Survival analysis is central in medical statistics. Not only because survival is an important medical concern, but also because survival analysis can be used to analyse data of non-fatal outcomes that are otherwise not analysable. Some examples of such non-fatal outcomes include time to tumor recurrence and age at achievement of developmental milestones.

This lecture will begin with an introduction to some of the basic concepts and examples of survival analysis. Two popular survival analysis techniques are then introduced: Kaplain-Meier analysis and Cox regression. The former is often seen as a basic technique, whereas the latter is relatively advanced. In cancer clinical trials these two techniques are almost the standard techniques. Finally we will analyse a real data set. We will provide a hyperlink to a resource of data sets and we encourage readers to practise on real data.