Censoring refers to the incomplete observation of an individual's time until an event occurs, often due to loss to follow-up or the study ending before the event takes place. This is important in survival analysis, as it affects how data is interpreted and analyzed, particularly when estimating survival functions, comparing groups, and modeling hazard rates. Properly handling censoring is crucial for obtaining unbiased estimates and drawing valid conclusions from statistical analyses.
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