 | |
| |
Applied Survival Analysis: Regression Modeling of Time to Event Data
 |
Author: David W. Hosmer Jr., Stanley Lemeshow
List Price: $99.95
Our Price: Click to see the latest and low price
ISBN: 0471154105
Publisher: Wiley-Interscience (07 January, 1999)
Edition: Hardcover
Sales Rank: 74,815
Average Customer Rating: 5 out of 5
|
Customer ReviewsRating: 5 out of 5
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: 5 out of 5
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 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.
Rating: 5 out of 5
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 social and behavioral scientists interesting in learning the fundamentals of these models, as well as a useful reference for applied researchers.
Similar Products
· Survival Analysis Using the SAS System: A Practical Guide
| | | | | |
| |
