Right censoring
Right censoring occurs in statistical studies, especially in survival analysis, when we do not have complete information about an event happening by a certain time. For example, if a researcher is studying how long patients live after treatment and a patient leaves the study or is still alive when the study ends, we only know that their survival time is at least the duration of the study. Thus, we can't fully measure their survival time, leading to "censored" data. This situation is common and must be accounted for to ensure accurate analysis of the overall data.
Additional Insights
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Right censoring occurs in research, particularly in studies involving time until an event (like failure or death), when we only know that an event has not happened by a certain point in time. For example, if a study tracks patients until they die, but some patients are still alive when the study ends, we only know that their survival time is longer than their last follow-up. This means the exact time of the event is unknown but is bounded by what is observed, making it "censored" on the right side of the time scale.