A Mixture Model Combining Logistic Regression with Proportional Hazards Regression
提出一个混合模型，用逻辑回归处理事件是否发生，用比例风险模型处理事件发生时间，适用于删失数据分析，并通过模拟验证估计方法的有效性。
A model is proposed for the analysis of censored data which combines a logistic formulation for the probability of occurrence of an event with a proportional hazards specification for the time of occurrence of the event. The proposed model is a semiparametric generalization of a parametric model due to Farewell (1982). Estimates of the regression parameters are obtained by maximizing a Monte Carlo approximation of a marginal likelihood and the EM algorithm is used to estimate the baseline survivor function. We present some simulation results to verify the validity of the suggested estimation procedure. It appears that the semiparametric estimates are reasonably efficient with acceptable bias whereas the parametric estimates can be highly dependent on the parametric assumptions.