New Statistical Methods for Randomized Experiments in Political Science and Public Policy

政治学和公共政策随机实验的新统计方法

• 批准号: 0752050
• 负责人: Kosuke Imai
• 金额: $ 5.26万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-01 至 2009-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0752050&HistoricalAwards=false
• 关键词: New; Statistical; Methods; Randomized; Experiments

Randomization of treatment assignment has been one of the most powerful tools for the development of modern science ever since the 1920s, and randomized experiments have been widely used to test hypotheses in the natural sciences. The fields of political science and public policy were long dominated by observational studies, but they now show growing use of experimental studies. The goal of the proposed research is to develop and evaluate new methods for the statistical analysis of randomized experiments. In the social sciences, experiments are often conducted outside of a laboratory to increase the generalizability of conclusions. However, this comes at the expense of having complete control over experimental participants' exposure to experimental treatments. Thus, statistical adjustments often must be made in order to ascertain valid causal effects. In the proposed research, new statistical methods will be developed and evaluated that address missing data problems in randomized experiments when the missing data mechanism depends on unobserved values of variables and implement efficient experimental designs when the unit of randomization is a cluster of individuals. The intellectual merit of the proposal lies in the wide applicability of the proposed methods within and beyond political science and public policy. The PI's ongoing strategy is to develop statistical methods in the context of specific experiments. Use of these motivating examples allows the PI to discover areas in which statistical analysis must be improved and new methods need to be developed. Five experiments will be analyzed; voting (survey) experiments in Germany and Japan, randomized evaluation of the Mexican universal health insurance program, a field experiment about deliberative decision-making in Africa, and a survey experiment about effects of racial priming on political attitudes. The PI has worked extensively on methodological research for causal inference with a particular emphasis on applications in political science, and the proposed research builds on the earlier work. The proposed methods as well as their substantive applications make original contributions. The broader impacts of this project are several. First, substantive progress will be made on the analyses of the aforementioned randomized experiments. New methods will be developed to better understand the effects of policy information and psychological manipulation on voting behavior; the health and financial effects of the Mexican universal health insurance program; the role of leaders in deliberative democracy; and the recent academic debate about racial priming. The proposed methods can also have applications beyond political science and public policy and into medical community recommendations for best practices in the conduct and analysis of cluster-randomized trials. The proposed research suggests the need to question the current standards for this research. Ultimately, improved methods will be made available to applied researchers with limited knowledge of statistical theory and computing.

自20世纪20年代以来，随机化治疗分配一直是现代科学发展最有力的工具之一，随机实验被广泛用于检验自然科学中的假设。政治学和公共政策领域长期以来以观察性研究为主，但它们现在越来越多地使用实验研究。本研究的目的是发展和评估随机实验统计分析的新方法。在社会科学中，实验经常在实验室之外进行，以增加结论的普遍性。然而，这是以完全控制实验参与者对实验治疗的暴露为代价的。因此，为了确定有效的因果关系，往往必须进行统计调整。在本研究中，将开发和评估新的统计方法，以解决随机实验中缺失数据的问题，当缺失数据的机制取决于变量的未观察值时，以及当随机化的单位是一群个体时，实现有效的实验设计。该建议的智力价值在于所提出的方法在政治学和公共政策内外的广泛适用性。PI目前的战略是在具体实验的背景下发展统计方法。使用这些鼓舞人心的例子，PI可以发现统计分析必须改进的领域和需要开发新方法的领域。将分析五个实验；德国和日本的投票（调查）实验，墨西哥全民健康保险计划的随机评估，非洲审议决策的实地实验，以及种族启动对政治态度影响的调查实验。PI在因果推理的方法论研究方面进行了广泛的工作，特别强调在政治学中的应用，而拟议的研究是建立在早期工作的基础上的。所提出的方法及其实际应用作出了原创性的贡献。这个项目有几个更广泛的影响。首先，上述随机实验的分析将取得实质性进展。将开发新的方法，以更好地了解政策信息和心理操纵对投票行为的影响；墨西哥全民健康保险方案的健康和财政影响；领导人在协商民主中的作用；最近关于种族启动的学术辩论。拟议的方法也可以应用于政治学和公共政策之外，并应用于医学界对进行和分析集群随机试验的最佳做法的建议。拟议的研究表明，有必要对这项研究的现行标准提出质疑。最终，改进的方法将提供给统计理论和计算知识有限的应用研究人员。