Statistical analysis of competing risks models

Statistical inference for the parameters in three competing risks models is considered in this paper. It is assumed that there are more than two causes of failure. The maximum likelihood procedure is used to derive point and asymptotic confidence interval estimates of the unknown parameters. The risks due to each cause of failure are investigated. Two sets of data are analyzed in order to (1) illustrate how the model can be applied and (2) test the hypothesis that the causes of failure follow the Chen distribution rather than the exponential distribution, or the Weibull distribution.