Censoring refers to the incomplete observation of data in survival analysis, where the exact time until an event of interest, like failure or death, is not fully known for all subjects. This often occurs when individuals drop out of a study, are lost to follow-up, or have not yet experienced the event by the end of the observation period. Understanding censoring is crucial because it can significantly affect the estimation of survival functions and the assessment of risk factors in statistical models.
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