Abstract
Time-to-event data, frequently referred to as survival data, consist of two pieces of information for each subject: the time under observation and the ultimate outcome at the end of that time. Analysis of these data is complicated because the follow-up time often is different for each participant, and the event of interest, such as myocardial infarction, often is not observed in all the subjects by the end of the study. For those participants in whom the event of interest is not observed, what is known is that their survival times are longer than their time spent in the study, but their exact survival times are unknown. This chapter describes features of time-to-event data and introduces the Kaplan–Meier or product-limit estimator for the survival function. It also presents several approaches for comparing two survival curves, a summary of stratified analysis methods, and Cox's proportional hazards regression analysis.
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