Results 241 to 250 of about 291,396 (287)
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2003
Let {X(t): t ∈ ℝ≥0} be a multivariate stochastic process indexed by time t. Let T denote an endpoint of this stochastic process, and define X(t) ≡ X(min(t, T)). Let R(t) = I(T≤ t) be one of the components of X(t). We define the full data as \(X = \bar{X}(T) = (X(s):s \leqslant T)\), where T is thus a function X.
Mark J. van der Laan, James M. Robins
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Let {X(t): t ∈ ℝ≥0} be a multivariate stochastic process indexed by time t. Let T denote an endpoint of this stochastic process, and define X(t) ≡ X(min(t, T)). Let R(t) = I(T≤ t) be one of the components of X(t). We define the full data as \(X = \bar{X}(T) = (X(s):s \leqslant T)\), where T is thus a function X.
Mark J. van der Laan, James M. Robins
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Regression with Interval-Censored Data
Biometrika, 1995Summary: Interval-censored data result when survival times are not known exactly, but are only known to have occurred between intermittent examination times. Here the accelerated failure time model is treated for interval- censored data. A class of score statistics that may be used for estimation and confidence procedures is proposed.
Rabinowitz, Daniel +2 more
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Median Regression with Censored Cost Data
Biometrics, 2002Because of the skewness of the distribution of medical costs, we consider modeling the median as well as other quantiles when establishing regression relationships to covariates. In many applications, the medical cost data are also right censored. In this article, we propose semiparametric procedures for estimating the parameters in median regression ...
Bang, Heejung, Tsiatis, Anastasios A.
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Bayesian Quantile Regression for Censored Data
Biometrics, 2013AbstractSummaryIn this paper we propose a semiparametric quantile regression model for censored survival data. Quantile regression permits covariates to affect survival differently at different stages in the follow‐up period, thus providing a comprehensive study of the survival distribution.
Reich, Brian J., Smith, Luke B.
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Hazard Regression with Interval-Censored Data
Biometrics, 1997In a recent paper, Kooperberg, Stone, and Truong (1995a) introduced hazard regression (HARE), in which linear splines and their tensor products are used to estimate the conditional log-hazard function based on possibly censored, positive response data and one or more covariates.
Kooperberg, Charles +1 more
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Multivariate Survival Data With Censoring
2008We define a new class of models for multivariate survival data, in continuous time, based on a number of cumulative hazard functions, along the lines of our family of models for correlated survival data in discrete time [Gross and Huber-Carol (2000, 2002)]. This family is an alternative to frailty and copula models.
Huber, Catherine, Gross, Shulamith
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Analyzing Censored Spatial Data
Mathematical Geology, 1999Spatial data that are incomplete because of observations arising below or above a detection limit occur in many settings, for example, in mining, hydrology, and pollution monitoring. These observations are referred to as censored observations. For example, in a life test, censoring may occur at random times because of accident or breakdown of equipment.
Ana F. Militino, M. Dolores Ugarte
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Identifiability and censored data
Biometrika, 2003Summary: It is well known that, without the assumption of independence between two nonnegative random variables \(X\) and \(Y\), the survival function of \(X\) is not identifiable on the basis of the joint distribution function of \(Z = \min(X, Y)\) and \(\delta = I(Z = Y)\).
Ebrahimi, Nader +2 more
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1984
Publisher Summary This chapter presents a survey of nonparametric methods for censored data. The literature in this field is quite extensive. It presents a survey of some recent developments in the area. The chapter defines Type I, Type II, arbitrarily censored and randomly censored data.
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Publisher Summary This chapter presents a survey of nonparametric methods for censored data. The literature in this field is quite extensive. It presents a survey of some recent developments in the area. The chapter defines Type I, Type II, arbitrarily censored and randomly censored data.
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Communications in Statistics - Simulation and Computation, 2005
ABSTRACT A histogram is an important tool for exploratory data analysis. No matter what the ultimate analysis of a given set of data, it is always important to plot the data. However, when data are censored, this becomes problematic. This article presents a method for constructing a histogram for censored data using the Kaplan–Meier survivor function ...
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ABSTRACT A histogram is an important tool for exploratory data analysis. No matter what the ultimate analysis of a given set of data, it is always important to plot the data. However, when data are censored, this becomes problematic. This article presents a method for constructing a histogram for censored data using the Kaplan–Meier survivor function ...
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