Cox regression is used when the outcome is time-to-event. Accordingly, the outcome can be said to consist of two components of information: whether an event has occurred or not, and the time at risk (i.e. the time up until the event has occurred). The event itself can be of any sort, such as death, hospitalization, job loss, or childbirth.

Example ● Time from birth to death ● Time from marriage to divorce ● Time from cancer diagnosis to death from cancer ● Time from admission to hospital to discharge from hospital ● Time from start of the game to the first goal

Cox regression analysis is a type of survival analysis. This term makes it sound like it is all about life and death – but survival analysis can actually be applied to any type of time-to-event data. It should also be mentioned that survival analysis goes by different names depending on discipline and research field (life table analysis, hazard analysis, duration analysis, transition analysis, event history analysis, etc). We personally prefer the term time-to-event analysis.