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In **survival analysis**, censoring occurs when the event of interest (e.g., death or failure) is not observed for all subjects in the study. *For example, suppose you are studying the survival times of patients with a certain disease*. If some patients are still alive at the end of the study, their survival times are censored. Ignoring censoring can lead to biased estimates of the survival distribution. Specialized methods, such as the Kaplan-Meier estimator and Cox proportional hazards model, are used to handle censoring and provide unbiased estimates.
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