Results 291 to 300 of about 298,780 (335)

Median Regression with Censored Cost Data

Biometrics, 2002
Because 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, 2013
AbstractSummaryIn 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, 1997
In 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, Clarkson, Douglas B.   +1 more
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Multivariate Survival Data With Censoring

2008
We 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, 1999
Spatial 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, 2003
Summary: 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, Molefe, Daniel, Ying, Zhiliang   +2 more
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25 Censored data

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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A Censored Data Histogram

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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Analysis of Censored Data

2018
Censored data occur when the value of an observation is only partially known. For example, it may be known that someone’s exact wealth is unknown but it may be known that their wealth exceeds one million dollars. In left censoring, the data may fall below a certain value whereas in right censoring, it may be above a certain value.
Mayer Alvo, Philip L. H. Yu
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An overview of real‐world data sources for oncology and considerations for research

Ca-A Cancer Journal for Clinicians, 2022
Lynne Penberthy, Donna R Rivera, Jennifer L Lund, Msph   +2 more
exaly