seeking a non-mathematical description this is a great guide. The original datasets from the text examples can even be downloaded and you can go through the same process yourself. Because of some mistakes in the text, I would recomend looking at other sources as well.
5.0 out of 5 stars
Great conceptual Introduction to Cox regression analysis,
By T Richards (Pittsburgh, PA) - See all my reviews
This review is from: Applied Survival Analysis: Regression Modeling of Time to Event Data (Hardcover)
I enjoyed the authors' book on logistic regression analysis in 1989, and this book is just as good, or better, with many extremely practical suggestions on building regression models for survival data. Happily, the authors summarize, compare, and contrast several major texts on survival analysis which have appeared in the past 10 years. For example, they discuss different names used by different authors for score residuals. They present a helpful appendix on the counting process approach to survival analysis, which will make more advanced texts accessible to students; thus, anyone who wants to use survival analysis, at any level, should consult this book, even if he has already studied books by Miller, Lee, Collett, Fleming-Harington,Andersen, et al, etc. An unfortunate drawback to this book is that the first printing contains many careless errors, some of which may affect student learning: for example, the definition of a survival function is misstated. I recommend that you insist on the second or third printing when buying this book, and you will be quite satisfied.
5.0 out of 5 stars
A clear, simple introduction to survival models,
By C. Zorn (Atlanta, GA) - See all my reviews
This review is from: Applied Survival Analysis: Regression Modeling of Time to Event Data (Hardcover)
Hosmer and Lemeshow have given us a clear, nontechnical introduction to using survival models. The book strikes a good balance between covering the basics and addressing the most recent, state-of-the-art techniques, including repeated events, frailty models, and others. They also do a good job of addressing practical issues, including estimation details and available software. While most of the examples are drawn from medicine and biostatistics, this book could also serve as a useful starting point for social and behavioral scientists interesting in learning the fundamentals of these models, as well as a useful reference for applied researchers.
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