Censoring in time-series data occurs when some event causes subjects to cease producing data for reasons beyond the control of the investigator, or for reasons external to the issue being studied. For example, patients in a study may drop out when they move away from the clinic that has been collecting their data. Or a study of time to engine failure may end while some engines have not yet failed.
