Results 211 to 220 of about 144,202 (264)
A New Approach to Modeling the Cure Rate in the Presence of Interval Censored Data. [PDF]
Comput StatPal S, Peng Y, Aselisewine W.
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Bayesian and non-bayesian inference for logistic-exponential distribution using improved adaptive type-II progressively censored data. [PDF]
PLoS OneDutta S, Alqifari HN, Almohaimeed A.
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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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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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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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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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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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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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