This volume examines modern techniques and research problems in the analysis of lifetime data analysis. This area of statistics deals with time-to-event data which is complicated not only by the dynamic nature of events occurring in time but also by censoring where some events are not observed directly, but rather they are known to fall in some interval or range.

Historically survival analysis is one of the oldest areas of statistics dating its origin to classic life table construction begun in the 1600s.  Much of the early work in this area involved constructing better life tables and long tedious extensions of non-censored nonparametric estimators.  Modern survival analysis began in the late 1980s with pioneering work by Odd Aalen on adapting classical Martingale theory to these more applied problems.  Theory based on these counting process martingales made the development of techniques for censored and truncated data in most cases easier and opened the door to both Bayesian and classical statistics for a wide range of  problems and applications.

In this volume we present a series of chapters which provide an introduction to the advances in survival analysis techniques in the past thirty years.  These chapters can serve four complementary purposes. First, they provide an introduction to various areas in survival analysis for graduates students and other new researchers to this field.  Second, they provide a reference to more-stablished investigators in this area of modern investigations into survival analysis.  Third, with a bit of supplementation on counting process theory this volume is useful as a text for a second or advanced course in survival analysis.  We have found  that the instructor of such a course can pick and choose chapters in areas he/she deems most useful to the students or areas of  interest to the instructor.  Lastly, these chapters can help practicing statisticians pick the best statistical method to analyze their survival data experiment.

To help with reading the volume we have grouped chapters into six parts, each with a brief introduction by the editor. These parts are:

  I Regression Models for Right Censoring  
 II Competing Risks  
III Model Selection and Validation  
 IV Other Censoring Schemes  
  V Multivariate/Multistate Models
 VI Clinical Trials

We believe that the chapters and topics presented here provide a good overview of the current status of survival analysis and will further inspire research into this area.

We would like to express our thanks to all the authors who contributed their time and effort to this volume.  Without these contributions the volume would not be possible.  A special thank you goes to Professor van Houwelingen who took upon himself much of the work of putting the authors' LaTeX and pdf files into a book format.