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).
Verfasserangaben: | Julia C. PostORCiDGND, Fabian ClassORCiDGND, Ulrich KohlerORCiDGND |
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DOI: | https://doi.org/10.18148/srm/2020.v14i2.7755 |
ISSN: | 1864-3361 |
Titel des übergeordneten Werks (Englisch): | Survey research methods |
Verlag: | European Survey Research Association |
Verlagsort: | Duisburg |
Publikationstyp: | Wissenschaftlicher Artikel |
Sprache: | Englisch |
Datum der Erstveröffentlichung: | 02.06.2020 |
Erscheinungsjahr: | 2020 |
Datum der Freischaltung: | 09.01.2023 |
Freies Schlagwort / Tag: | COVID-19; conservative confidence limits; nonresponse bias; prevalence; probability samples; unit nonresponse |
Band: | 14 |
Ausgabe: | 2 |
Seitenanzahl: | 7 |
Erste Seite: | 115 |
Letzte Seite: | 121 |
Organisationseinheiten: | Wirtschafts- und Sozialwissenschaftliche Fakultät / Sozialwissenschaften / Fachgruppe Soziologie |
DDC-Klassifikation: | 3 Sozialwissenschaften / 30 Sozialwissenschaften, Soziologie / 300 Sozialwissenschaften |
Peer Review: | Referiert |
Publikationsweg: | Open Access / Gold Open-Access |
Lizenz (Deutsch): | ![]() |