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Competing Risks and Multistate Models with R

By Jan Beyersmann , Arthur Allignol , Martin Schumacher

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This book explains hazard-based analyses of competing risks and multistate data using the R statistical programming code, placing special emphasis on interpretation of results. Includes real data examples, and encourages readers to simulate their own data.

Full Description

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  • ISBN13: 978-1-4614-2034-7
  • 256 Pages
  • Publication Date: November 18, 2011
  • Available eBook Formats: PDF
Full Description
This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models). Both R and multistate methods are promoted with a focus on nonparametric methods.
Table of Contents

Table of Contents

  1. Data examples.
  2. An informal introduction to hazard
  3. based analyses.
  4. Competing risks.
  5. Multistate modelling of competing risks.
  6.  Nonparametric estimation.
  7. Proportional hazards models.
  8. Nonparametric hypothesis testing.
  9. Further topics in competing risks.
  10. Multistate models and their connection to competing risks.
  11. Nonparametric estimation.
  12. Proportional transition hazards models.
  13. Time
  14. dependent covariates and multistate models.
  15. Further topics in multistate modeling.

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