Narayanan, Martina;
Dodgeon, Brian;
Katsoulis, Michail;
Ploubidis, George;
Silverwood, Richard;
(2024)
How to mitigate selection bias in COVID-19 surveys: evidence from five national cohorts.
European Journal of Epidemiology
, 39
pp. 1221-1227.
10.1007/s10654-024-01164-y.
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Abstract
Non-response to surveys is a common problem; even more so during the COVID-19 pandemic with social distancing measures challenging data collection. As respondents often differ from non-respondents, this can introduce bias. The goal of the current study was to see if we can reduce bias and restore sample representativeness in a series of COVID-19 surveys embedded within five UK cohort studies by using the rich data available from previous waves of data collection. Three surveys were conducted during the pandemic across five UK cohorts: National Survey of Health and Development (NSHD, born 1946), 1958 National Child Development Study (NCDS), 1970 British Cohort Study (BCS70), Next Steps (born 1989-90) and Millennium Cohort Study (MCS, born 2000-02). Response rates in the COVID-19 surveys were lower compared to previous waves, especially in the younger cohorts. We identified bias due to systematic non-response in several variables, with more respondents in the most advantaged social class and among those with higher childhood cognitive ability. Making use of the rich data available pre-pandemic in these longitudinal studies, the application of non-response weights and multiple imputation was successful in reducing bias in parental social class and childhood cognitive ability, nearly eliminating it for the former. Surveys embedded within existing cohort studies offer a clear advantage over cross-sectional samples collected during the pandemic in terms of their ability to mitigate selection bias. This will enhance the quality and reliability of future research studying the medium and long-term effects of the pandemic.
| Type: | Article |
|---|---|
| Title: | How to mitigate selection bias in COVID-19 surveys: evidence from five national cohorts |
| Location: | Netherlands |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s10654-024-01164-y |
| Publisher version: | https://doi.org/10.1007/s10654-024-01164-y |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | COVID-19, Longitudinal data, Missing data, Multiple imputation, Non-response, Weighting |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Social Research Institute UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine > MRC Unit for Lifelong Hlth and Ageing |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10201605 |
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