The GMLE With Interval-Censored And Masked Competing Risks Data.
Abstract
We consider the estimation problem of the joint cumulative distribution
function (cdf) of the failure time T and the failure cause C of a
J-component series system. The study is motivated by a cancer research
data with interval-censored (IC) T and masked C. This type of data is
called the
interval-censored and masked competing risks (ICMCR) data. We
propose a model for such data and propose to estimate the cdf by
the generalized maximum likelihood estimator(GMLE). In general, there is
no explicit solution for the GMLE based on the ICMCR data.
We discuss the algorithm for the GMLE. We show that with the continuous
right-censored and masked competing risks data the standard GMLE is
inconsistent. However, our simulation results suggest that with ICMCR data
the GMLE is consistent. Moreover, we study the empirical convergent rates
of the GMLE through simulation.
