开展新冠肺炎疫情时代全国调查

Conducting data collection for national surveys during a crisis is not unusual. 飓风, 地震, 森林大火, 内乱, and other emergency situations have posed challenges to data collection in geographically localized areas at different times. But how do researchers tackle the challenges of conducting a nationally representative survey during a health pandemic? “The situation with this COVID-19 pandemic is especially unpredictable,” notes 蕾拉Mohadjer, Ph.D., 趣赢平台 Vice President and Associate Director for Statistics and 评价科学. “So, we continually plan for different scenarios and quick turnaround strategies that rely on the fundamentals of statistical research and survey methodology.”

Proactive planning is key to conducting survey research especially at this time. 趣赢平台 is in ongoing communication with our clients on strategies to move forward on in-person data collection. “We’re continually taking the temperature of projects as we move forward and continually planning for different contingencies depending on the expected timing of returning to the field,”博士解释说. Mohadjer.

调查模式的改变

Many surveys that were conducted in person have transitioned to telephone or web surveys. “We’re studying any mode changes to see if there is a mode change effect. If so, we have developed plans for adjusting the final samples to minimize the impact of mode change. 也, 对于一些调查, combining data from the pre- and post-COVID period may not be justifiable,博士警告说. Mohadjer. “This is true for surveys where the pre-COVID and post-COVID respondents are coming from different parts of the country. 在某些情况下, 有关的统计数字, 像就业状况, 从疫情前到疫情后发生了巨大变化. We have developed special sampling procedures that create a bridge between the pre- and post-COVID samples to best deal with these kinds of situations.”

回应率是关键

Getting high response rates is critical no matter how the survey is conducted, but the U.S. Census Bureau and the Bureau of Labor Statistics have already raised concerns about lower response rates for their large surveys. “We need to prepare for a similar impact on response rates in surveys we conduct,”博士指出. Mohadjer. “在某些情况下, it is a matter of working with survey methods specialists to devise ways to improve response rates. We are also mitigating this risk by doing extensive analyses to assess bias due to nonresponse, and to adjust the resulting sample to reduce bias in outcome statistics by applying various sample weighting adjustments, 像基准测试.”

Lower response rates not only impact the representativeness of the sample but also result in a smaller sample size for the survey. “缓解这一问题的一种方法是，”他说. Mohadjer解释说, “is to split the selected sample into a main sample and many smaller random samples, 主样本首先被释放到字段中. 在整个数据收集过程中, 趣赢平台 monitors data collection activity in real time and is prepared to release new samples if need be. We can implement this seamless process because of our integrated network of survey statisticians, 调查操作人员, 现场数据收集监督, 和分析人员. If the original sample released to data collectors is not providing enough responses,”她继续, “我们将公布另一个不同家庭的子样本, maintaining random representativeness of the survey at the same time as aiming to achieve the desired sample size.”

处理不可预测的变化

Part of the planning for surveying during a pandemic is to also man年龄 potential pauses in data collection either in local hot spots or across the country. “We have to be cognizant and flexible as different parts of the country are affected at different times, 以及我们如何减少收集样本的偏差,”博士指出. Mohadjer. 趣赢平台 has established procedures to minimize disruption and risk by developing data collection plans with quick turnarounds, 暂停后快速重启数据收集, 或者在需要的时候改变数据收集的方式.

专注于高质量的数据收集

“在趣赢平台, we put priority on the quality of the data collected during the pandemic, and also prepare for correcting for any potential bias through sample adjustment and weighting,“继续博士. Mohadjer. “We share the methods that are working effectively across different data collection projects, 这有利于所有韦斯特项目和客户.”

统计学家还利用其他工具, 像数据链接, where data sources are linked to augment or replace missing data as a result of the pandemic, and data science techniques such as machine learning to quickly gather large amount of data and conduct various analyses either using paradata or external data sources for various needs.

The rapidly evolving nature of the COVID-19 pandemic requires researchers to quickly adapt and be nimble in meeting the challenges of sampling and data collection. 尽管挑战可能看起来令人生畏, 创新使用统计工具和技术, 包括适应性调查方法, are instrumental in achieving the quality and integrity of the data.