Abstract #301749

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JSM 2003 Abstract #301749
Activity Number: 206
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Physical and Engineering Sciences
Abstract - #301749
Title: Dropping the Masks: Simple Inference Procedures Based on the EM Algorithm for the Competing Risk Model with Masked Causes of Failure
Author(s): Thierry Duchesne*+ and Radu V. Craiu
Companies: Universite Laval and University of Toronto
Address: Department of Mathematics and Statistics, Quebec, PQ, G1K 7P4, Canada
Keywords: likelihood ratio test ; proportional hazards ; SEM algorithm ; symmetry assumption
Abstract:

We propose inference methods based on the EM algorithm for estimation of the parameters of a weakly parameterized competing risk model with masked causes of failure and second-stage data. By assuming piecewise constant cause-specific hazard functions and with a suitable definition of "complete data,'' we are able to carry out maximum likelihood estimation of the cause-specific hazard functions and of the masking probabilities with minimal assumptions. Both the E- and M-step of the algorithm can be solved in closed form under the full model and under some restricted models of interest. We show how one can obtain the observed information matrix and perform likelihood ratio tests of assumptions such as symmetry and proportional hazards. Robustness of the method is investigated through simulation, and an example of application to a dataset on hard drive failures (Flehinger et al. 2002) is provided.

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