AUTHOR:  McKeague, I. W. and Subramanian, S.
DATE: 1996
TITLE: Product-Limit Estimators and Cox Regression  
with Missing Cause-of-Failure Information

ABSTRACT:
The Kaplan--Meier estimator of a survival function is used when cause 
of failure (censored or non-censored) is always observed. A method of 
survival function estimation is developed under the assumption that 
the failure indicators are missing completely at random (MCR). The resulting 
estimator is a smooth functional of the Nelson--Aalen estimators of 
certain cumulative transition intensities. The asymptotic properties 
of this estimator are derived.  A simulation study shows 
that the proposed estimator has greater
efficiency than competing MCR-based estimators.  The approach is extended 
to the Cox model setting for the estimation of a conditional
survival function given a covariate.