Results 1 to 10 of about 219,918 (211)
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.
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Interval-specific censoring set adjusted Kaplan-Meier estimator. [PDF]
J Appl Stat, 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.
Wu Y, Kolassa J.
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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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Displaying survival of patient groups defined by covariate paths: Extensions of the Kaplan-Meier estimator. [PDF]
Stat Med, 2021 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.
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Using the Kaplan–Meier Estimator to Assess the Reliability of Agricultural Machinery
Agronomy, 2022 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
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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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Improved Kaplan-Meier Estimator in Survival Analysis Based on Partially Rank-Ordered Set Samples. [PDF]
Comput Math Methods Med, 2020 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
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Factors determining disease duration in Alzheimer's disease: a postmortem study of 103 cases using the Kaplan-Meier estimator and Cox regression. [PDF]
Biomed Res Int, 2014 Factors associated with duration of dementia in a consecutive series of 103 Alzheimer's disease (AD) cases were studied using the Kaplan-Meier estimator and Cox regression analysis (proportional hazard model).
Armstrong RA.
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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.
Cai, Zongwu, Roussas, George G.
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Bootstrapping the Kaplan–Meier estimator on the whole line [PDF]
Annals of the Institute of Statistical Mathematics, 2018 This article is concerned with proving the consistency of Efron's (1981) bootstrap for the Kaplan-Meier estimator on the whole support of a survival function. While other works address the asymptotic Gaussianity of the estimator itself without restricting time (e.g.
Dennis Dobler
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