人口健康研究中的非代表性：来自一项 COVID-19 抗体研究的证据
Nonrepresentativeness in Population Health Research: Evidence from a COVID-19 Antibody Study
AER: Insights · 2024 · [{"name": "Deniz Dutz", "affiliation": ["University of Chicago"]}, {"name": "Michael Greenstone", "affiliation": ["University of Chicago"]}, {"name": "Alı Hortaçsu", "affiliation": ["University of Chicago"]}, {"name": "Santiago Lacouture", "affiliation": ["University of Chicago"]}, {"name": "Magne Mogstad", "affiliation": ["University of Chicago"]}, {"name": "Azeem M. Shaikh", "affiliation": ["University of Chicago"]}, {"name": "Alexander Torgovitsky", "affiliation": ["University of Chicago"]}, {"name": "Winnie van Dijk", "affiliation": ["Yale University"]}]
中文摘要
我们分析了一项采用随机参与激励的 COVID-19 血清学研究中的代表性问题。我们发现，当激励较低时，不同种族和收入群体之间存在较大的参与差距。高激励提高了所有群体的参与率，但对代表性不足群体的提升更大。高激励恢复了种族和收入方面的代表性，也恢复了可能与血清阳性率相关的健康变量方面的代表性，例如未参保率、住院率以及一个综合 COVID-19 风险指数。（JEL C83, I11, I14, J15）
Abstract
We analyze representativeness in a COVID-19 serological study with randomized participation incentives. We find large participation gaps by race and income when incentives are lower. High incentives increase participation rates for all groups but increase them more among under-represented groups. High incentives restore representativeness on race and income and also on health variables likely to be correlated with seropositivity, such as the uninsured rate, hospitalization rates, and an aggregate COVID-19 risk index. (JEL C83, I11, I14, J15)