"Nonparametric Estimation with Applications to Large and Complex Survey Data"

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。当今调查统计学家面临的一个困难是调查的结构日益复杂。美国提供了各种各样的纵向调查，这些调查在捕捉动态人口关系方面比广泛使用的横截面数据有相当大的优势。从这些复杂的调查中做出尽可能不受模型影响的推论是可取的。非参数统计是一种灵活而有前途的工具，可以正确地反映复杂的设计结构。然而，在非参数测量分析中，同时考虑高维测量误差的检测、平滑和复杂相关结构带来的额外复杂性，给非参数测量分析带来了很大的挑战。研究者通过整合“廉价”的辅助信息，为大型和复杂的调查（包括纵向调查）研究新颖的非参数模型辅助方法。目前的项目包括：(1)开发更精细和更智能的非参数工具用于调查抽样；(2)研究存在非抽样误差（如非响应误差和测量误差）的非参数调查方法；(3)探索纵向调查分析的新方法和新理论。由于社会、技术和理论的发展，调查研究领域正在经历深刻而迅速的变化。随着许多研究领域的大型复杂调查越来越多地可供公众使用，本提案中的理论和实践可以作为调查从业者、（生物）统计学家、流行病学家、经济学家、社会学家和其他研究人员的重要工具。所提出的方法将大大丰富纵向调查建模技术，拓宽对调查抽样的传统理解。拟议的研究还将加强美国联邦统计系统，为几个联邦机构（包括人口普查局、国家卫生统计中心、司法统计局和劳工统计局）的调查研究人员提供现代和先进的调查方法。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). One difficulty facing today's survey statisticians is the increasingly complex structures of surveys. The U.S. is very well provided with various sorts of longitudinal surveys which have considerable advantages over widely used cross-sectional data for capturing dynamic demographic relationships. It is desirable to make inferences from these complex surveys as model-free as they can be. Nonparametric statistics is a flexible and promising tool that properly reflects complex design structures. However, the simultaneous consideration of detection of survey errors with high dimensionality, smoothing and the additional complexity emerging from complex correlation structures presents great challenges in nonparametric survey analysis. The investigator works on novel nonparametric model-assisted methods for large and complex surveys, including longitudinal surveys, via incorporation of "cheap" auxiliary information. The current project includes (1) developing finer and more intelligent nonparametric tools for survey sampling; (2) investigating nonparametric survey methodology in the presence of nonsampling errors, such as nonresponse and measurement errors;(3) exploring new procedures and novel theory in longitudinal survey analysis.The field of survey research is undergoing profound and rapid changes brought on by larger societal, technological, and theoretical developments. With large complex surveys in many research areas becoming increasingly available for public use, the theory and practice in this proposal can serve as an important tool for survey practitioners, (bio)statisticians, epidemiologists, economists, sociologists, and other researchers.The proposed methodologies will significantly enrich the techniques of longitudinal survey modeling and broaden the traditional understanding of survey sampling. The proposed research will also strengthen the U.S. federal statistical system by providing survey researchers from several federal agencies (including Census Bureau, the National Center for Health Statistics, the Bureau of Justice Statistics, and the Bureau of Labor Statistics) modern and advanced methods in survey methodology.