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.