Censoring

Summary

Censoring is the situation in which the value of a measurement is only partly known. One learns that it lies in some interval, but not its exact value. The most common case is right censoring of event times, where one only knows that the event had not happened by the end of follow-up. Ignoring censored observations, or treating them as exact, biases the estimates. Methods of survival analysis, such as the Kaplan–Meier estimator, are built to use censored data correctly.