Statistical Methods for Outcome-Dependent Sampling

结果相关抽样的统计方法

• 批准号: 7465043
• 负责人: HAIBO ZHOU
• 金额: $ 22.49万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-01 至 2011-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7465043
• 关键词: Androgen Antagonists; Benchmarking; Budgets; Cohort Studies; Computer software; Cost Savings; Data; Data Set; Development; Disease; Environmental Exposure; Epidemiologic Studies; Evaluation; Family; Heart; Investigation; Linear Models; Malignant Neoplasms; Measures; Methods; Outcome; Perinatal; Probability; Probability Samples; Productivity; Public Health; Regression Analysis; Relative (related person); Research; Research Design; Research Personnel; Resources; Sampling; Sampling Biases; Scheme; Staging; Statistical Methods; Study of magnetics; Techniques; Testing; Time; Uranium; analytical method; base; cancer risk; cost; design; environment related cancer; improved; indexing; interest; magnetic field; malignant breast neoplasm; prospective; response; simulation; tool

DESCRIPTION (provided by applicant): We will develop and evaluate improved statistical methods for the design and analysis of biomedical studies conducted with general biased sampling design schemes, the univariate and multivariate outcome-auxiliary- dependent sampling (OADS) and the two-stage OADS designs. The advantage of such designs is that it allows both prospective and retrospective samples at the same time where the prospective sample provides the benefits of a cohort study and the retrospective sample enables investigators to concentrate resources on where there is the greatest amount of information, i.e., some judiciously chosen subsets based on the outcome and auxiliary covariate information. New statistical methods is needed to achieve the potential statistical efficiency. Extension of the simple ODS design to allow the sampling probability to depend on a continuous outcome and a continuous auxiliary covariates will be developed. We also develop optimal two-stage OADS designs under commonly encountered budget and precision/power constraints in practice. Tools and benchmark for distinguishing available sampling options in the planning stage of the study will be developed. These are the relative-budget-index for fixed precision/power case and the relative-gain-index for fixed budget case. The proposed methods are particularly useful in cancer and environmental research where auxiliary exposure information and expensive exposure assessment are frequent challenges. The proposal consists of six projects. The first project deals with semiparamtric efficient inference for two-stage OADS design where the first stage data can be either from a simple random sample or from an ODS sample itself. The second project concerns the optimal two-stage OADS design for a fixed budget and the development of a formal evaluation criteria (RGI) that measures the closeness of an alternative design to the optimal one. The third project concerns the optimal two-stage OADS design for a given precision/power and the development of a formal evaluation criteria (RBI) that measures the closeness of an alternative design to the optimal one (the one with the minimal budget). The fourth project considers a multivariate OADS and multivariate two-stage OADS design and develop the semiparametric inferences for correlated responses under the multivariate OADS. The fifth project concerns a partial linear model for the nonlinear exposure effects in both fixed and random effects regression analysis under an OADS and two-stage OADS design. The sixth project investigates a variable selection and hypothesis testing techniques for data from two-stage OADS design. The strengths and weaknesses of proposed methods will be critically examined via theoretical investigations and simulations. Cost-effective sampling strategies in a given setting will be investigated. Comparisons with existing methods will be conducted. Related software will be developed. Data sets from epidemiologic and environmental studies on the effects of environmental exposures, and on cancer and other diseases will be analyzed. These include the Cancer Risk in Uranium Miners Study, the Magnetic Fields and Breast Cancer Risk Study, the Collaborative Perinatal Project, the Family Heart Study, and the DDE-antiandrogen Study. PUBLIC HEALTH RELEVANCE: We propose and investigate some new study designs/analytical methods that will allow biomedical study to be conducted less costly in practice while still providing a good statistical power to detect the effect of interests. These designs allow investigators to conduct their study more efficiently for a given budget and hence can help improve the overall efficiency and productivity of the public health research.

描述(申请人提供)：我们将为生物医学研究的设计和分析开发和评估改进的统计方法，这些设计和分析采用一般有偏抽样设计方案、单变量和多变量辅助结果相关抽样(OADS)以及两阶段OADS设计。这种设计的优点是，它允许前瞻性和回溯性样本同时进行，其中前瞻性样本提供了队列研究的好处，回溯性样本使研究人员能够将资源集中在信息量最大的地方，即根据结果和辅助协变量信息明智地选择一些子集。需要新的统计方法来实现潜在的统计效率。将开发简单的ods设计的扩展，以允许抽样概率取决于连续的结果和连续的辅助协变量。在实际应用中，我们还开发了在预算和精度/功率约束下的最优两阶段OADS设计。将制定工具和基准，以便在研究的规划阶段区分可用的抽样选择。它们是固定精度/功率情况下的相对预算指数和固定预算情况下的相对增益指数。建议的方法在癌症和环境研究中特别有用，在这些领域，辅助暴露信息和昂贵的暴露评估是经常面临的挑战。 该提案包括六个项目。第一个项目涉及两阶段OADS设计的半参数有效推断，其中第一阶段的数据可以来自简单的随机样本，也可以来自消耗臭氧层物质样本本身。第二个项目涉及固定预算的最优两阶段OADS设计，以及制定衡量备选设计与最佳设计接近程度的正式评价标准。第三个项目涉及给定精度/功率的最优两阶段OADS设计，以及制定衡量备选设计与最佳设计(预算最小的设计)接近程度的正式评估标准(RBI)。第四个项目考虑了多变量OADS和多变量两阶段OADS，设计并发展了多变量OADS下相关响应的半参数推断。第五个项目涉及OADS和两阶段OADS设计下的固定和随机效应回归分析中的非线性暴露效应的部分线性模型。第六个项目研究了两阶段OADS设计数据的变量选择和假设检验技术。 所提出的方法的优点和缺点将通过理论研究和模拟进行严格的检验。本课程将探讨在特定环境下的成本效益抽样策略。将与现有方法进行比较。将开发相关软件。将分析流行病学和环境研究中关于环境暴露的影响以及癌症和其他疾病的数据集。这些研究包括铀矿工的癌症风险研究、磁场与乳腺癌风险研究、合作围产期项目、家庭心脏研究和DDE-抗雄激素研究。公共卫生相关性：我们提出并调查了一些新的研究设计/分析方法，这些方法将使生物医学研究在实践中成本更低，同时仍提供良好的统计能力来检测利益的影响。这些设计使研究人员能够在给定的预算内更有效地进行研究，从而有助于提高公共卫生研究的整体效率和生产率。