eShop USA > Books > Applied Survival Analysis: Regression Modeling of Time to Event Data (Wiley Series in Probability and Statistics)
Applied Survival Analysis: Regression Modeling of Time to Event Data (Wiley Series in Probability and Statistics)
List Price: $110.00Our Price: $88.00 You Save: $22.00 (20%)Prices subject to change.
Availability: Usually ships in 24 hours
Save $10.00 when you spend $50.00 or more on qualifying items offered by Amazon.com. Enter code BMLSAVES at checkout.
Binding: Hardcover
Dewey Decimal Number: 610.727
EAN: 9780471754992
Edition: 2
ISBN: 0471754994
Label: Wiley-Interscience
Manufacturer: Wiley-Interscience
Number Of Items: 1
Number Of Pages: 416
Publication Date: March 07, 2008
Publisher: Wiley-Interscience
Studio: Wiley-Interscience
Related Items: Featured Listmania!
Editorial Review:
Applied Survival Analysis: Regression Modeling of Time to Event Data, Second Edition provides a comprehensive, self-contained introduction to regression modeling used in the analysis of time-to-event data in epidemiological, biostatistical, and other health-related research. Unlike other texts on the subject, it focuses almost exclusively on practical applications rather than mathematical theory and it offers clear, accessible presentations of modern modeling techniques supplemented with real-world examples and case studies.
Customer Reviews
Average Rating: 
Rating:  - A Good Read, but Read it Carefully!
The authors provide a really nice, non-technical survey of the landscape for Cox Proportional Hazards models. A nice aspect of their treatment is the care they take to reference all highly technical texts and journal articles. For example, if you'd like to find out more about goodness-of-fit tests for survival models, the authors provide ample references to the Counting Process Theory of Martingale Residuals.
The first chapter discusses the basic characteristics of survival data, including ... Read More
Rating: - nice introduction
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.
Rating: - Great conceptual Introduction to Cox regression analysis
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 ... Read More
Rating: - A clear, simple introduction to survival models
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 ... Read More
Rating: - Excellent Nontechnical Coverage of Survival Analysis
Applied Survival Analysis is an excellent book for someone seeking a non-mathematicial explanation of survival analysis. The book covers the motivation behind the development of survival analysis, estimation of survival curves, the Cox proportionial hazards, and some parametric models. The book also covers the major methods used in variable selection, model building, and diagnostics. Someone with an undergraduate background in statistics and econometrics will understand the book. The book relies on text ... Read More
Related Categories:
| |
 |
