Smooth Hazard Function Estimation for Interval Censored Data with Time Varying Covariates
In this paper we propose methods for smooth hazard estimation of a time variable where that variable is interval censored. These methods allow one to model the transformed hazard in terms of either smooth (smoothing splines) or linear functions of time and other relevant time varying predictor variables. We illustrate the use of this method on a dataset of hemophiliacs where the outcome, time to seroconversion for HIV, is interval censored and left-truncated.
Quale, Christopher and Bacchetti, Peter, "Smooth Hazard Function Estimation for Interval Censored Data with Time Varying Covariates" (February 2001). U.C. Berkeley Division of Biostatistics Working Paper Series. Working Paper 90.
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