Multiple imputation of a randomly censored covariate improves logistic regression analysis

Linear Regression with a Randomly Censored Covariate: Application to an Alzheimer's Study.

The association between maternal age of onset of dementia and amyloid deposition (measured by in vivo positron emission tomography (PET) imaging) in cognitively normal older offspring is of interest. In a regression model for amyloid, special methods are required due to the random right censoring of the covariate of maternal age of onset of dementia. Prior literature has proposed methods to add...

Linear regression for bivariate censored data via multiple imputation.

Bivariate survival data arise, for example, in twin studies and studies of both eyes or ears of the same individual. Often it is of interest to regress the survival times on a set of predictors. In this paper we extend Wei and Tanner's multiple imputation approach for linear regression with univariate censored data to bivariate censored data. We formulate a class of censored bivariate linear re...

Multiple Imputation for M-Regression With Censored Covariates

Censored Quantile Regression with Covariate Measurement Errors

Censored quantile regression has become an important alternative to the Cox proportional hazards model in survival analysis. In contrast to the central covariate effect from the meanbased hazard regression, quantile regression can effectively characterize the covariate effects at different quantiles of the survival time. When covariates are measured with errors, it is known that naively treatin...

A multiple imputation approach to regression analysis for doubly censored data with application to AIDS studies.

Sun, Liao, and Pagano (1999) proposed an interesting estimating equation approach to Cox regression with doubly censored data. Here we point out that a modification of their proposal leads to a multiple imputation approach, where the double censoring is reduced to single censoring by imputing for the censored initiating times. For each imputed data set one can take advantage of many existing te...