STATISTICAL METHODS FOR OUTCOME-DEPENDENT SAMPLING

这项资助申请的主要目的是开发和评估改进的统计方法，用于设计和分析采用结果依赖抽样（ODS）方案进行的流行病学研究。抽样策略，导致一个更具成本效益的设计在给定的设置将进行调查。所提出的方法对于癌症和环境研究特别有用，因为暴露错误分类和昂贵的暴露评估是常见的挑战。该提案包括四个项目。第一个项目涉及一个连续结果变量的一阶段ODS设计。在该项目中，将研究对回归参数进行推断的两种方法：针对观察到的ODS样本的半参数似然方法，以及当基础队列的结果变量值已知时进一步提高效率的伪似然方法。第二个项目考虑在存在替代和缺失/错误测量的暴露信息的情况下病例对照研究的新推断程序。第三个项目涉及一个新的半参数似然推理程序，提高研究效率相结合的上级测量暴露的ODS样本和一个低劣的测量从底层队列人口。第四个项目认为一个新的半参数似然为基础的推理程序的两阶段ODS设计与连续的结果变量。该设计使用第一阶段受试者的替代或混杂协变量的信息，在第二阶段的抽样中从某些亚群中进行目标抽样。每种方法的优点和缺点将通过理论研究和模拟研究进行严格审查。将与现有方法进行比较。将开发相关软件。将使用开发的方法分析正在进行的关于环境和营养暴露影响以及癌症和心血管疾病的流行病学研究的数据集。这些研究包括磁场和乳腺癌风险研究、围产期合作项目、铀矿工人癌症风险研究、社区动脉粥样硬化风险研究、妊娠、感染和营养研究以及预防、压力和早产流行病学研究。

The main objective of this grant application is to develop and evaluate improved statistical methods for the design and analysis of epidemiologic studies conducted with an outcome-dependent sampling (ODS) scheme. Sampling strategies that lead to a more cost-effective design in a given setting will be investigated. The proposed methods are particularly useful for cancer and environmental research because exposure misclassification and expensive exposure assessment are frequent challenges. The proposal consists of four projects. The first project deals with a onestage ODS design with a continuous outcome variable. In this project, two methods for making inferences about regression parameters will be studied: a semiparametric likelihood approach for observed ODS sample, and a pseudo-likelihood approach for further improving efficiency when the values of the outcome variable are known for the underlying cohort. The second project considers a new inference procedure for case-control studies in the presence of surrogate and missing/mismeasured exposure information. The third project concerns a new semiparametric likelihood based inference procedure that improves study efficiency by combining a superior measurement of exposure from the ODS sample and an inferior measurement from the underlying cohort population. The fourth project considers a new semiparametric likelihood based inference procedure for a two-stage ODS design with a continuous outcome variable. This design uses the information on surrogate or confounding covariates for subjects in stage one, to target sampling from certain subpopulations in the second stage of sampling. The strengths and weaknesses of each proposed method will be critically examined via theoretical investigations and simulation studies. Comparisons with existing methods will be conducted. Related software will be developed. Data sets from ongoing epidemiologic studies on the effects of environmental and nutritional exposures, and on cancer and cardiovascular disease will be analyzed using the methods developed. These include the Magnetic Fields and Breast Cancer Risk Study, the Collaborative Perinatal Project, the Cancer Risk in Uranium Miners Study, the Atherosclerosis Risk in Communities Study, the Pregnancy, Infection, and Nutrition Study, and the Epidemiology of Exertion, Stress, and Preterm Delivery Study.