The Kaplan-Meier estimator estimates the distribution function of a lifetime T based on a sample of randomly right censored observations. In survival analysis the lifetime Tis a nonnegative random variable describing the time until a certain event of interest happens. In medical applications examples of such events are the time till death of a patient suffering from a specific disease, the time till recovery of a disease after the start of the treatment, or the time till remission after the curing of a patient. A typical difficulty in survival analysis is that the observations might be incomplete. For example, when studying the time till death of a patient with a specific disease, the patient might die from another cause. As a consequence the lifetime of this patient is not observed, and is only known to be larger than the time till the patient was “censored” by the other cause of death. Such a type of censoring mechanism is called right random censorship. Other areas of applications...
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Gijbels, I. (2011). Kaplan-Meier Estimator. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_322
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