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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.
Isotonic regression has applications in statistical inference.For example, one might use it to fit an isotonic curve to the means of some set of experimental results when an increase in those means according to some particular ordering is expected.
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 ]
In full generality, the accelerated failure time model can be specified as [2] (|) = ()where denotes the joint effect of covariates, typically = ([+ +]). (Specifying the regression coefficients with a negative sign implies that high values of the covariates increase the survival time, but this is merely a sign convention; without a negative sign, they increase the hazard.)
This entry needs more examples, possibly a sample calculation, and a review of the citation history of the original article. I can do it eventually but if anyone else is game, feel free...this is an important entry, so I think a little tutorial on how to do a KM estimation is in order. 63.250.186.17 16:27, 16 November 2005 (UTC)Theoriste
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In all cases, the estimation target is a function of the independent variables called the regression function. In regression analysis, it is also of interest to characterize the variation of the dependent variable around the regression function which can be described by a probability distribution .