Kaplan-meier estimate - Open Access .click

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2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM), 2020
The Kaplan-Meier estimator (KME) is a classical non-parametric reliability estimator for incomplete data; and it underestimates the reliability. Few estimators have been developed to correct its bias. This paper aims to fill this gap by proposing a bias-corrected estimator.
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Efficiency Loss with the Kaplan-Meier Estimator.

1985
Abstract : We consider the proportional hazards model where the distribution G of the censoring random variable is related to the distribution F of the lifetime random variable via (1 - G)=(1 - F) to the beta power. Nonparametric estimators of F are developed for the case where beta is unknown and the case where beta is known.
James Sconing, Frank Proschan, Myles Hollander +2 more
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-deficiency of the Kaplan–Meier estimator

Statistics & Probability Letters, 2003
Mohamed Lemdani, Elias Ould-Saı̈d
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Kaplan–Meier Estimator

2003
Hongyu Jiang, Jason Fine
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Kaplan–Meier Statistics to Estimate Treatment Success

Journal of Neuro-Ophthalmology, 2022
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Competing risk bias was common in Kaplan–Meier risk estimates published in prominent medical journals

Journal of Clinical Epidemiology, 2016
Finlay A McAlister
exaly

The jackknife estimate of variance of a Kaplan-Meier integral

Annals of Statistics, 1996
Winfried Stute
exaly

Competing risk bias in Kaplan–Meier risk estimates can be corrected

Journal of Clinical Epidemiology, 2016
Steven Hawken
exaly