Statistical Methods for Partially Controlled Studies

描述(由申请人提供)：本项目的目标是 开发新的统计设计和方法，以更好地进行部分评估 公共卫生方面的对照研究。 有三个具体目标。第一个目标是开发评估方法 研究中的处理：不直接控制哪些受试者得到哪些 治疗，或哪些受试者提供结果；但确实控制了 提供治疗的地点。因为现有的方法，包括 标准工具变量，不能处理 接受治疗和提供结果的不可控因素，工作 根据目标1，对于适当的治疗评估是必不可少的。这项工作将是 应用于巴尔的摩正在进行的针头交换计划，以预防艾滋病毒 变速箱。第二个目标是开发临床试验的新方法。 控制接受的治疗，并衡量结果；a 测量治疗后替代终点；目标是估计 治疗对结果的影响是同时发生的和不是同时发生的 代孕妈妈。目标2下的方法使用了一种新类型的分层 不受控制的代理，避免了标准的复杂情况 治疗后变量的分层。这项工作对适当的 评估治疗后早期症状作为后期治疗的措施 效果，我们将把它应用于癌症和眼科试验。第三个目标 是开发研究设计的方法，其中：一些人退出了一项 纵向跟踪，以及我们在哪里可以找到(双样本)代表 辍学学生的子集。这项工作对于保持概括性是必不可少的 长期跟踪研究的结果，我们将应用它来更好地评估 青少年潜在的药物依赖时间到了。

DESCRIPTION (provided by applicant): The objective of this project is to develop new statistical designs and methods to better evaluate partially controlled studies in public health. There are three specific aims. The first aim is to develop methods to evaluate treatments in studies that: do not directly control which subjects get which treatment, or which subjects provide outcomes; but do control the location of the sites that provide the treatments. Because existing methods, including standard instrumental variables, cannot handle the coexistence of the uncontrolled factors of taking treatment and of providing outcomes, the work under aim 1 is essential for proper treatment evaluation. This work will be applied to ongoing needle exchange programs in Baltimore, for preventing HIV transmission. The second aim is to develop new methods for clinical trials where treatment received is controlled, and outcomes are measured; a post-treatment surrogate endpoint is measured; and the goal is to estimate the treatments effects on the outcome that are concurrent and not concurrent with the surrogate. The methods under aim 2 use a new type of stratification for the uncontrolled surrogates that avoid the complications of standard stratifications on post-treatment variables. This work is essential for proper evaluation of early post-treatment symptoms as measures of later treatment effect, and we will apply it to cancer and ophthalmology trials. The third aim is to develop methods for study designs where: some persons drop out of a longitudinal follow-up, and where we can find (double-sample) a representative subset of the dropouts. This work is essential for preserving generalizability of results from long follow-up studies, and we will apply it to better evaluate time to potential drug dependence in youths.