Applications of Modern Statistical Thinking to the Social Sciences

该项目的目的是继续开发新的统计工具和方法，以解决经验性社会科学研究中真正令人关切的问题。以前的工作主要集中在多重补偿技术上，其中包括一系列处理不完整数据的技术。人口普查局和国税局等政府机构越来越多地使用这些技术。在广泛主题的学术研究中的应用也有所增加。事实上，从社会调查到临床医学方案，大量使用的科学数据都存在着不完备性。拟议的研究涉及四个主要领域。首先，将继续努力磨练多重归责的工具。第二，将继续采用现代统计计算方法，如EM算法和Gibbs采样器的扩展。第三，将进一步发展因果推理的基础和在观察性研究中得出因果推理的实用方法。第四，将探索与社会科学研究相关的各种其他技术，如荟萃分析和混合建模。首席调查员在该项目所涵盖的广泛领域作出的统计贡献在深度和数量上都令人印象深刻。此外，他在这项长期研究议程中培训的许多学生都非常有能力传播研究结果，并加入到推动最先进技术的行列中来。他取得进一步重大成就的可能性很高。

The purpose of this project is to continue the development of new statistical tools and methods that address real issues of concern in empirical social science research. The primary focus of the prior work was on multiple imputation technology, which includes a family of techniques dealing with incomplete data. These techniques have been used increasingly by government agencies such as the Census Bureau and the Internal Revenue Service. Applications also have grown in academic research on a wide range of topics. Incompleteness, in fact, pervades intensively used scientific data as far ranging as social surveys and clinical medical protocols. Four main areas are addressed in the proposed research. First, continuing efforts will be made to hone the tools for multiple imputation. Second, modern methods of statistical computation such as extensions of the EM algorithm and the Gibbs sampler, will continue to be pursued. Third, the foundations of causal inference and practical methods for drawing causal inferences in observational studies will be further developed. And fourth, a variety of other techniques relevant to social science research, such as meta-analysis and mixture modelling, will be explored. The principal investigator's statistical contributions in the broad areas covered by this project have been impressive both in depth and volume. In addition, the many students he has trained in this long-term research agenda are superbly equipped to disseminate the results and to join in advancing the state of the art. The prospect of his achieving further significant accomplishments is very high.