Shape-Constrained Estimation and Inference for Surveys

调查的形状约束估计和推断

• 批准号: 1533804
• 负责人: Mary Meyer
• 金额: $ 50万
• 依托单位: Colorado State University
• 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: 2015-09-15 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1533804&HistoricalAwards=false
• 关键词: Shape; Constrained; Estimation; Inference; Surveys

This research project will provide a new class of tools for survey practitioners to improve the stability and precision of survey estimates. Surveys represent a key source of data for government, business, and academics. The cost of conducting surveys has increased dramatically during the last decade, however, while response rates have declined. The new methods developed by this project will take advantage of "soft" or vague information often available in practice in many different contexts but not directly used or used in only "ad hoc" ways. This information is referred to as "shape constraints" in statistics. The new shape-constrained survey estimation tools will represent an important advance in design-based estimation, which continues to be the primary approach used in large-scale government surveys. At the same time, this work will be the first application of shape constraints in the survey context. The new tools will be especially useful for large-scale survey agencies and have the potential to lead to considerably improved efficiency and to result in estimates that satisfy the qualitative properties expected by data users. The investigators will develop user-friendly software.This research project will develop new survey estimation methods for a variety of different types of shape constraints that can be encountered in practice, together with statistical tools to assess whether the shape constraint holds in the survey population and to estimate the precision of the estimates. Shape-constrained estimation will be introduced in several important survey methodological areas of practical interest, including in estimation for sub-populations, post-stratification, adjusting for nonresponse and small area estimation. The research will result in new statistical algorithms for weighted constrained estimation, in statistical testing methods for the validity of the shape constraints for survey data, and in a new class of weight calibration methods that are based on shape constraints. 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.

这项研究项目将为调查从业人员提供一种新的工具，以提高调查估计的稳定性和准确性。 调查是政府、企业和学术界的重要数据来源。 然而，在过去十年中，进行调查的费用急剧增加，而答复率却下降了。 本项目开发的新方法将利用在许多不同情况下实际上常常可以获得但不直接使用或仅以“临时”方式使用的“软”或模糊信息。 该信息在统计学中被称为“形状约束”。 新的形状约束调查估计工具将代表基于设计的估计的一个重要进步，这仍然是大规模政府调查中使用的主要方法。 同时，这项工作将是第一个应用程序的形状约束的调查背景下。 这些新工具对大型调查机构特别有用，有可能大大提高效率，并产生符合数据用户预期的质量特性的估计数。 研究人员将开发方便用户的软件，该研究项目将开发新的调查估计方法，用于实际中可能遇到的各种不同类型的形状限制，以及统计工具，以评估形状限制是否适用于调查人群，并估计估计的精度。 形状约束估计将被引入几个重要的调查方法领域的实际利益，包括估计亚人群，分层后，调整无响应和小面积估计。 这项研究将导致新的统计算法加权约束估计，在统计测试方法的有效性的形状约束的调查数据，并在一类新的重量校准方法，是基于形状约束。 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。