Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons and patterns. This text describes the types of censoring, their implications, and the methods used to address them.
Types of Censoring
Several statistical techniques have been developed to handle censored data in survival analysis such as Kaplan-Meier Estimator, Cox Proportional Hazards Model, and Multiple Imputation.
From Chapter 15:
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