Responsive Design for Random Digit Dial Surveys Using Auxiliary Survey Process Data and Contextual Data

使用辅助调查过程数据和上下文数据的随机数字拨号调查的响应式设计

• 批准号: 0719253
• 负责人: Sunghee Lee
• 金额: $ 9万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0719253&HistoricalAwards=false
• 关键词: Responsive; Design; Random; Digit; Dial

This study develops a framework for a tailored random digit dial (RDD) telephone survey design that responds to findings from nonresponse bias studies. The lack of data for nonrespondents, a major challenge in RDD nonresponse studies, is overcome by using two types of data available regardless of response behavior - paradata and contextual data. Paradata are data created by the survey process itself and include the history of all calls made to each sampled number (e.g., number of calls placed, calling dates and times) and the survey design features used for each number (e.g., advance letter, monetary incentives, refusal conversion). Contextual data come from external sources (e.g., decennial census data) and are created by linking the geographic identifier (e.g., census tract, ZIP code) of all sampled telephone numbers to the external data at the corresponding geographic level. These data include various characteristics of the corresponding location, such as demographics and socio-economics, which are assumed to approximate the characteristics of individuals residing in that location. The study regards survey response behaviors as a stochastic process influenced simultaneously by the traits of the sample, the survey features, situational circumstances, and the perceived importance of these factors. Response behavior is modeled with variables in the paradata and contextual data and their interactions. The fitted model is used to predict how response behaviors change given hypothetical calling schedules and survey design features, allowing design tailoring for any subsequent surveys. An estimate of a bias indicator can be calculated for respondents and nonrespondents separately. The magnitude of nonresponse bias can be diagnosed by comparing these estimates.Survey data are a vital source for quantifiable information about the population and are widely used by government agencies, policy makers, and social, political, and health science researchers. Advancing the current RDD survey practice is important given the popularity of these surveys in spite of ever-decreasing response rates. This study will provide a new design framework that takes a holistic approach to nonresponse and incorporates the understandings of nonresponse. The major element of the design tailoring is that it aims to increase response rates and decrease potential nonresponse bias. The results of this study will help organizations conducting RDD surveys improve their design process. The research 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.

这项研究开发了一个量身定制的随机数字拨盘（RDD）电话调查设计的框架，该设计对无响应偏见研究的发现做出了反应。 通过使用两种可用的数据，无论响应行为如何 - paradata和上下文数据，都可以克服非响应的数据，这是RDD无反应研究中的主要挑战。 PARADATA是由调查过程本身创建的数据，包括对每个采样数字进行的所有呼叫的历史记录（例如，呼叫数量，呼叫日期和时间）以及每个数字使用的调查设计功能（例如，预先信函，货币激励措施，拒绝转换）。 上下文数据来自外部来源（例如，十年型人口普查数据），是通过将所有采样电话号码的地理标识符（例如，人口普查区域，邮政编码，邮政编码）链接到相应地理级别的外部数据而创建的。 这些数据包括相应位置的各种特征，例如人口统计学和社会经济学，假定这些特征可以近似居住在该位置的个人的特征。 该研究将调查响应行为视为一种随机过程，同时受样本特征，调查特征，情境环境以及这些因素的感知重要性的影响。 响应行为是用术语中的变量和上下文数据及其相互作用建模的。 拟合模型用于预测假设的调用时间表和调查设计功能如何改变响应行为，从而为任何后续的调查量身定制设计。 可以分别针对受访者和非响应者计算偏差指标的估计值。 可以通过比较这些估计值来诊断非反应偏见的大小。调查数据是有关人口的可量化信息的重要来源，并且由政府机构，政策制定者以及社会，政治和健康科学研究人员广泛使用。 鉴于这些调查的普及，尽管响应率不断降低，但推进当前的RDD调查实践很重要。 这项研究将提供一个新的设计框架，该框架采用了无反应的整体方法，并结合了对无响应的理解。 设计裁缝的主要要素是它旨在提高响应率并减少潜在的无响应偏差。 这项研究的结果将帮助进行RDD调查的组织改善其设计过程。 这项研究得到了方法，测量和统计计划以及联邦统计机构的联盟的支持，作为支持调查和统计方法研究的共同活动的一部分。