Semiparametric and Empirical Process Methods in Oncology

描述（由申请人提供）：拟议项目的长期目标是为流行病学研究和临床试验中的癌症研究开发灵活的半参数分析工具。上一奖项名称的变化反映了原始资助（R29 CA75 142）中大部分目标的完成，以及对半参数和经验过程方法的更加重视，这些方法在上一资助的多变量临床试验研究中发挥着越来越重要的作用。半参数模型在医学研究中非常有用，因为它们既涉及通常易于解释的参数部分，又涉及在生物不确定性存在的情况下允许更大灵活性的非参数部分。提出的三个相互关联的目标是：（1）开发和评估半参数比例风险脆弱性回归模型的推理方法，以解释事件时间数据中未观察到的个体水平异质性； (2) 开发和评估癌症研究中灵活的半参数危险因素测试工具； (3) 创建工具，对半参数模型中的生存​​函数、分位数函数和风险函数进行高效的计算推理。用于这些具有挑战性和相互关联的目标的主要统计研究方法包括经验过程和半参数推理技术以及蒙特卡罗计算方法。这些目标将为癌症研究人员提供一系列显着改进的有用建模工具。

DESCRIPTION (provided by applicant): The long-term goal of the proposed project is to develop flexible semi parametric analysis tools for cancer research in both epidemiologic studies and clinical trials. The change in title from the previous award reflects the completion of most of the aims in the original grant (R29 CA75 142) as well as a greater emphasis on semi parametric and empirical process methods which played an increasingly important role throughout the previous grant's multivariate clinical trial research. Semi parametric models are useful in medical research because they involve both a parametric component which is usually easy to interpret and a nonparametric component which permits greater flexibility in the presence of biologic uncertainty. The three proposed interrelated aims are: (1) Develop and evaluate inferential methods for semi parametric proportional hazards frailty regression models to account for unobserved individual-level heterogeneity in time-to-event data; (2) Develop and evaluate tools for flexible semi parametric risk-factor testing in cancer studies; and (3) Create tools for computationally efficient inference for survival, quantile and hazard functions in semi parametric models. The primary statistical research methods used for these challenging and interrelated aims include empirical process and semi parametric inference techniques as well as Monte Carlo computational approaches. These aims will provide cancer researchers with a significantly improved collection of useful modeling tools.