Unit nonresponse biases in estimates of SARS-CoV-2 prevalence
- Since COVID-19 became a pandemic, many studies are being conducted to get a better understanding of the disease itself and its spread. One crucial indicator is the prevalence of SARS-CoV-2 infections. Since this measure is an important foundation for political decisions, its estimate must be reliable and unbiased. This paper presents reasons for biases in prevalence estimates due to unit nonresponse in typical studies. Since it is difficult to avoid bias in situations with mostly unknown nonresponse mechanisms, we propose the maximum amount of bias as one measure to assess the uncertainty due to nonresponse. An interactive web application is presented that calculates the limits of such a conservative unit nonresponse confidence interval (CUNCI).
Author details: | Julia C. PostORCiDGND, Fabian ClassORCiDGND, Ulrich KohlerORCiDGND |
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DOI: | https://doi.org/10.18148/srm/2020.v14i2.7755 |
ISSN: | 1864-3361 |
Title of parent work (English): | Survey research methods |
Publisher: | European Survey Research Association |
Place of publishing: | Duisburg |
Publication type: | Article |
Language: | English |
Date of first publication: | 2020/06/02 |
Publication year: | 2020 |
Release date: | 2023/01/09 |
Tag: | COVID-19; conservative confidence limits; nonresponse bias; prevalence; probability samples; unit nonresponse |
Volume: | 14 |
Issue: | 2 |
Number of pages: | 7 |
First page: | 115 |
Last Page: | 121 |
Organizational units: | Wirtschafts- und Sozialwissenschaftliche Fakultät / Sozialwissenschaften / Fachgruppe Soziologie |
DDC classification: | 3 Sozialwissenschaften / 30 Sozialwissenschaften, Soziologie / 300 Sozialwissenschaften |
Peer review: | Referiert |
Publishing method: | Open Access / Gold Open-Access |
License (German): | CC-BY-NC - Namensnennung, nicht kommerziell 4.0 International |