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An important advantage of the Kaplan–Meier curve is that the method can take into account some types of censored data, particularly right-censoring, which occurs if a patient withdraws from a study, is lost to follow-up, or is alive without event occurrence at last follow-up. On the plot, small vertical tick-marks state individual patients ...
An early paper to use the Kaplan–Meier estimator for estimating censored costs was Quesenberry et al. (1989), [3] however this approach was found to be invalid by Lin et al. [4] unless all patients accumulated costs with a common deterministic rate function over time, they proposed an alternative estimation technique known as the Lin estimator.
Left-censored data can occur when a person's survival time becomes incomplete on the left side of the follow-up period for the person. For example, in an epidemiological example, we may monitor a patient for an infectious disorder starting from the time when he or she is tested positive for the infection.
The logrank test is based on the same assumptions as the Kaplan-Meier survival curve—namely, that censoring is unrelated to prognosis, the survival probabilities are the same for subjects recruited early and late in the study, and the events happened at the times specified. Deviations from these assumptions matter most if they are satisfied ...
Dorota Maria Dabrowska is a Polish statistician known for applying nonparametric statistics and semiparametric models to counting processes and survival analysis.Dabrowska's estimator, from her paper "Kaplan–Meier estimate on the plane" (Annals of Statistics, 1988) is a widely used tool for bivariate survival under random censoring.
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
Dr. Deborah Birx, former White House’s Coronavirus Task Force coordinator, on Sunday said that attempts to convey accurate scientific information about the pandemic were “censored.” Birx ...
The survival function is one of several ways to describe and display survival data. Another useful way to display data is a graph showing the distribution of survival times of subjects. Olkin, [5] page 426, gives the following example of survival data. The number of hours between successive failures of an air-conditioning (AC) system were recorded.