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Applied Survival Analysis Using R

  • Dirk F.¬†Moore

Part of the Use R! book series (USE R)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Dirk F. Moore
    Pages 1-10
  3. Dirk F. Moore
    Pages 11-24
  4. Dirk F. Moore
    Pages 25-42
  5. Dirk F. Moore
    Pages 73-86
  6. Dirk F. Moore
    Pages 87-100
  7. Dirk F. Moore
    Pages 101-111
  8. Dirk F. Moore
    Pages 137-155
  9. Dirk F. Moore
    Pages 177-199
  10. Dirk F. Moore
    Pages E1-E13
  11. Back Matter
    Pages 201-226

About this book

Introduction

Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis.

Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis, as well as a basic knowledge of calculus and the R system, will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points, shedding light on the application of survival analysis in a way that is useful for graduate students, researchers, and practitioners in biostatistics.

  • Clearly illustrates concepts of survival analysis principles and analyzes actual survival data using R, in addition to including an appendix with a basic introduction to R
  • Organized via basic concepts and most frequently used procedures, with advanced topics toward the end of the book and in appendices
  • Includes multiple original data sets that have not appeared in other textbooks

Dirk F. Moore is Associate Professor of Biostatistics at the Rutgers School of Public Health and the Rutgers Cancer Institute of New Jersey. He received a Ph.D. in biostatistics from the University of Washington in Seattle and, prior to joining Rutgers, was a faculty member in the Statistics Department at Temple University. He has published numerous papers on the theory and application of survival analysis and other biostatistics methods to clinical trials and epidemiology studies.

Keywords

censoring partial likelihood proportional hazards survival data truncation competing risks analyses confidence intervals product-limit Kaplan-Meier estimator Nelson-Aalen nonparametric estimator survival curves log-rank test Prentice-modification of Gehan test

Authors and affiliations

  • Dirk F.¬†Moore
    • 1
  1. 1.Department of BiostatisticsRutgers School of Public HealthPiscatawayUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-31245-3
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-31243-9
  • Online ISBN 978-3-319-31245-3
  • Series Print ISSN 2197-5736
  • Series Online ISSN 2197-5744
  • Buy this book on publisher's site
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