Maximum likelihood estimation in a semiparametric logistic/proportional-hazards mixture model
Maximum likelihood estimation in a semiparametric logistic/proportional-hazards mixture model
复制标题
DOI：
10.1111/j.1467-9469.2005.00415.x
复制
发表时间：
2005-03-01
影响因子：
1
通讯作者：
Sun, JG
中科院分区：
文献类型：
--
作者：
Fang, HB;Li, G;Sun, JG
我们考虑半参数Logistic/比例风险混合模型中的大样本推断。这一模型已被提出用来模拟存活率数据，在人群中存在对所考虑的事件不敏感的受试者的积极部分。以往对Logistic/比例风险混合模型的研究主要集中于开发未知参数的点估计程序。研究了基于半参数极大似然估计的大样本推断问题。特别地，我们建立了半参数极大似然估计的存在性、相合性和渐近正态结果。我们还得到了参数分量和非参数分量的一致方差估计。研究结果为在Logistic/比例风险混合模型下进行大样本推断提供了理论依据。
We consider large sample inference in a semiparametric logistic/proportional-hazards mixture model. This model has been proposed to model survival data where there exists a positive portion of subjects in the population who are not susceptible to the event under consideration. Previous studies of the logistic/proportional-hazards mixture model have focused on developing point estimation procedures for the unknown parameters. This paper studies large sample inferences based on the semiparametric maximum likelihood estimator. Specifically, we establish existence, consistency and asymptotic normality results for the semiparametric maximum likelihood estimator. We also derive consistent variance estimates for both the parametric and non-parametric components. The results provide a theoretical foundation for making large sample inference under the logistic/proportional-hazards mixture model.