|
Abstract:
|
Interval-censored failure time data occur in many fields such as demography, economics, medical research and reliability and many inference procedures on them have been developed (Chen et al., 2012; Sun, 2006). However, most of the existing approaches assume that the mechanism that yields interval censoring is independent of the failure time of interest and it is clear that this may not be true in practice (Zhang et al., 2007). In this talk, we discuss regression analysis of interval-censored failure time data when the censoring mechanism may be related to the failure time of interest. For the problem, an estimated sieve maximum likelihood approach is proposed and the asymptotic properties of the proposed estimators of regression parameters are established. In addition, an extensive simulation study is conducted and suggests that the method works well. Finally, we apply the method to a set of real interval-censored data that motivated this study.
|
