Taking Large-Scale Surveys into the Future

对未来进行大规模调查

• 批准号: 2049164
• 负责人: David Cantor
• 金额: $ 97.99万
• 依托单位: Westat Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2049164&HistoricalAwards=false
• 关键词: Taking; Large; Scale; Surveys; into

Society has come to rely on large-scale surveys of human populations. Until recently, in-person surveys have been seen as the ‘gold standard,’ primarily because of their high response rates. However, cooperation with such surveys has been declining dramatically. At the same time, an increasing share of the U.S. population has gained access to the internet, which has given rise to web surveys. Such surveys are much less expensive than in-person ones, are not vulnerable to interruptions related to events like pandemics, and are not subject to errors that interviewers may introduce. At present, however, our understanding of the trade-offs between in-person and web administration for lengthy surveys is not well developed. The project assesses the impact of converting the in-person General Social Survey -- an essential part of the data infrastructure for social science in the United States -- to a state-of-the-art web survey. The results will be of significant value to survey researchers. The project conducts an experimental study of the effects of survey mode and delivery format using the 2022 General Social Survey (GSS) questionnaire. A nationally representative sample of households will be randomly assigned to one of two different versions of the web survey. One version will be a single long instrument. The other version will break up the 90-minute GSS into three parts, asking respondents to complete each module at three separate times. The goal is to reduce respondent burden by breaking up the respondent’s task into more manageable pieces. The web surveys will be administered at approximately the same time as the 2022 in-person GSS. Comparison of the in-person GSS to the long web survey will measure the effect of mode of administration. Comparison of the long versus the modular web surveys will provide a measure of the effects of breaking up the survey into shorter tasks. Analysis will compare the three surveys by: 1) response rates and indicators of non-response bias; 2) indicators of the response process and data quality; 3) GSS demographic, behavioral, and opinion measures; and 4) costs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

社会已经开始依赖对人类人口的大规模调查。直到最近，面对面调查一直被视为“黄金标准”，主要是因为它们的回复率很高。然而，与这类调查的合作一直在急剧下降。与此同时，越来越多的美国人接触到了互联网，这引发了网络调查。这类调查比面对面调查便宜得多，不容易受到与流行病等事件相关的干扰，也不会受到采访者可能引入的错误的影响。然而，目前，我们对面对面管理和网络管理之间对于长时间调查的权衡的理解还不够深入。该项目评估了将面对面的综合社会调查--美国社会科学数据基础设施的重要组成部分--转变为最先进的网络调查的影响。研究结果将对调查研究人员具有重要的价值。该项目利用2022年一般社会调查(GSS)问卷对调查方式和交付格式的影响进行了实验研究。具有全国代表性的家庭样本将被随机分配到网络调查的两个不同版本中的一个。其中一个版本将是单一的长乐器。另一个版本将90分钟的GSS分为三个部分，要求受访者在三个不同的时间完成每个模块。目标是通过将受访者的任务分解为更易于管理的部分来减轻受访者的负担。网络调查将与2022年面对面GSS大致同时进行。面对面GSS与长期网络调查的比较将衡量管理模式的效果。比较长的网络调查和模块化的网络调查将提供将调查分成较短任务的效果的衡量标准。分析将通过以下方面对三项调查进行比较：1)响应率和无响应偏差指标；2)响应过程和数据质量指标；3)GSS人口统计、行为和意见测量；以及4)成本。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。