Survival analysis (a.k.a. event history analysis, duration analysis or transition analysis) has been used to investigate things like how long people stay unemployed, how long a cancer patient lives, how long it takes before a lightbulb breaks, etc. What these examples have in common is that they all investigate how long it takes before a certain event (finding a job, dying, breaking of a lightbulb) happens. The concepts of survival analysis will be discussed with the help of a small fictitious example about how long it takes ten countries to ratify a treaty. We may think of this as countries that every year run a `risk' of ratifying that year. We would expect that the duration is short when this risk is high and long when the risk is low. That risk of ratifying may change from year to year or may be different for countries with different characteristics/explanatory variables. With survival analysis we can estimate the impact of the explanatory variables on the risk of ratifying. Three techniques will be discussed: the non-parametric (Kaplan-Meier estimates of the survival function), the parametric and the semi-parametric (Cox regression).