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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. In other fields, Kaplan–Meier estimators may be ...
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. He attended the Carnegie Institute of Technology from 1937 to 1941 and graduated with a bachelor's ...
The curve represents the odds of an endpoint having occurred at each point in time (the hazard). The hazard ratio is simply the relationship between the instantaneous hazards in the two groups and represents, in a single number, the magnitude of distance between the Kaplan–Meier plots. [7] Hazard ratios do not reflect a time unit of the study.
Retrieved from "https://en.wikipedia.org/w/index.php?title=Kaplan-Meier_curve&oldid=301564058"
S(t) is theoretically a smooth curve, but it is usually estimated using the Kaplan–Meier (KM) curve. The graph shows the KM plot for the aml data and can be interpreted as follows: The x axis is time, from zero (when observation began) to the last observed time point. The y axis is the proportion of subjects surviving. At time zero, 100% of ...
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.
Retrieved from "https://en.wikipedia.org/w/index.php?title=Kaplan-Meier&oldid=301563849"This page was last edited on 11 July 2009, at 17:10 (UTC). (UTC).
The Dvoretzky–Kiefer–Wolfowitz inequality is one method for generating CDF-based confidence bounds and producing a confidence band, which is sometimes called the Kolmogorov–Smirnov confidence band. The purpose of this confidence interval is to contain the entire CDF at the specified confidence level, while alternative approaches attempt ...