Survival Analysis and Related Topics

该研究开发了统计模型、方法和相关理论，以解决生存数据的设计、建模和分析中出现的问题，这些数据经常受到审查、截断和/或其他类型的缺失。它为生存数据引入了新的基于风险的回归模型，扩展和补充了标准的比例风险回归，但仍然具有后者所具有的基本良好特征。除了通常的右截除数据外，它还通过利用模型变异和开发合适的分析工具，为区间截除、随机效应和多元生存时间等重要而困难的问题提供了解决方案。它包括寻找计算上方便的表示，并为离散（生存）数据的分析建立清晰的理论性质，特别是那些可以用二乘二或更多的一般列联表总结的数据。回顾性研究通常被概括为病例-对照和病例-队列回归问题，适合于回顾性研究的新方法和理论也得到了发展。生存数据是在许多科学调查中收集的，包括生物医学后续研究、工业寿命试验、经济持续时间研究、天文学、人口统计学等。发展适当的统计方法对于处理这些数据至关重要，这样才能得出有效的科学结论。本项目开发了几种新方法，其中一些适用于识别与健康有关的风险因素，如暴露于有害环境、食用某些食物等，另一些适用于评估治疗效果和医疗的成本效益。这些新方法可能影响公共和科学利益的其他领域，其中一个例子是研究影响失业持续时间的因素。

Ying The research develops statistical models, methodologies and related theory to address issues arising from design, modeling and analysis of survival data, which are often subject to censoring, truncation and/or other types of missingness. It introduces new hazard-based regression models for survival data that extend and complement the standard proportional hazards regression, and yet still possess essential good features that the latter has. Besides the usual right-censored data, it also provides solutions to such important and difficult problems as interval censoring, random effects and multivariate survival times by exploiting model variation and developing suitable analytic tools. It involves finding computationally convenient representations and establishing sharp theoretical properties for the analysis of discrete (survival) data, particularly of those that can be summarized by two-by-two or more general contingency tables. New methods and theory tailored to retrospective studies, which are often summarized as the case-control and case-cohort regression problems, are also developed. Survival data are collected in many scientific investigations, including biomedical follow-up studies, industrial life tests, study of economic durations, astronomy, demography among others. Development of suitable statistical methods is crucial to handling of such data so that valid scientific conclusions can be derived. This project develops several novel approaches, some of which are suitable for identification of health related risk factors, such as exposure to hazardous environment, consumption of certain foods etc., and others are applicable to evaluation of therapeutic effects as well cost effectiveness of medical treatments. These new methods may impact other areas of public and scientific interests, an example of which is the study of factors influencing unemployment duration.