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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：飞芳胡题：适应性设计中的功率、可变性和最佳性摘要：适应性设计在分配决策中使用顺序累积的数据以达到某个目标。在这个建议中，目标是基于一个优化标准，例如最小化实验成本。研究人员使用假设检验的力量作为比较适应性设计的基准。他们从设计引起的实际分配和变化中，根据目标分配的偏差，明确地推导出功率与设计之间的关系。对于四类自适应设计：骨灰盒模型、序贯最大似然程序、双自适应偏置硬币设计和治疗效果映射，研究人员将唯一地统一理论，以便于基于功率、最优性和变异性进行比较。自适应设计在许多科学学科中都很有用，并在临床研究、工业实验、生物测定等领域有应用。其思想是在收集未来数据的决策中动态使用连续积累的数据，以满足某些目标，这些目标可能是最小化实验成本，最大化临床试验的预期治疗成功等。适应性设计的使用可以通过将当前知识整合到设计决策中来提高实验的效率。到目前为止，尚不清楚的是适应性设计的可变性与实验效率的关系。调查人员将制定指导方针，通过探索设计的可变性，直接比较设计的效率。这笔助学金将涉及两个校区的本科生和研究生，并将使人们更好地理解如何有效地设计昂贵或道德要求高的实验。