AbstractThe nonparametric estimator of the conditional survival function proposed by Beran is a useful tool to evaluate the effects of covariates in the presence of random right censoring. However, censoring indicators of right censored data may be missing for different reasons in many applications. We propose some estimators of the conditional cumulative hazard and survival functions which allow to handle this situation. We also construct the likelihood ratio confidence bands for them and obtain their asymptotic properties. Simulation studies are used to evaluate the performances of the estimators and their confidence bands
Consider a regression model in which the responses are subject to random right censoring. In this mo...
In the literature much work has been devoted to the non-parametric estimation of survival analysis f...
AbstractAn alternative to the accelerated failure time model is to regress the median of the failure...
The nonparametric estimator of the conditional survival function proposed by Beran is a useful tool ...
Along with the analysis of time-to-event data, it is common to assume that only partial information ...
International audienceIn this paper, we consider the problem of hazard rate estimation in presence o...
The aim of paper is considering the problem of estimation of conditional survival function in the ca...
The aim of paper is considering the problem of estimation of conditional survival function in the ca...
International audienceWe consider the problem of estimation from right-censored data, when the censo...
PolyU Library Call No.: [THS] LG51 .H577P AMA 2016 Haoxx, 164 pages :color illustrationsCensored dat...
In most reliability studies involving censoring, one assumes that censoring probabilities are unknow...
One of the primary problems facing statisticians who work with survival data is the loss of informat...
Let (X, Y ) be a random vector, where Y denotes the variable of interest possibly subject to random ...
The Kaplan–Meier estimator of a survival function is well known to be asymptotically efficient when ...
In most reliability studies involving censoring, one assumes that censoring probabilities are unknow...
Consider a regression model in which the responses are subject to random right censoring. In this mo...
In the literature much work has been devoted to the non-parametric estimation of survival analysis f...
AbstractAn alternative to the accelerated failure time model is to regress the median of the failure...
The nonparametric estimator of the conditional survival function proposed by Beran is a useful tool ...
Along with the analysis of time-to-event data, it is common to assume that only partial information ...
International audienceIn this paper, we consider the problem of hazard rate estimation in presence o...
The aim of paper is considering the problem of estimation of conditional survival function in the ca...
The aim of paper is considering the problem of estimation of conditional survival function in the ca...
International audienceWe consider the problem of estimation from right-censored data, when the censo...
PolyU Library Call No.: [THS] LG51 .H577P AMA 2016 Haoxx, 164 pages :color illustrationsCensored dat...
In most reliability studies involving censoring, one assumes that censoring probabilities are unknow...
One of the primary problems facing statisticians who work with survival data is the loss of informat...
Let (X, Y ) be a random vector, where Y denotes the variable of interest possibly subject to random ...
The Kaplan–Meier estimator of a survival function is well known to be asymptotically efficient when ...
In most reliability studies involving censoring, one assumes that censoring probabilities are unknow...
Consider a regression model in which the responses are subject to random right censoring. In this mo...
In the literature much work has been devoted to the non-parametric estimation of survival analysis f...
AbstractAn alternative to the accelerated failure time model is to regress the median of the failure...