Journal ArticleDOI
M-estimation in censored linear models
TLDR
In this article, a method of obtaining an M-estimator in a linear model when the responses are subject to right censoring is proposed, and the central limit theorem for the estimator using squared error loss, i.e. least squares, is derived using counting process martingale techniques.Abstract:
SUMMARY We propose a method of obtaining an M-estimator in a linear model when the responses are subject to right censoring. The central limit theorem for the estimator using squared error loss, i.e. least squares, is derived using counting process martingale techniques. The estimation method is applied to the Stanford heart transplant data for illustration.read more
Citations
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Journal ArticleDOI
Three-Step Censored Quantile Regression and Extramarital Affairs
Victor Chernozhukov,Han Hong +1 more
TL;DR: In this paper, the authors proposed a simple three-step estimator for censored quantile regression models with a separation restriction on the censoring probability, which is asymptotically as efficient as the celebrated Powell's censored least absolute deviation estimator.
Journal Article
Distributional Convergence under Random Censorship when Covariables are Present
TL;DR: In this article, a linear functional of the correspond- ing (p + 1)-dimensional Kaplan-Meier estimator is shown to be asymptotically normal under weak moment assumptions.
Journal ArticleDOI
A review on empirical likelihood methods for regression
TL;DR: The authors provide a review on the empirical likelihood method for regression-type inference problems, including parametric, semiparametric, and nonparametric models, and both missing data and censored data are accommodated.
Journal ArticleDOI
Variable selection in the accelerated failure time model via the bridge method.
Jian Huang,Shuangge Ma +1 more
TL;DR: This article models the relationship between gene expressions and survival using the accelerated failure time (AFT) models and uses the bridge penalization for regularized estimation and gene selection, and shows that the proposed bridge estimator is selection consistent under appropriate conditions.
Journal ArticleDOI
Nonparametric Estimation and Regression Analysis with Left-Truncated and Right-Censored Data
Shulamith T. Gross,Tze Leung Lai +1 more
TL;DR: In this paper, a nonparametric estimation of trimmed functionals of the conditional distribution of the response variable Y was proposed, with the trimming inside the observable range between τ and τ*, where τ is the lower boundary of the support of the left-truncation variable T.
References
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Book ChapterDOI
Nonparametric Estimation from Incomplete Observations
Edward L. Kaplan,Paul Meier +1 more
TL;DR: In this article, the product-limit (PL) estimator was proposed to estimate the proportion of items in the population whose lifetimes would exceed t (in the absence of such losses), without making any assumption about the form of the function P(t).
Journal ArticleDOI
Linear regression with censored data
Jonathan Buckley,Ian R. James +1 more
TL;DR: In this paper, a method of estimating parameters in the linear regression model which allows the dependent variable to be censored and the residual distribution to be unspecified is presented, which appears to overcome the inconsistency problems in Miller's approach.
Journal ArticleDOI
Regression Analysis with Randomly Right-Censored Data
TL;DR: In this paper, a new estimator of the parameter vector in a linear regression model when the observations are randomly censored on the right and when the error distribution is unknown is proposed, and sufficient conditions under which this estimator is mean square consistent and asymptotically normal.
Journal ArticleDOI
Regression with censored data
Rupert G. Miller,Jerry Halpern +1 more
TL;DR: Four regression techniques currently available for use with censored data which do not assume particular parametric families of survival distributions are described, and their performances compared on the updated Stanford heart transplant data are compared.