Overview
- This book enables the reader to analyse complex time-to-event data himself, using the free open source language R for statistical computing
- The data situations considered are competing risks--several, mutually exclusive event types and multistate models, that track an individuals history through different stages over time. These methods are a generalization of the now classical survivalanalysis--the analysis of time to one single event. Such data occur in a variety of fields, including life sciences, social sciences, economics and engineering
- The methods are explained on a non-technical level and instantly carried out in R. This book covers data structures, simulating data, analyses of real life data and plotting
- Includes supplementary material: sn.pub/extras
Part of the book series: Use R! (USE R)
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Table of contents (12 chapters)
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Front Matter
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Data examples and some mathematical background
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Front Matter
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Back Matter
Keywords
About this book
Authors and Affiliations
About the authors
The authors are affiliated with the Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg and the Freiburg Center for Data Analysis and Modelling, University of Freiburg, Germany. Jan Beyersmann is Senior Statistician and serves on the editorial board of Statistics in Medicine. Arthur Allignol is Statistician and has contributed several R packages on competing risks and multistate models. Martin Schumacher is Professor of Biostatistics and Director of the Institute of Medical Biometry and Medical Informatics, Freiburg. He has been involved in theoretical developments as well as in practical applications of survival analyses and their extensions over many years.
Bibliographic Information
Book Title: Competing Risks and Multistate Models with R
Authors: Jan Beyersmann, Arthur Allignol, Martin Schumacher
Series Title: Use R!
DOI: https://doi.org/10.1007/978-1-4614-2035-4
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC 2012
Softcover ISBN: 978-1-4614-2034-7Published: 17 November 2011
eBook ISBN: 978-1-4614-2035-4Published: 18 November 2011
Series ISSN: 2197-5736
Series E-ISSN: 2197-5744
Edition Number: 1
Number of Pages: XI, 245
Number of Illustrations: 49 b/w illustrations
Topics: Statistical Theory and Methods