Hidden Imputations and the Kaplan-Meier Estimator. [PDF]
AbstractThe Kaplan-Meier (KM) estimator of the survival function imputes event times for right-censored and left-truncated observations, but these imputations are hidden and therefore sometimes unrecognized by applied health scientists. Using a simple example data set and the redistribution algorithm, we illustrate how imputations are made by the KM ...
Cole SR, Edwards JK, Naimi AI, Muñoz A.
europepmc +5 more sources
Interval-specific censoring set adjusted Kaplan–Meier estimator [PDF]
We propose a non-parametric approach to reduce the overestimation of the Kaplan-Meier (KM) estimator when the event and censoring times are independent.
exaly +3 more sources
A Privacy-Preserving Log-Rank Test for the Kaplan-Meier Estimator With Secure Multiparty Computation: Algorithm Development and Validation [PDF]
BackgroundPatient data is considered particularly sensitive personal data. Privacy regulations strictly govern the use of patient data and restrict their exchange. However, medical research can benefit from multicentric studies in which patient data from
von Maltitz, Marcel +6 more
doaj +3 more sources
Kaplan–Meier Estimator under Association
This work studies the Kaplan-Meier estimator and the estimation of the hazard function in a model with censored failure times. The true survival times \(T_1,\dots T_n\), with common marginal \(F\), are not assumed mutually independent. They satisfy two different notions of weak dependence: a) They are positively associated, i.e.
Zongwu Cai, George G Roussas
exaly +4 more sources
Displaying survival of patient groups defined by covariate paths: Extensions of the Kaplan-Meier estimator. [PDF]
Extensions of the Kaplan‐Meier estimator have been developed to illustrate the relationship between a time‐varying covariate of interest and survival.
Jay M, Betensky RA.
europepmc +2 more sources
A Note on the Uniform Consistency of the Kaplan-Meier Estimator
Let \(\{X_ n\), \(n\geq 1\}\) be i.i.d. with \(P(X_ i\leq u)=F(u)\) and \(\{U_ n\), \(n\geq 1\}\) be i.i.d. with \(P(U_ i\leq u)=G(u)\). \(\hat F_ n(t)\) is the Kaplan-Meier estimator based on the censored data \((\tilde X_ i=X_ i\wedge U_ i\), \(\delta_ i=1_{(X_ i\leq U_ i)}\), \(1\leq i\leq n)\).
Jia-gang Wang
exaly +4 more sources
Using the Kaplan–Meier Estimator to Assess the Reliability of Agricultural Machinery
Kaplan–Meier analyses can be used in many disciplines, e.g., agricultural engineering. Agricultural machinery and vehicles can be regarded as objects that ‘die’ because, like living creatures, they failed, although after repair they can be used until ...
Karol Durczak +5 more
doaj +2 more sources
Conditional Kaplan–Meier Estimator with Functional Covariates for Time-to-Event Data
Due to the wide availability of functional data from multiple disciplines, the studies of functional data analysis have become popular in the recent literature. However, the related development in censored survival data has been relatively sparse.
Sudaraka Tholkage +2 more
doaj +2 more sources
Improved Kaplan-Meier Estimator in Survival Analysis Based on Partially Rank-Ordered Set Samples. [PDF]
This study presents a novel methodology to investigate the nonparametric estimation of a survival probability under random censoring time using the ranked observations from a Partially Rank-Ordered Set (PROS) sampling design and employs it in a ...
Nematolahi S +4 more
europepmc +2 more sources
In this paper, we consider the estimators of distribution function and hazard rate for censored survival time. First, some properties and inequalities are established for linearly extended negative quadrant-dependent sequence as auxiliary results.
Yongming Li +3 more
doaj +2 more sources

