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The Kaplan–Meier estimator, [1] [2] also known as the product limit estimator, is a non-parametric statistic used to estimate the survival function from lifetime data. In medical research, it is often used to measure the fraction of patients living for a certain amount of time after treatment.
Paul Meier (July 24, 1924 – August 7, 2011) [1] was a statistician who promoted the use of randomized trials in medicine. [2] [3]Meier is known for introducing, with Edward L. Kaplan, the Kaplan–Meier estimator, [4] [5] a method for measuring how many patients survive a medical treatment from one duration to another, taking into account that the sampled population changes over time.
Edward Lynn Kaplan (May 11, 1920 – September 26, 2006) [1] was a mathematician most famous for the Kaplan–Meier estimator, [2] developed together with Paul Meier. Biography [ edit ]
The problem with measuring overall survival by using the Kaplan-Meier or actuarial survival methods is that the estimates include two causes of death: deaths from the disease of interest and deaths from all other causes, which includes old age, other cancers, trauma and any other possible cause of death. In general, survival analysis is ...
Kaplan–Meier estimator [ edit ] The Dvoretzky–Kiefer–Wolfowitz inequality is obtained for the Kaplan–Meier estimator which is a right-censored data analog of the empirical distribution function
Pages in category "Estimator" The following 27 pages are in this category, out of 27 total. ... Kaplan–Meier estimator; L. L-estimator; M. M-estimator; Maximum ...
Kaplan–Meier estimator; Meijer G-function This page was last edited on 29 December 2019, at 10:22 (UTC). Text is available under the Creative Commons ...
Isambard Kingdom has proposed deletion of the section "Example calculation of Kaplan-Meier estimate" because it is long (and possibly tedious). I beleive that an example calculation is necessary for a comprehensive description of the Kaplan-Meier estimate.