Add to ORKGWe develop a new method for covariate error correction in the Cox survival regression model, given a modest sample of internal validation data. Unlike most previous methods for this setting, our method can handle covariate error of arbitrary form. Asymptotic properties of the estimator are derived. In a simulation study, the method was found to perform very well in terms of bias reduction and confidence interval coverage. The method is applied to data from the Health Professionals Follow-Up Study (HPFS) on the effect of diet on incidence of Type II diabetes.R01 AG056764/AG/NIA NIH HHS/United StatesR21 AG058198/AG/NIA NIH HHS/United StatesT42 OH008416/OH/NIOSH CDC HHS/United StatesU01 CA209414/CA/NCI NIH HHS/United States2019-08-23T00:00:00Z...
There have been proposed so far many methods of statistical diagnostics in Cox regression for checki...
For instance nutritional data are often subject to severe measurement error, and an adequate adjust...
[[abstract]]Covariate measurement error problems have been extensively studied in the context of rig...
We develop a new method for covariate error correction in the Cox survival regression model, given a...
We propose a new method for fitting proportional hazards models with error-prone covariates. Regress...
Measurement error in the covariate of main interest (e.g. the exposure variable, or the risk factor)...
ABSTRACT. We propose a new method for fitting proportional hazards models with error-prone covariate...
The Cox (1972) regression model was a major advancement in the analysis of survival data because it ...
In large cohort studies, it often happens that some covariates are expensive to measure and hence on...
This paper investigates diagnostic measures for assessing the influence of observations and model mi...
This paper studies Cox`s proportional hazards model under covariate measurement error. Nakamura`s (1...
Prentice (1982) proposed a regression calibration estimator in Cox regression when covariate variabl...
We consider Cox proportional hazards regression when the covariate vector includes error-prone discr...
Many survival studies have error-contaminated covariates, which may lack a gold standard of measurem...
In survival analysis, time-dependent covariates are usually present as longitudinal data collected p...
There have been proposed so far many methods of statistical diagnostics in Cox regression for checki...
For instance nutritional data are often subject to severe measurement error, and an adequate adjust...
[[abstract]]Covariate measurement error problems have been extensively studied in the context of rig...
We develop a new method for covariate error correction in the Cox survival regression model, given a...
We propose a new method for fitting proportional hazards models with error-prone covariates. Regress...
Measurement error in the covariate of main interest (e.g. the exposure variable, or the risk factor)...
ABSTRACT. We propose a new method for fitting proportional hazards models with error-prone covariate...
The Cox (1972) regression model was a major advancement in the analysis of survival data because it ...
In large cohort studies, it often happens that some covariates are expensive to measure and hence on...
This paper investigates diagnostic measures for assessing the influence of observations and model mi...
This paper studies Cox`s proportional hazards model under covariate measurement error. Nakamura`s (1...
Prentice (1982) proposed a regression calibration estimator in Cox regression when covariate variabl...
We consider Cox proportional hazards regression when the covariate vector includes error-prone discr...
Many survival studies have error-contaminated covariates, which may lack a gold standard of measurem...
In survival analysis, time-dependent covariates are usually present as longitudinal data collected p...
There have been proposed so far many methods of statistical diagnostics in Cox regression for checki...
For instance nutritional data are often subject to severe measurement error, and an adequate adjust...
[[abstract]]Covariate measurement error problems have been extensively studied in the context of rig...