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

用于非线性/风险/中心回归的非/半参数方法；

• 批准号: RGPIN-2017-05047
• 负责人: Singh, Radhey
• 金额: $ 1.17万
• 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: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=636005
• 关键词: Non; semiparametric; methods; nonlinear; hazards

When the response is the time-to-event outcome such as lifetimes of patients, failure times, the data are often censored and involve time dependent covariates. For example, in a clinical trial, the 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 time 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 centers. Part of the objective of this research proposal is to develop improved non/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 as well as their efficiency and the optimal convergence rates.

当响应是事件发生时间的结果（例如患者的寿命，失败时间）时，数据通常会受到审查并涉及依赖时间的协变量。例如，在一项临床试验中，研究人员有兴趣评估治疗对HIV-1血清阳性药物使用者对其他预测性协变量（例如BMI（身体混乱指数）和年龄）的影响。研究终止时，一些患者可能仍然活着。因此，这些患者的生存时间进行了审查。另一方面，当患者从不同的健康中心带走时，同一中心的患者之间可能存在依赖性。该研究建议的一部分是为了开发改进的非/半参数回归模型，用于固定和混合协方差效应，并审查样品和聚集样品，并研究估计器的较大样本性能及其效率及其最佳收敛速率。