A Novel Model for Competing Risks Data with Masking

Suny At Binghamton, Binghamton NY

Investigators

Abstract

A masked competing risks (MCR) model is a popular model for studying the lifetime (denoted by T) and the associated failure cause (denoted by C) of a J-component series system. The system fails if one of its components fails. The failure time might be censored and the failure cause might be masked. The investigator discovered that some of the assumptions used in the MCR modelare erroneous. In this project, the investigator proposes a new and a more realistic model, which is a significant improvement of the MCR model. Based on the new model, the PI proposes to study the parametric, non-parametric and semi-parametric estimation problems of the joint distribution of T and C. The MCR data appear in numerous medical and industrial applications. For example, Dinse (1982) presents the MCR data of time until progression and the patient status at the time of progression for patients with glioblastoma (a cancer of the brain). The patient status may not be identified. Reiser et al.(1995) show that the MCR data arises from the testing of a particular type of IBM PS/2 computer. The cause of failure of a computer may only be narrowed down to a set of possible causes. The estimation of the joint distribution of T and C has a great impact in detecting the failure cause efficiently. The results of this research would provide a novel and realistic model for the MCR data and would provide statistical tools for analyzing the MCR data.