Statistical methods for survey data in the social sciences

社会科学调查数据的统计方法

• 批准号: RGPIN-2016-03688
• 负责人: Thompson, Mary
• 金额: $ 1.44万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=677050
• 关键词: Statistical; methods; survey; data; social

I will pursue research in three areas related to complex survey methodology, with common themes of latent variables and linkages.******The first area is latent variable modeling in the complex survey context. Latent variables are hypothesized but unobservable variables, giving structure and meaning to a statistical model. For example, a random effect in a mixed or multilevel model is often regarded as latent; structural equation models use latent constructs to explain the relationships among observed psychometric variables; in item response theory (IRT) models used in educational testing, item difficulty and test taker ability are often taken to be latent. I will extend previous work on multilevel models, and apply estimating function approaches to robust estimation of latent variable model parameters. ******The second area is the analysis of data from sampling on social networks. A network is a collection of nodes, some of which are joined by links. My collaborators and I have worked on “patchwork sampling”, wherein links from a probability sample of nodes are followed to a certain distance, with multiple inclusions recorded. Applications include a collaboration network of scholars; a network of telecom customers who call each other; or a contact network with links for disease transmission. I plan to extend our preliminary work to the estimation of connectivity and complex dependences.******The third area is multi-frame methods and data linkage. A frame is a database or list of members of a population, from which samples can be drawn. The members may or may not be contactable, and the frame may or may not be “rich” in the sense of providing useful information about the members. Typically the databases or samples overlap considerably, and proper linkage of the records can make analysis more efficient. If the identifiers are not unique, or if erroneous or missing identifiers make linkage uncertain, it is desirable to have techniques for automatic estimation of links. I will explore relationships among traditional multi-frame methods, record linkage methods, and sampling using linkage information. ******The work on latent variable models addresses two problems facing social science researchers: the need for accurate multi-level analysis when the sampling design is structurally informative and/or the models are non-normal; and the need for robustly estimable latent variable models. The rest of the proposal concerns trends in survey methods arising from the increasing availability of vast amounts of rich and linkable data on people and establishments, and the increasing difficulty of carrying out designed studies such as traditional sample surveys due to non-response. The list of potential application areas includes not only official statistics and social research methods but also forensic uses such as detection of unusual activity in communications traffic.*** Supervision of graduate students will be included in each area.**

我将在与复杂调查方法相关的三个领域进行研究，共同主题是潜在变量和联系。******第一个领域是复杂调查背景下的潜在变量建模。潜在变量是假设的但不可观察的变量，为统计模型提供结构和意义。例如，混合或多层模型中的随机效应通常被认为是潜在的；结构方程模型使用潜在构念来解释观察到的心理测量变量之间的关系；在教育测试中使用的项目反应理论（IRT）模型中，项目难度和考生能力往往被认为是潜在的。我将扩展先前在多层模型上的工作，并将估计函数方法应用于潜在变量模型参数的鲁棒估计。******第二个领域是对社交网络抽样数据的分析。网络是节点的集合，其中一些节点通过链路连接起来。我和我的合作者研究了“拼接采样”，其中从节点的概率样本中链接到一定距离，并记录多个内含物。应用包括学者合作网络；互相打电话的电信客户网络；或者是一个具有疾病传播环节的接触网络。我计划将我们的初步工作扩展到连通性和复杂依赖性的估计。******第三个领域是多帧方法和数据链接。框架是总体成员的数据库或列表，从中可以抽取样本。成员可以是可接触的，也可以不是可接触的，从提供有关成员的有用信息的意义上说，框架可以是“丰富的”，也可以不是“丰富的”。通常，数据库或样本重叠很大，记录的适当链接可以使分析更有效。如果标识符不是唯一的，或者错误的或缺少的标识符使链接不确定，则需要有自动估计链接的技术。我将探讨传统的多帧方法、记录链接方法和使用链接信息采样之间的关系。******关于潜在变量模型的工作解决了社会科学研究人员面临的两个问题：当抽样设计具有结构信息性和/或模型是非正态时，需要准确的多层次分析；并且需要鲁棒可估计的潜变量模型。提案的其余部分涉及调查方法的趋势，这是由于关于人员和机构的大量丰富和可联系的数据越来越多，以及由于没有答复，进行诸如传统抽样调查等设计好的研究越来越困难。潜在的应用领域不仅包括官方统计和社会研究方法，还包括法医用途，如检测通信流量中的异常活动。***研究生的监督将包括在每个区域