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dc.contributor.authorBENZEVAL, Michaela
dc.contributor.authorBURTON, Jonathan
dc.contributor.authorCROSSLEY, Thomas F.
dc.contributor.authorFISHER, Paul
dc.contributor.authorGARDINER, Colin
dc.contributor.authorJÄCKLE, Annette
dc.contributor.authorMOORE, Jamie
dc.date.accessioned2021-11-25T13:57:49Z
dc.date.available2021-11-25T13:57:49Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1814/73119
dc.descriptionPublished online: 05 March 2021en
dc.description.abstractUnderstanding Society is the UK’s largest household panel survey. From April 2020, Understanding Society participants were invited to partake in a series of web surveys (the Understanding Society COVID-19 Study) designed to capture higher frequency information during the pandemic. To prevent bias, the COVID-19 Study invites the full range of Understanding Society participants – both those who regularly use the internet and those who do not – to take part and, furthermore, periodically invites a subset of non-respondents to a telephone follow-up. To adjust for bias, a weighting strategy is implemented that takes advantage of the rich background information available from past annual interviews. We examine the efficacy of these bias reduction and bias adjustment measures. We find that both the telephone follow-ups and weighting help to reduce bias, but that inviting those who do not regularly use the internet to the web survey appears to be of little benefit.en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherUnderstanding societyen
dc.relation.ispartofseriesUnderstanding Society Working Paperen
dc.relation.ispartofseries2021/03en
dc.relation.urihttps://www.understandingsociety.ac.uk/research/publications/536631en
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.subjectInformation and communication technologiesen
dc.subjectSurvey methodologyen
dc.subjectHealthen
dc.subjectCOVID 19en
dc.titleHigh frequency online data collection in an annual household panel study : some evidence on bias prevention and bias adjustmenten
dc.typeWorking Paperen
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