Non/semiparametric methods for nonlinear/hazards/censored regression; Nonparametric monotone empirical Bayes; Non/semiparametric seemingly unrelated regression

用于非线性/危险/删失回归的非/半参数方法；

• 批准号: 4631-2012
• 负责人: Singh, Radhey
• 金额: $ 0.87万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=508445
• 关键词: Non; semiparametric; methods; nonlinear; hazards

When the response is the time-to-event outcome such as lifetimes of patients, data are often clustered and censored. For example, in a clinical trial, researchers are interested in evaluating the effect of a treatment on survival in the HIV-1 seropositive drug users adjusted for other predictive covariates such as BMI (body mess index) and age. Some patients may still be alive when the study terminates. Hence, the survival times of these patients are censored. On the other hand, when patients are taken from different health centers; there might be a dependence between patients in the same center. Part of the objective of this research proposal is to develop semi-parametric regression models for fixed and mixed covariate effects with censored and clustered samples and to investigate the large sample performance of the estimators.

当响应是事件发生时间结果（例如患者的寿命）时，数据通常会被聚类和审查。例如，在一项临床试验中，研究人员有兴趣评估治疗对 HIV-1 血清阳性吸毒者生存的影响，并根据 BMI（身体混乱指数）和年龄等其他预测协变量进行调整。当研究结束时，一些患者可能仍然活着。因此，这些患者的生存时间受到审查。另一方面，当患者来自不同的医疗中心时；同一中心的患者之间可能存在依赖性。本研究提案的部分目标是开发针对经过审查和聚类样本的固定和混合协变量效应的半参数回归模型，并研究估计器的大样本性能。