Novel nonparametric methods for prognosis studies with missing covariates

在预后研究中经常会遇到生存数据缺失时间独立或时间依赖协变量的情况。现有的方法大多集中在标准的比例风险模型，这可能是在某些应用中受到限制。为了全面了解数据，识别与生存时间相关的变量也很重要。在这项研究中，研究人员将开发更灵活的模型与缺失的协变量的非参数方法，并探讨在这个复杂的设置变量的选择，拟议的研究预计将产生广泛的影响和应用在生物医学研究，计量经济学，环境研究，行为和社会科学，其中信息收集的时间感兴趣的事件和多个协变量。这项拟议的研究将促进来自不同机构/部门和背景的研究人员之间的合作。它将促进格鲁吉亚大学统计系和新成立的流行病学和生物统计学系的教学、培训和学习。在这项研究中进行的研究将有助于开发高级研究生课程的生存分析，缺失数据和变量选择。它将为研究人员监督的研究生创造具有挑战性的统计项目。这项建议的研究结果将通过在主要统计会议上的介绍加以传播。所开发的软件将公开提供，以便所提出的方法可以在各个领域的实践中方便地使用。

Survival data with missing time-independent or time-dependent covariates are commonly encountered in prognosis studies. Existing approaches mostly focus on the standard proportional hazards model, which may be too restricted in some applications. To obtain a comprehensive understanding of data, it is also important to identify variables that are associated with survival time. In this study, the investigators will develop nonparametric approaches for more flexible models with missing covariates, and investigate variable selection in this complicated setup.The proposed research is expected to have broad impacts and application in biomedical studies, econometrics, environmental studies, behavioral and social sciences, where information is collected on time to an event of interest and multiple covariates. This proposed study will foster collaborations among investigators from different institutions/departments and backgrounds. It will promote teaching, training and learning in the Statistics Department and the newly founded Epidemiology and Biostatistics Department at the University of Georgia. Research conducted in this study will help develop advanced graduate courses in survival analysis, missing data and variable selection. It will create challenging statistical projects for graduate students that the investigators are supervising. Research results from this proposal will be disseminated through presentation at major statistical meetings. Software developed will be made publicly available, so that the proposed methods can be readily used in practice in various fields.