Power, Variability, and Optimality in Adaptive Designs

自适应设计中的强大功能、可变性和最优性

基本信息

批准号：
0204232
负责人：
Feifang Hu
金额：
$ 20.54万
依托单位：
University of Virginia Main Campus
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2002
资助国家：
美国
起止时间：
2002-07-15 至 2006-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=0204232&HistoricalAwards=false
关键词：
Power Variability Optimality Adaptive Designs

项目摘要

Proposal ID: DMS-0204232PI: Feifang HuTitle: Power, variability, and optimality in adaptive designsAbstract:Adaptive designs use sequentially accruing data in allocation decisions to reach some objective. In this proposal, the objective is based on an optimization criterion, such as minimizing the cost of an experiment. The investigators use the power of a hypothesis test as a benchmark for comparisons of adaptive designs. They explicitly derive the relationship between power and the design in terms of bias of the target allocation from the actual allocation and variation induced by the design. For four classes of adaptive designs: urn models, sequential maximum likelihood procedures, doubly adaptive biased coin designs, and treatment effect mappings, the investigators will uniquely unify the theory for easy comparison based on power, optimality, and variability.Adaptive designs are useful in many scientific disciplines and have application in clinical research, industrial experiments, bioassay, to name a few areas. The idea is to dynamically use sequentially accruing data in decisions for collecting future data in order to satisfy some objective, which could be minimizing the cost of an experiment, maximizing expected treatment successes in a clinical trial, etc. The use of adaptive designs can improve efficiency of an experiment by incorporating current knowledge into design decisions. Heretofore what has been unknown is the relationship of variability of the adaptive designs to efficiency of the experiment. The investigators will develop guidelines that will allow direct comparison of efficiency of designs by exploring their variability. The grant will involve both undergraduate and graduate students across two campuses and will lead to increased understanding of how to efficiently design costly or ethically demanding experiments.

提案ID：DMS-0204232PI：Feifang Hutitle：自适应设计中的功率，可变性和最佳性：自适应设计使用在分配决策中使用依次计算数据来达到目标。在此提案中，目标基于优化标准，例如最大程度地降低实验的成本。研究人员使用假设检验的力量作为比较自适应设计的基准。他们明确地从目标分配的偏差角度明确得出了功率与设计之间的关系，从设计引起的实际分配和变化。对于四类的自适应设计：urn模型，顺序最大似然程序，双重自适应偏见的硬币设计以及治疗效果映射，研究者将唯一地统一基于功率，最佳性和可变性的简易比较理论。适应性设计在许多科学的科学领域中都有用来在许多科学领域中应用，并且在工业研究中很少有临床研究，Bies Anipore a Anderial a Andial Andial Andial Andimains a Plays Andimains a Plays a Andoss Ane Biosears，Bize Ane biay。这个想法是在决策中动态地使用数据来收集未来数据以满足某些目标，这可以最大程度地降低实验的成本，从而最大程度地提高临床试验中的预期治疗成功等等。适应性设计的使用可以通过将当前知识纳入设计决策来提高实验的效率。迄今为止未知的是自适应设计与实验效率的可变性关系。调查人员将制定指南，以通过探索其可变性来直接比较设计的效率。该赠款将涉及两个校园的本科生和研究生，并将提高人们对如何有效设计昂贵或道德要求的实验的了解。