Accelerated Failure Time Models with Auxiliary Covariates

Failure time regression with continuous informative auxiliary covariates

In this paper we use Cox's regression model to fit failure time data with continuous informative auxiliary variables in the presence of a validation subsample. We first estimate the induced relative risk function by kernel smoothing based on the validation subsample, and then improve the estimation by utilizing the information on the incomplete observations from non-validation subsample and the...

Analysis of Failure Time Data with Missing and Informative Auxiliary Covariates

Marginal hazard regression for correlated failure time data with auxiliary covariates.

In many biomedical studies, it is common that due to budget constraints, the primary covariate is only collected in a randomly selected subset from the full study cohort. Often, there is an inexpensive auxiliary covariate for the primary exposure variable that is readily available for all the cohort subjects. Valid statistical methods that make use of the auxiliary information to improve study ...

Buckley-James Estimator of AFT Models with Auxiliary Covariates

In this paper we study the Buckley-James estimator of accelerated failure time models with auxiliary covariates. Instead of postulating distributional assumptions on the auxiliary covariates, we use a local polynomial approximation method to accommodate them into the Buckley-James estimating equations. The regression parameters are obtained iteratively by minimizing a consecutive distance of th...

Space-time models with time-dependent covariates