» Statistical Models and Methods for Lifetime Data (Wiley Series in Probability and Statistics)
Statistical Models and Methods for Lifetime Data (Wiley Series in Probability and Statistics) Details
Binding: HardcoverDewey Decimal Number: 519.5
EAN: 9780471372158
ISBN: 0471372153
Label: Wiley-Interscience
Manufacturer: Wiley-Interscience
Number Of Items: 1
Number Of Pages: 664
Publication Date: 2002-11-27
Publisher: Wiley-Interscience
Studio: Wiley-Interscience
Items related to Statistical Models and Methods for Lifetime Data (Wiley Series in Probability and Statistics)
- The Statistical Analysis of Failure Time Data (Wiley Series in Probability and Statistics)
- Statistical Methods for Reliability Data (Wiley Series in Probability and Statistics)
- Survival Analysis Using SAS: A Practical Guide
- Survival Analysis: A Self-Learning Text (Statistics for Biology and Health)
- The Statistical Analysis of Recurrent Events (Statistics for Biology and Health)
Statistical Models and Methods for Lifetime Data (Wiley Series in Probability and Statistics) Reviews
Customer Rating:




Summary: one of the best texts on life data analysis
Comment: When I started my biostatistical career in 1995 at a medical device company this was the book I relied on for valuable reference information on life tables and survival curves. This book is particularly good at dealing with nonparametric methods and covering the distinctions between the various types of censoring.
There are now also a number of other good books with more recent developments. Nelson's book was a competitor. Under the subject of reliability the same important paramatric models are covered in such books as the one by Mann, Schafer and Singpurwalla, the recent text by Meeker and Escobar and the book by Blischke and Murthy. Hougaard covers multivariate models.
Customer Rating:





Summary: Excellent for Pre-Multivariate Survival Analysis
Comment: This is one of the best books about survival data analysis, or lifetime analysis. This book covers univariate survival data analysis, providing necessary mathematical details. But it does not deal with multivariate cases. If you are climbing from the univariate toward multivariate, and taking a rest, this is perfect. This books is kind. However, watch two warnings. If you need accompanying software manuals, this book doesn't provide S-Plus, SAS, Stata or other advanced software code. Second, if you need competing risk or multivariate model, try others, including Hougaard or Cox. Elisa T. Lee's book presents less detail, but is still excellent, or may be better, depending reader's needs.
Customer Rating:





Summary: one of my favorite books on survival analysis
Comment: When I started my biostatistical career in 1995 at a medical device company this was the book I relied on for valuable reference information on life tables and survival curves. This book is particularly good at dealing with nonparametric methods and covering the distinctions between the various types of censoring. There are now also a number of other good books with more recent developments. Nelson's book was a competitor. Under the subject of reliability the same important paramatric models are covered in such books as the one by Mann, Schafer and Singpurwalla, the recent text by Meeker and Escobar and the book by Blischke and Murthy. Hougaard cover multivariate models.
Editorial Review for Statistical Models and Methods for Lifetime Data (Wiley Series in Probability and Statistics):
Praise for the First Edition"An indispensable addition to any serious collection on lifetime data analysis and . . . a valuable contribution to the statistical literature. Highly recommended . . ."
-Choice
"This is an important book, which will appeal to statisticians working on survival analysis problems."
-Biometrics
"A thorough, unified treatment of statistical models and methods used in the analysis of lifetime data . . . this is a highly competent and agreeable statistical textbook."
-Statistics in Medicine
The statistical analysis of lifetime or response time data is a key tool in engineering, medicine, and many other scientific and technological areas. This book provides a unified treatment of the models and statistical methods used to analyze lifetime data.
Equally useful as a reference for individuals interested in the analysis of lifetime data and as a text for advanced students, Statistical Models and Methods for Lifetime Data, Second Edition provides broad coverage of the area without concentrating on any single field of application. Extensive illustrations and examples drawn from engineering and the biomedical sciences provide readers with a clear understanding of key concepts.
New and expanded coverage in this edition includes:
* Observation schemes for lifetime data
* Multiple failure modes
* Counting process-martingale tools
* Both special lifetime data and general optimization software
* Mixture models
* Treatment of interval-censored and truncated data
* Multivariate lifetimes and event history models
* Resampling and simulation methodology



