Statistical Models and Methods for Lifetime Data (Wiley Series in Probability and Statistics)

A unified treatment of models and statistical methods used in the analysis of lifetime or response time data. Draws together the most important, up-to-date methods used in engineering, medical and the biological sciences, including parametric, distribution-free, nonparametric, and graphical methods. Numerical illustrations and examples involving real data demonstrate the application of each method to problems in areas such as reliability, product performance evaluation, clinical trials, and experimentation in the biomedical sciences.

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