Results 251 to 260 of about 237,530 (303)

About an adaptively weighted Kaplan-Meier estimate

Lifetime Data Analysis, 2009
The minimum averaged mean squared error nonparametric adaptive weights use data from m possibly different populations to infer about one population of interest. The definition of these weights is based on the properties of the empirical distribution function.
Jean-Francois Plante
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Expert Kaplan–Meier estimation [PDF]

Scandinavian Actuarial Journal, 2023
The setting of a right-censored random sample subject to contamination is considered. In various fields, expert information is often available and used to overcome the contamination. This paper integrates expert knowledge into the product-limit estimator in two different ways with distinct interpretations.
Martin Bladt, Christian Furrer
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Bootstrapping the Kaplan-Meier Estimator

Journal of the American Statistical Association, 1986
Abstract Randomly censored data consist of iid pairs of observations (Xi, δi), i = 1, …, n; if δ i = 0, Xi denotes a censored observation, and if δ i = 1, Xi denotes an exact “survival” time, which is the variable of interest. For estimating the distribution F of the survival times, the product-limit estimator proposed by Kaplan and Meier (1958) has ...
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Interval-specific censoring set adjusted Kaplan–Meier estimator

Journal of Applied Statistics, 2023
We propose a non-parametric approach to reduce the overestimation of the Kaplan-Meier (KM) estimator when the event and censoring times are independent. We adjust the KM estimator based on the interval-specific censoring set, a collection of intervals where censored data are observed between two adjacent event times.
Yaoshi, Wu, John, Kolassa
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Two bias‐corrected Kaplan‐Meier estimators

Quality and Reliability Engineering International, 2021
AbstractThe Kaplan‐Meier estimator (KME) is a classical nonparametric reliability estimator for incomplete data. Although it has been widely used, its two drawbacks have not been addressed well in the literature: (a) as a staircase function, it actually has two reliability estimates for each failure observation, and (b) it is biased. This paper aims to
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Kaplan–Meier representation of competing risk estimates

Statistics & Probability Letters, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Satten, Glen A., Datta, Somnath
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The Jackknife Estimate of a Kaplan-Meier Integral

Biometrika, 1994
Summary: We derive an explicit formula for the jackknife estimate of a Kaplan- Meier integral. From this the asymptotic analysis of the jackknifed Kaplan-Meier process becomes straightforward. In a small simulation study it is demonstrated that jackknifing may lead to a considerable reduction of the bias.
Stute, Winfried, Wang, Jane-Ling
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Revisit Kaplan–Meier Estimator in Estimating QAL Survival Distributions

Journal of Statistical Theory and Practice, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wang, J., Li, Y.
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