CAREER: Adaptive experiments towards learning treatment effect heterogeneity

职业:学习治疗效果异质性的适应性实验

基本信息

  • 批准号:
    2239047
  • 负责人:
  • 金额:
    $ 45.28万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-09-01 至 2028-08-31
  • 项目状态:
    未结题

项目摘要

Understanding and characterizing differential and heterogeneous causal effects have become increasingly important in many scientific fields. For example, in precision health, identifying differential treatment effects serves as an essential step towards materializing the benefits of precision health, because it provides evidence regarding how individuals with specific characteristics respond to a given treatment either in efficacy or in adverse effects. In social science research, evaluations of the effectiveness of government programs or public policies across different individuals inform more effective policy-making. As reliably designed randomized experiments often provide evidence of the highest grade for verifying the effectiveness of a treatment or an intervention, this research project aims to develop three randomized experimental design strategies for better learning causal effect heterogeneity. These design strategies are broad and will be applicable in clinical trials, social experiments in biomedical sciences, public health sectors, and online controlled experiments in technological enterprises. Since the project will develop modern experimental design strategies and new statistical methods with many applications, this research project will provide opportunities for integrating research with teaching and training students across different stages. The project will impact STEM education through the training of undergraduate and graduate students and the recruitment of students from underrepresented groups into (bio)statistical fields. Activities to achieve these education-related goals include introductory reading groups, course developments, university undergraduate research programs, and outreach activities to underrepresented minorities.This research project will develop three novel response adaptive experimental design strategies and theoretical insights toward learning treatment effect heterogeneity from a frequentist viewpoint. The first strategy will focus on designing randomized experiments to sequentially allocate experimental efforts so that subpopulations mostly harmed or benefited from a particular treatment can be efficiently identified. The second strategy will focus on learning treatment effect heterogeneity measured by the variability of the conditional causal effect variability. The learned heterogeneity allows the development of a new efficient covariate-adjusted response adaptive framework whose estimator may attain the best achievable efficiency. The third strategy aims to further materialize the benefit of treatment effect heterogeneity by designing randomized experiments to maximize participants' overall welfare. The research project is thus expected to open a new research connection between adaptive experiments and social welfare improvement.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
在许多科学领域,理解和描述不同的和异质的因果效应变得越来越重要。例如,在精准医疗领域,确定不同治疗效果是实现精准医疗效益的重要一步,因为它提供了证据,说明具有特定特征的个体如何对特定治疗产生疗效或不利影响。在社会科学研究中,对不同个体的政府项目或公共政策的有效性进行评估,可以为更有效的决策提供信息。由于可靠设计的随机实验通常为验证治疗或干预的有效性提供最高等级的证据,本研究项目旨在制定三种随机实验设计策略,以更好地了解因果效应异质性。这些设计策略是广泛的,将适用于临床试验、生物医学的社会实验、公共卫生部门和科技企业的在线对照实验。由于本研究将发展现代实验设计策略和具有多种应用的新统计方法,因此本研究项目将提供将研究与教学相结合的机会,并为不同阶段的学生提供培训。该项目将通过培训本科生和研究生以及从代表性不足的群体招募学生进入(生物)统计领域来影响STEM教育。实现这些教育相关目标的活动包括介绍性阅读小组、课程开发、大学本科生研究项目以及针对少数族裔的拓展活动。本研究项目将发展三种新的反应适应性实验设计策略,并从频率论的角度研究治疗效果异质性的理论见解。第一种策略将侧重于设计随机实验,按顺序分配实验努力,以便有效地识别出最受伤害或从特定治疗中受益的亚群。第二种策略将关注学习治疗效果的异质性,通过条件因果效应的变异性来衡量。学习到的异质性允许开发一种新的有效的协变量调整响应自适应框架,其估计器可以达到最佳的可实现效率。第三种策略旨在通过设计随机实验,使参与者的整体福利最大化,从而进一步实现治疗效果异质性的益处。因此,该研究项目有望在适应性实验和社会福利改善之间开辟新的研究联系。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

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Jingshen Wang其他文献

Comparative study of a nano-bacterial rat kidney stone model and the traditional ethylene glycol rat kidney stone model
纳米细菌大鼠肾结石模型与传统乙二醇大鼠肾结石模型的对比研究
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    B. Qian;Jingshen Wang;Z. Hao;Yuan Wang;Heng Yang;Yongle Li;Minghui Tan;Guoxi Zhang;X. Zou
  • 通讯作者:
    X. Zou
Systematic identification of modifiable risk factors and drug repurposing options for Alzheimer's disease: Mendelian randomization analyses
系统识别阿尔茨海默病的可改变风险因素和药物再利用选择:孟德尔随机分析
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chong Wu;Lang Wu;Jingshen Wang;Lifeng Lin;Yanming Li;Qing Lu;Hong
  • 通讯作者:
    Hong
Rudi Kundini, Pamoja Kundini (RKPK): study protocol for a hybrid type 1 randomized effectiveness-implementation trial using data science and economic incentive strategies to strengthen the continuity of care among people living with HIV in Tanzania
Rudi Kundini、Pamoja Kundini (RKPK):使用数据科学和经济激励策略来加强坦桑尼亚艾滋病毒感染者护理连续性的 1 型混合随机有效性实施试验的研究方案
  • DOI:
    10.1186/s13063-024-07960-x
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    2.5
  • 作者:
    Jillian L Kadota;Laura Packel;Matilda Mlowe;Nzovu K Ulenga;Natalino Mwenda;P. Njau;William H Dow;Jingshen Wang;Amon Sabasaba;Sandra I McCoy
  • 通讯作者:
    Sandra I McCoy
Debiased inference on heterogeneous quantile treatment effects with regression rank scores
使用回归排名分数对异质分位数治疗效果进行去偏推断
Preoperative risk factors associated with urosepsis following percutaneous nephrolithotomy: a meta-analysis
经皮肾镜取石术后尿脓毒症相关的术前危险因素:一项荟萃分析
  • DOI:
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Z. Hao;Jingshen Wang;Qinzhang Wang;Guangchao Luan;Biao Qian
  • 通讯作者:
    Biao Qian

Jingshen Wang的其他文献

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{{ truncateString('Jingshen Wang', 18)}}的其他基金

ATD: Algorithms for Real-time Dynamic Risk Identification with Statistical Confidence
ATD:具有统计置信度的实时动态风险识别算法
  • 批准号:
    2220537
  • 财政年份:
    2023
  • 资助金额:
    $ 45.28万
  • 项目类别:
    Standard Grant
Robust Post-Selection Inference with Application to Subgroup Analysis
稳健的选择后推理及其在子组分析中的应用
  • 批准号:
    2015325
  • 财政年份:
    2020
  • 资助金额:
    $ 45.28万
  • 项目类别:
    Standard Grant

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通过中央指令和政策实验实现适应性威权主义
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