Collaborative research: Topics in Small Area Estimation

合作研究：小区域估计主题

• 批准号: 0318184
• 负责人: Tapabrata Maiti
• 金额: $ 16万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-15 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0318184&HistoricalAwards=false
• 关键词: Collaborative; research; Topics; Small; Area

The term "small area" or "local area" usually refers to a small geographic area, such as a county, municipality, a census tract, or a school district. It can also refer to socio-demographic domains, such as a specific age-sex-race group within a large geographic area. Small area estimation has become a topic of growing importance in recent years because of the need for reliable small area estimates by many agencies, both public and private, for making useful policy decisions. This project is aimed at addressing several important aspects of small area estimation. One basic question to address in this context is how to use the survey weights (usually inverses of the selection probabilities of the different units in the population) in conjunction with models to arrive at meaningful small area estimators. While many exclusive model-based small area estimators have been proposed, design-assisted model-based small area estimators have been very sparse. The goal is to obtain such estimators for a very general class of distributions. The method will be used to find the proportion and the number of poor school-age children in different counties of the United States. This is a very important problem for many Federal agencies, especially for the Bureau of the Census. Another aspect of this research is to obtain small area estimates by combining results from two or more surveys designed to estimate the same quantity of interest. A typical application of this procedure consists of combining data based on the Current Population Survey (CPS) and the newly introduced American Community Survey (ACS) of the Bureau of the Census. The ACS is intended to replace the decennial census long form in the year 2010. Finally, Bayesian methods will be developed for detecting outliers in finite population sampling, especially in the context of small area estimation.The broader impact of this research is that it aims to achieve an interface between survey methodology and survey practice. As an immediate example, the research findings have direct bearing on small area income and poverty estimation as well as small area estimation by combining estimates from two surveys such as the CPS and the ACS. The findings also should be of interest to staff at the National Center for Health Statistics who are interested in estimating the proportion of uninsured people of different ethnicities, proportion of people under Medicaid, and so on.

“小区域”或“本地”一词通常是指小型地理区域，例如县，市政当局，人口普查区或学区。 它还可以参考社会人口统计领域，例如大型地理区域内的特定年龄性别群体。 近年来，由于许多公共和私人机构需要可靠的小面积估算，近年来，近年来，小面积估算已成为越来越重要的话题。 该项目旨在解决小面积估计的几个重要方面。 在这种情况下要解决的一个基本问题是如何使用调查权重（通常是人口中不同单位的选择概率的倒置）与模型结合使用以达到有意义的小面积估计器。尽管已经提出了许多基于模型的小区域估计器，但基于设计的基于设计的小区域估计器非常稀疏。目的是获得非常一般的分布类别的估计量。 该方法将用于查找美国不同县的贫困学龄儿童的比例和数量。 对于许多联邦机构来说，这是一个非常重要的问题，尤其是对于人口普查局而言。 这项研究的另一个方面是通过结合旨在估计相同兴趣的两个或多个调查的结果来获得较小的面积估计。 该程序的典型应用包括基于当前人口调查（CPS）和普查局新引入的美国社区调查（ACS）组合。 ACS旨在替代2010年的十年期间人口普查形式。最后，将开发贝叶斯方法来检测有限种群采样中的异常值，尤其是在小面积估计的背景下。这项研究的更广泛的影响是，它旨在在调查方法和调查实践之间实现界面。 例如，研究结果直接取决于小面积的收入和贫困估计以及小面积估计，通过结合两项调查（例如CPS和ACS）的估计。 国家卫生统计中心的工作人员也应该感兴趣，他们有兴趣估计具有不同种族的未保险人的比例，医疗补助以下的人的比例等等。