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1987
The censored normal regression model considered by Tobin (1958), also commonly known as the ‘tobit’ model, is the following: $$y_i^* = \beta {x_i} + {u_i}.\quad {u_i} \sim IN(0,{\sigma ^2})$$ The observed y i are related to y i * according to the relationship $$\eqalign{ & {y_i} = y_i^*\quad if\,y_i^* > {y_0} \cr & = {y_0}\quad \;\quad ...
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The censored normal regression model considered by Tobin (1958), also commonly known as the ‘tobit’ model, is the following: $$y_i^* = \beta {x_i} + {u_i}.\quad {u_i} \sim IN(0,{\sigma ^2})$$ The observed y i are related to y i * according to the relationship $$\eqalign{ & {y_i} = y_i^*\quad if\,y_i^* > {y_0} \cr & = {y_0}\quad \;\quad ...
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Renovated Scatterplots for Censored Data
Biometrika, 1995Summary: In simple linear regression where the response variable has been subject to right-censoring, censored points in the scatterplot of observed data are moved vertically to create a renovated scatterplot where the bias of censoring is removed. The relationship to least squares estimation and the effect on regression diagnostics are examined in the
Smith, Peter J., Zhang, J.
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WIREs Computational Statistics, 2010
AbstractThe analysis of censored data is a major issue in survival studies. Censored data are together with truncated data, missing data, current status data, and others, among the complex data structures in which only partial information on the variable(s) of interest is available.
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AbstractThe analysis of censored data is a major issue in survival studies. Censored data are together with truncated data, missing data, current status data, and others, among the complex data structures in which only partial information on the variable(s) of interest is available.
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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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Linear Regression with Censored Data
Biometrika, 1979SUMMARY We give 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. The method differs from that of Miller (1976) in that the normal equations rather than the sum of squares of residuals are modified and this appears to overcome the ...
Buckley, Jonathan, James, Ian
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Evaluation of censored contamination data†
Food Additives and Contaminants, 1995Laboratory measures of low-level contamination are typically strongly skewed, and observations below a specified detection limit are recorded merely as not detectable or less than a specified limit. In these circumstances, a full description of the distribution requires assumptions about the form of the lower tail.
I G, Vlachonikolis, F H, Marriott
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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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