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1920年代以来，治疗分配的随机化一直是现代科学发展的最强大工具之一，随机实验已被广泛用于测试自然科学中的假设。 政治学和公共政策领域长期以来一直受到观察研究的控制，但现在它们显示了对实验研究的日益增长的利用。 拟议的研究的目的是开发和评估新方法，以进行随机实验的统计分析。在社会科学中，实验通常是在实验室之外进行的，以提高结论的普遍性。但是，这是为了完全控制实验参与者对实验治疗的牺牲。因此，通常必须进行统计调整才能确定有效的因果关系。在拟议的研究中，将开发和评估新的统计方法，即当缺少的数据机制取决于变量的未观察值并实施有效的实验设计时，随机实验中缺失的数据问题时，将在随机实验中解决缺失。该提案的智力优点在于政治和公共政策内外提议的方法的广泛适用性。 PI的持续策略是在特定实验的背景下开发统计方法。使用这些激励的例子可以使PI发现必须改进统计分析并需要开发新方法的领域。将分析五个实验；在德国和日本进行投票（调查）实验，对墨西哥通用健康保险计划的随机评估，关于非洲审议决策的现场实验以及关于种族启动对政治态度的影响的调查实验。 PI在因果推断的方法论研究方面进行了广泛的研究，并特别强调政治学中的应用，而拟议的研究基于早期的工作。拟议的方法及其实质性应用做出了原始贡献。该项目的更广泛影响是几个。首先，将在上述随机实验的分析中取得实质性进展。将开发新方法，以更好地了解政策信息和心理操纵对投票行为的影响；墨西哥通用健康保险计划的健康和财务影响；领导人在审议民主中的作用；以及最近关于种族启动的学术辩论。拟议的方法还可以在政治学和公共政策之外以及医学界的建议中提出申请，以在集群随机试验的行为和分析中提出最佳实践。 拟议的研究表明，有必要质疑这项研究的当前标准。 最终，将为对统计理论和计算知识有限的应用研究人员提供改进的方法。