Inference for the dependent competing risks model with masked causes of failure.
The competing risks model is useful in settings in which individuals/units may die/fail for different reasons. The cause specific hazard rates are taken to be piecewise constant functions. A complication arises when some of the failures are masked within a group of possible causes. Traditionally, statistical inference is performed under the assumption that the failure causes act independently on each item. In this paper we propose an EM-based approach which allows for dependent competing risks and produces estimators for the sub-distribution functions. We also discuss identifiability of parameters if none of the masked items have their cause of failure clarified in a second stage analysis (e.g. autopsy). The procedures proposed are illustrated with two datasets.
Department of Statistics, University of Toronto, 100 St. George Street, Toronto, Ontario, M5S 3G3, Canada. craiu@utstat.toronto.edu
Radu V
RV
Craiu
Benjamin
B
Reiser
D000465:Algorithms; D000818:Animals; D002273:Carcinogens / Q000633:toxicity; D003201:Computers; D015233:Models, Statistical; D009602:Nitrosamines / Q000633:toxicity; D018570:Risk Assessment / Q000379:methods*; D012377:Rodentia
D002273:Carcinogens; D009602:Nitrosamines