ABSTRACT
The thing that characterizes event history and survival data the most is its dynamic nature. Individuals are followed over time, and during that course, the timings of events of interest are noted. Naturally, thingsmay happen that makes it necessary to interrupt an individual follow-up, such as the individual suddenlydisappearing for some reason. With classical statistical tools, such as linear regression, these observationsare difficult or impossible to handle in the analysis. The methods discussed in this book aim, among otherthings, at solving such problems. The special techniques that constitute survival and event history analysisare motivated. The concepts of right censoring and left truncation are defined and discussed. Real life dataexamples, used throughout the book, are described.
