Results 11 to 20 of about 18,301 (299)
Hidden Imputations and the Kaplan-Meier Estimator. [PDF]
Am J Epidemiol, 2020 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 +6 more sources
Kaplan–Meier Estimator under Association
Journal of Multivariate Analysis, 1998 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
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A Privacy-Preserving Log-Rank Test for the Kaplan-Meier Estimator With Secure Multiparty Computation: Algorithm Development and Validation [PDF]
JMIR Medical Informatics, 2021 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
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A Generalized Kaplan-Meier Estimator
Annals of Statistics, 1984 A class of nonparametric maximum likelihood estimators of the survival function based on incomplete or right-censored data is derived in the general situation that the time to death and the time to loss (censoring) are not necessarily independent. This is the competing risks problem with two causes of failure.
V R R Uppuluri
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Private and Collaborative Kaplan-Meier Estimators
Proceedings of the 23rd Workshop on Privacy in the Electronic Society, 2023 Kaplan-Meier estimators are essential tools in survival analysis, capturing the survival behavior of a cohort. Their accuracy improves with large, diverse datasets, encouraging data holders to collaborate for more precise estimations. However, these datasets often contain sensitive individual information, necessitating stringent data protection ...
Shadi Rahimian +3 more
openaire +3 more sources
A Combinatoric Approach to the Kaplan-Meier Estimator
Annals of Statistics, 1985 The paper considers the Kaplan-Meier estimator \(F_ n^{KM}\) from a combinatoric viewpoint. Under the assumption that the estimated distribution F and the censoring distribution G are continuous, the combinatoric results are used to show that \(\int | \theta (z)| dF_ n^{KM}(z)\) has expectation not larger than \(\int | \theta (z)| dF(z)\) for any ...
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ESTIMACIÓN DE KAPLAN MEIER BOOTSTRAP DE LA CURVA DE SUPERVIVENCIA
Pesquimat, 2014 In this work the function of survival is estimated by means of the non-parametric method known like the Kaplan Meier Bootstrap estimator, under the assumption of asymptotical normality.
Freddy Tineo Guevara +2 more
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A Note on the Uniform Consistency of the Kaplan-Meier Estimator
Annals of Statistics, 1987 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 \((\tilde X_ i=X_ i\wedge U_ i\), \(\delta_ i=1_{(X_ i\leq U_ i)}\), \(1\leq i\leq n)\).
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Interval-specific censoring set adjusted Kaplan–Meier estimator [PDF]
Journal of Applied StatisticsYaoshi Wu
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Conditional Kaplan–Meier Estimator with Functional Covariates for Time-to-Event Data
Stats, 2022 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
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