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Estimating Transition Intensity Rate on Interval-censored Data Using Semi-parametric with EM Algorithm Approach. [PDF]
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Biometrika, 1982
SUMMARY There are four regression techniques currently available for use with censored data which do not assume particular parametric families of survival distributions. They are due to (i) Cox (1972), (ii) Miller (1976), (iii) Buckley & James (1979), and (iv) Koul, Susarla & Van Ryzin (1981).
Miller, Rupert, Halpern, Jerry
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SUMMARY There are four regression techniques currently available for use with censored data which do not assume particular parametric families of survival distributions. They are due to (i) Cox (1972), (ii) Miller (1976), (iii) Buckley & James (1979), and (iv) Koul, Susarla & Van Ryzin (1981).
Miller, Rupert, Halpern, Jerry
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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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Quantile Autoregression for Censored Data
Journal of Time Series Analysis, 2016Quantile autoregression (QAR) is particularly attractive for censored data. However, unlike the standard regression models, the autoregressive models must take account of censoring on both response and regressors. In this article, we show that the existing censored quantile regression methods produce consistent estimators for QAR models when using only
Choi, Seokwoo Jake, Portnoy, Stephen
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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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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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Laplace regression with censored data
Biometrical Journal, 2010AbstractWe consider a regression model where the error term is assumed to follow a type of asymmetric Laplace distribution. We explore its use in the estimation of conditional quantiles of a continuous outcome variable given a set of covariates in the presence of random censoring. Censoring may depend on covariates.
Bottai, Matteo, Zhang, Jiajia
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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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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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