Modeling Discrete Time-to-Event Data

  • Gerhard Tutz
  • Matthias Schmid

Part of the Springer Series in Statistics book series (SSS)

Table of contents

  1. Front Matter
    Pages i-x
  2. Gerhard Tutz, Matthias Schmid
    Pages 1-13
  3. Gerhard Tutz, Matthias Schmid
    Pages 15-34
  4. Gerhard Tutz, Matthias Schmid
    Pages 35-72
  5. Gerhard Tutz, Matthias Schmid
    Pages 73-104
  6. Gerhard Tutz, Matthias Schmid
    Pages 105-127
  7. Gerhard Tutz, Matthias Schmid
    Pages 129-148
  8. Gerhard Tutz, Matthias Schmid
    Pages 149-165
  9. Gerhard Tutz, Matthias Schmid
    Pages 167-184
  10. Gerhard Tutz, Matthias Schmid
    Pages 185-211
  11. Gerhard Tutz, Matthias Schmid
    Pages 213-223
  12. Back Matter
    Pages 225-247

About this book


This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are explained. Each section includes a set of exercises on the respective topics. Various functions and tools for the analysis of discrete survival data are collected in the R package discSurv that accompanies the book. 


Survival data Survival functions Discrete hazard function Time-to-Event Data Life tables Discrete hazard model Continuation ratio model Goodness-of-Fit Time-dependent AUC discSurv Interval censoring Recursive partitioning Multiple spells Competing risks Generalized estimation equations Sequential methods in item response theory Discrete frailty model Smooth effects Additive models Penalized regression Gradient boosting

Authors and affiliations

  • Gerhard Tutz
    • 1
  • Matthias Schmid
    • 2
  1. 1.LMU MunichMünchenGermany
  2. 2.University of BonnBonnGermany

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-28156-8
  • Online ISBN 978-3-319-28158-2
  • Series Print ISSN 0172-7397
  • Series Online ISSN 2197-568X
  • Buy this book on publisher's site
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