Statistical Methods for Outcome-Dependent Sampling

结果相关抽样的统计方法

• 批准号: 8727550
• 负责人: HAIBO ZHOU
• 金额: $ 26.68万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8727550
• 关键词: Age; Algorithmic Software; Attention deficit hyperactivity disorder; Budgets; Child; Childhood; Cohort Studies; Collaborations; Computer software; Data; Data Set; Disease; Environmental Exposure; Epidemiologic Studies; Failure; Follow-Up Studies; Future; Generations; Investigation; Linear Regressions; Malignant Neoplasms; Methods; Modeling; Mothers; National Institute of Environmental Health Sciences; Oils; Outcome; Perinatal; Phase; Probability; Procedures; Publications; Regression Analysis; Research; Research Design; Research Personnel; Sample Size; Sampling; Sampling Biases; Scheme; Staging; Statistical Methods; Sum; Time; Toxicant exposure; Uranium; base; cancer risk; cost effective; design; follow-up; innovation; magnetic field; malignant breast neoplasm; novel; public health relevance; response; simulation; software development; user friendly software; web page; web site

DESCRIPTION (provided by applicant): We propose innovative and cost-effective sampling designs that will enable the investigators to collect more informative samples at a fixed budget. We will also develop/evaluate new and efficient statistical methods that will reap the gains provided by these designs. User-friendly software and algorithms of the proposed designs/methods will be developed and disseminated. The proposed designs are generally multi-stage based and are of a biased sampling scheme where one observes the main exposure variable with a probability that depends on the outcome variable and auxiliary covariates. The proposed research is in response to the needs in design a more powerful study and these designs have been used in the current ongoing studies. These studies are collaborations the PI has with researchers at National Institute of Environmental Health Sciences to study the effects of environmental exposures on cancer and other diseases. The specific aims include: (1) Develop a FDS and two-stage FDS design for the Norwegian Mother and Child Cohort Study (MoBA) and evaluate an estimated empirical likelihood method. Data from MoBa study as well as the Cancer Risk in Uranium Miners Study will be analyzed; (2) Pro- pose a two-phase probability-dependent sampling (PDS) design for the Gulf Oil Spill Long-term Follow Up Study (GuLF) and evaluate a linear regression analysis and linear mixed model with PDS design. Data from GuLF Study will be analyzed with these methods. (3) Develop a two-stage Longitudinal outcome dependent sampling (LODS) sampling design for the Generation R Study with either a baseline response based sampling scheme or summation of all responses based sampling scheme. Data from Generation R Study as well as Collaborative Perinatal Project (CPP) will be analyzed with these methods; (4) Develop inference procedure for a continuous secondary response in a two-stage ODS design and a two-stage FDS design; Data from CPP Study, MoBa Study, and Uranium Miners Study will be analyzed; (5) Power study and optimal sample size allocation to achieve the maximum power for a given budget for studies with a two-stage FDS and two-phase PDS designs. The strengths and weaknesses of each proposed method will be critically examined via theoretical investigations and simulation studies. The developed software will be made available through publication and dedicated web page which will come with "User's Guide" as well as illustrative data examples on how to use them. Successful completion of the proposed research will have a significant impact on how future cost-effective biomedical studies to be conducted and how data from these studies be efficiently analyzed.

描述（由申请人提供）：我们提出创新和具有成本效益的抽样设计，使研究人员能够在固定预算下收集更多信息样本。我们还将开发/评估新的和有效的统计方法，以获得这些设计提供的收益。拟定的设计/方法的用户友好软件和算法将被开发和分发。所提出的设计通常是基于多阶段的，并且采用有偏抽样方案，其中观察主要暴露变量的概率取决于结果变量和辅助协变量。提出的研究是为了响应设计一个更强大的研究的需要，这些设计已经在目前正在进行的研究中使用。这些研究是PI与国家环境健康科学研究所的研究人员合作进行的，目的是研究环境暴露对癌症和其他疾病的影响。具体目标包括：(1)为挪威母亲和儿童队列研究（MoBA）开发FDS和两阶段FDS设计，并评估估计的经验似然方法。将分析MoBa研究和铀矿工人癌症风险研究的数据；(2)提出墨西哥湾溢油长期跟踪研究（Gulf）的两阶段概率相关抽样（PDS）设计，并对PDS设计下的线性回归分析和线性混合模型进行评价。来自GuLF Study的数据将用这些方法进行分析。(3)为R代研究制定两阶段的纵向结果相关抽样（LODS）抽样设计，采用基于基线反应的抽样方案或基于所有反应的抽样方案的总和。R世代研究和围产期合作项目（CPP）的数据将用这些方法进行分析；(4)开发两阶段ODS设计和两阶段FDS设计中连续二次响应的推理程序；将分析CPP研究、MoBa研究和铀矿商研究的数据；(5)两阶段FDS和两阶段PDS设计的功率研究和最佳样本量分配，以实现给定预算下的最大功率。每个提出的方法的优点和缺点将通过理论调查和模拟研究进行严格审查。开发的软件将通过出版物和专门的网页提供，该网页将附有“用户指南”以及如何使用这些软件的说明性数据示例。拟议研究的成功完成将对今后如何进行具有成本效益的生物医学研究以及如何有效地分析这些研究的数据产生重大影响。