On Area Specific Uncertainty Measures in Small Area Estimation

小区域估计中区域特定不确定性测度

• 批准号: 1534413
• 负责人: Parthasarathi Lahiri
• 金额: $ 22万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1534413&HistoricalAwards=false
• 关键词: Area; Specific; Uncertainty; Measures; Small

This research project will investigate new ways to evaluate small area estimates. There is a growing demand for statistics related to small geographic areas. These small area estimates are used by policymakers to assess the well-being of a nation, develop public policies, and allocate funds in various government programs. Users of these estimates generally are interested in understanding the uncertainty that is relevant to their specific small area as opposed to average uncertainty measures. However, most of the uncertainty measures proposed in the literature for small area estimates are not area specific in the study variable. This project will develop new uncertainty measures and examine their effectiveness in measuring area specific uncertainty in the study variable. A focus of the project will be on the mentoring of students and early-career researchers. The new research results will be incorporated into both a graduate course and a short course on small area estimation. Software will be developed to implement the new techniques and will be made publicly available.This research project will examine the versatility of the adjusted maximum likelihood method, already found useful in certain small area problems, in obtaining reliable uncertainty measures of the estimates that are small area specific in the study variable. The investigator will conduct a design-based simulation and real data analysis in order to understand the robust properties of the proposed uncertainty measures. Data for evaluating the new methodology will be drawn from census and household survey data. The project is supported by the Methodology, Measurement, and Statistics Program and a consortium of federal statistical agencies as part of a joint activity to support research on survey and statistical methodology.

本研究项目将探讨评估小面积估计的新方法。 对与小地理区域有关的统计数据的需求日益增加。 决策者使用这些小面积估计来评估一个国家的福祉，制定公共政策，并在各种政府计划中分配资金。 这些估计的用户通常有兴趣了解与其特定小区域相关的不确定性，而不是平均不确定性度量。 然而，大多数的不确定性措施，在文献中提出的小面积估计是不特定的研究变量。 本项目将开发新的不确定性测量方法，并检查其在测量研究变量中特定区域不确定性方面的有效性。 该项目的重点将是对学生和早期职业研究人员的指导。 新的研究成果将纳入研究生课程和关于小面积估计的短期课程。 将开发软件以实施新技术并将向公众提供，本研究项目将审查已发现在某些小区域问题中有用的调整最大似然法的多功能性，以获得研究变量中特定于小区域的估计数的可靠不确定性计量。 研究人员将进行基于设计的模拟和真实的数据分析，以了解拟议的不确定性措施的稳健性。 评价新方法的数据将来自人口普查和住户调查数据。 该项目得到了方法、测量和统计方案以及联邦统计机构联合会的支持，作为支持调查和统计方法研究的联合活动的一部分。