Abstract
The survival analysis methodology is used in the analysis of data in which the outcome of interest for each participant is composed of two components: time and event. In biomedical studies, it is not often possible to wait until the event in question has happened to all the participants or losses to follow-up may occur. In such cases, the event is censored at the last follow-up time each participant was assessed for the occurrence of the event, without treating those participants' data as missing. In other words, the available incomplete information from censored observations is utilized in the analysis. The main objectives of survival analysis include estimating and interpreting survival—and/or hazard—functions from the time-to-event data, comparing survival curves, and assessing the relationship of explanatory variables to survival time or time-to-event.