Shape-Constrained Estimation and Inference for Surveys

该研究项目将为调查从业者提供一类新的工具，以提高调查估计的稳定性和精度。调查是政府、企业和学术界重要的数据来源。然而，在过去十年中，进行调查的费用急剧增加，而回复率却有所下降。本项目开发的新方法将利用“软”或模糊的信息，这些信息通常在许多不同的环境中可用，但不直接使用或仅以“特别”的方式使用。这些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，这项工作将是形状约束在测量环境中的第一次应用。这些新工具对大型调查机构将特别有用，有可能大大提高效率，并得出符合数据用户所期望的质量性质的估计。调查人员将开发用户友好的软件。本研究项目将针对实践中可能遇到的各种不同类型的形状约束开发新的调查估计方法，并使用统计工具来评估形状约束在调查人群中是否成立，并估计估计的精度。形状约束估计将引入几个重要的调查方法领域的实际兴趣，包括估计亚种群，后分层，调整无响应和小面积估计。该研究将产生用于加权约束估计的新的统计算法，用于测量数据形状约束有效性的统计检验方法，以及一类基于形状约束的新的权重校准方法。该项目由方法、测量和统计项目和联邦统计机构联盟支持，作为支持调查和统计方法研究的联合活动的一部分。

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.