Some Issues in Analytic Inference from Complex Surveys

复杂调查分析推理的一些问题

• 批准号: 0922142
• 负责人: Jay Breidt
• 金额: $ 44.79万
• 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: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0922142&HistoricalAwards=false
• 关键词: Some; Issues; Analytic; Inference; Complex

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Surveys represent a key source of data in a wide range of scientific disciplines, and are often an important input in public and corporate decision-making processes. While the primary use of survey data is to describe the population from which the sample was drawn, analysts are increasingly using those data to make inference about statistical models. This use of survey data in model estimation and analysis is referred to as analytic inference for survey data. Survey data producing organizations usually recommend that survey weights be used in all model fitting with survey data, in order to account for the sampling design and the post-sampling adjustments. This often significantly complicates the work of data analysts, in large part because the effect of survey weighting in analytic inference is still incompletely understood. This research will explore some long-standing open issues in analytic inference for surveys. First, within the survey-weighted mode of inference, the PIs will investigate improved variance estimation methods and distributional theory. Second, they will evaluate a number of alternatives to survey weighting in model fitting and inference. This research will advance the state of knowledge in how to properly conduct analytic inference for survey data by bringing together concepts, methods and approaches from survey statistics and other areas of statistics. Ultimately, it will enhance the ability of data analysts to conduct perform analytic inference for survey data. Because of the importance of survey data collection and analysis in so many disciplines, the results of the proposed research will be widely applicable.

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。调查代表了广泛的科学学科数据的关键来源，通常是公共和企业决策过程中的重要投入。虽然调查数据的主要用途是描述从中抽取样本的人口，但分析人员越来越多地使用这些数据对统计模型进行推断。在模型估计和分析中使用调查数据被称为调查数据的分析推断。 调查数据产生组织通常建议在所有与调查数据拟合的模型中使用调查权重，以说明抽样设计和抽样后调整。 这通常会使数据分析师的工作变得非常复杂，这在很大程度上是因为分析推断中调查加权的效果仍然没有完全理解。 本研究将探讨一些长期存在的开放性问题，在分析推理的调查。 首先，在调查加权推理模式中，PI将研究改进的方差估计方法和分布理论。其次，他们将评估一些替代调查加权模型拟合和推理。这项研究将通过汇集调查统计和其他统计领域的概念、方法和途径，促进对调查数据进行正确分析推断的知识水平。最终，它将提高数据分析师对调查数据进行分析推理的能力。 由于调查数据的收集和分析在许多学科中的重要性，因此所提出的研究结果将具有广泛的适用性。