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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.
Epi Info has been in development for over 20 years. The first version, Epi Info 1, was originally developed by Jeff Dean while he was in high school. [3] [4] It was an MS-DOS batch file on 5.25" floppy disks and released in 1985. [5]
Kaplan–Meier curves and log-rank tests are most useful when the predictor variable is categorical (e.g., drug vs. placebo), or takes a small number of values (e.g., drug doses 0, 20, 50, and 100 mg/day) that can be treated as categorical.
Retrieved from "https://en.wikipedia.org/w/index.php?title=Kaplan-Meier_curve&oldid=301564058"
It can be thought of as the kaplan-meier survivor function for a particular year, divided by the expected survival rate in that particular year. That is typically known as the relative survival (RS). If five consecutive years are multiplied, the resulting figure would be known as cumulative relative survival (CRS). It is analogous to the five ...
Edward Lynn Kaplan was born in Philadelphia, Pennsylvania, on May 11, 1920. [3] His parents were Eugene V. Kaplan (1887–1977) and Frances Rhodes Kaplan (1891–1978). He graduated from Swissvale High School in Swissvale, Pennsylvania, in 1937.
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