DDRIG in DRMS: Measuring Persuasion Without Measuring a Prior Belief: A New Application of Planned Missing Data Techniques

DRMS 中的 DDRIG：在不衡量先验信念的情况下衡量说服力：计划丢失数据技术的新应用

• 批准号: 2242100
• 负责人: David Budescu
• 金额: $ 2.46万
• 依托单位: Fordham University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2242100&HistoricalAwards=false
• 关键词: DDRIG; DRMS; Measuring; Persuasion; Without

Experiments on advice taking typically require a person receiving advice (an “advisee”) express their belief about the topic they are being advised about before receiving the actual advice. Then, after advice is given, the advisee reports a new belief. Researchers can then study the effects of advice by looking at how the advisee’s belief changed. However, there is a potential problem with this setup. Making the advisee explicitly consider their expectation before receiving advice can change its effects, but there is no way to study how the advisee’s belief changes without knowing what they believed beforehand. This research uses cutting edge statistical methods to estimate advisees’ prior beliefs based on other factors that are known about them, allowing researchers to understand the influence of advice under more realistic conditions, where advisees don’t have to directly think about what they believe before being advised. The scientific term for situations where measurement affects subsequent behavioral processes is “measurement reactivity”. This project’s approach to curing this measurement reactivity is to treat advisees’ prior beliefs as missing data. Advances in statistical methods allow researchers to impute missing data with without bias under the right set of circumstances. These methods are typically utilized when data are missing incidentally, but this project will experimentally randomize when data are missing, ensuring the correct conditions for the imputation to work effectively. Because these advisees never directly report their prior beliefs, the researchers can study how advice utilization occurs in the absence of measurement reactivity. This work has important implications for how advisors can help advisees optimize their expertise in many real-life scenarios. The methodological innovation of using a planned missing data experimental design to cure measurement reactivity also has the potential to generalize to other scientific domains where it is a potential confound.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.

实验通常接受建议（“咨询”）的人在接受实际建议之前表达了主题。咨询者的信念在收到建议之前就会改变了期望，但是研究咨询者的信念的变化方式无法改变他们的信念。在被授权的过程中，请考虑“测量反应”由于这些情况从未直接进行反应性，因此缺少对这些情况的反应性。 NSF'Sf'Stututory Mission，并使用基金会的知识分子优点和更广泛的影响标准进行了支持评估。