Handbook of Survival Analysis

John P. Klein, Hans C. van Houwelingen, Joseph G. Ibrahim, Thomas H. Scheike

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$79.96

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July 22, 2013 by Chapman and Hall/CRC
Handbook - 656 Pages - 89 B/W Illustrations
ISBN 9781466555662 - CAT# K15384
Series: Chapman & Hall/CRC Handbooks of Modern Statistical Methods

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Features

  • Helps statisticians pick the best statistical method to analyze their survival data experiment
  • Provides statistical methods for right-censored and left-truncated survival data
  • Describes numerous techniques for regression modeling of competing risks data
  • Examines techniques for model selection and validation as well as the robustness of the Cox regression model
  • Discusses the estimation of models with more complex censoring and sampling schemes than simple right censoring
  • Presents multistate models for a patient’s complete disease/recovery process and multivariate models that have some dependency between a set of event times
  • Covers topics useful in the design and analysis of clinical trials where the outcome is the time to some event
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Summary

Handbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis. This area of statistics deals with time-to-event data that is complicated by censoring and the dynamic nature of events occurring in time.

With chapters written by leading researchers in the field, the handbook focuses on advances in survival analysis techniques, covering classical and Bayesian approaches. It gives a complete overview of the current status of survival analysis and should inspire further research in the field. Accessible to a wide range of readers, the book provides:

  • An introduction to various areas in survival analysis for graduate students and novices
  • A reference to modern investigations into survival analysis for more established researchers
  • A text or supplement for a second or advanced course in survival analysis
  • A useful guide to statistical methods for analyzing survival data experiments for practicing statisticians