Estimating the mixture of proportional hazards model with incomplete failure data

Cox’s proportional hazards model (PHM) has been widely applied to the analysis of lifetime data. It involves covariates influencing the failure of products. Regarding the covariates as discrete random variables, the probability model is reduced to a mixture of PHM. This article presents a statistical procedure to estimate model parameters in the mixture of PHM. The estimation procedure is developed in a parametric framework when not only complete sets of field data but also incomplete ones are given. The expectation‐maximization algorithm is employed to handle the incomplete data problem. Simulation results are presented to illustrate the accuracy and some properties of the estimation results.