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[journal article]

dc.contributor.authorSiddiqui, Nadiade
dc.contributor.authorBoliver, Vikkide
dc.contributor.authorGorard, Stephende
dc.date.accessioned2019-01-14T13:28:10Z
dc.date.available2019-01-14T13:28:10Z
dc.date.issued2019de
dc.identifier.issn2183-2803de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/61035
dc.description.abstractLongitudinal social surveys are widely used to understand which factors enable or constrain access to higher education. One such data resource is the Next Steps survey comprising an initial sample of 16,122 pupils aged 13-14 attending English state and private schools in 2004, with follow up annually to age 19-20 and a further survey at age 25. The Next Steps data is a potentially rich resource for studying inequalities of access to higher education. It contains a wealth of information about pupils' social background characteristics - including household income, parental education, parental social class, housing tenure and family composition - as well as longitudinal data on aspirations, choices and outcomes in relation to education. However, as with many longitudinal social surveys, Next Steps suffers from a substantial amount of missing data due to item non-response and sample attrition which may seriously compromise the reliability of research findings. Helpfully, Next Steps data has been linked with more robust administrative data from the National Pupil Database (NPD), which contains a more limited range of social background variables, but has comparatively little in the way of missing data due to item non-response or attrition. We analyse these linked datasets to assess the implications of missing data for the reliability of Next Steps. We show that item non-response in Next Steps biases the apparent socioeconomic composition of the Next Steps sample upwards, and that this bias is exacerbated by sample attrition since Next Steps participants from less advantaged social backgrounds are more likely to drop out of the study. Moreover, by the time it is possible to measure access to higher education, the socioeconomic background variables in Next Steps are shown to have very little explanatory power after controlling for the social background and educational attainment variables contained in the NPD. Given these findings, we argue that longitudinal social surveys with much missing data are only reliable sources of data on access to higher education if they can be linked effectively with more robust administrative data sources. This then raises the question - why not just use the more robust datasets?de
dc.languageende
dc.subject.ddcSoziologie, Anthropologiede
dc.subject.ddcSociology & anthropologyen
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.otherNext Steps; missing data; sampling biasde
dc.titleReliability of Longitudinal Social Surveys of Access to Higher Education: The Case of Next Steps in Englandde
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.identifier.urlhttps://www.cogitatiopress.com/socialinclusion/article/view/1631de
dc.source.journalSocial Inclusion
dc.source.volume7de
dc.publisher.countryMISC
dc.source.issue1de
dc.subject.classozBildungs- und Erziehungssoziologiede
dc.subject.classozSociology of Educationen
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.subject.thesozHochschulbildungde
dc.subject.thesozuniversity level of educationen
dc.subject.thesozHochschulzugangde
dc.subject.thesozuniversity admissionen
dc.subject.thesozGroßbritanniende
dc.subject.thesozGreat Britainen
dc.subject.thesozUngleichheitde
dc.subject.thesozinequalityen
dc.subject.thesozsozioökonomische Faktorende
dc.subject.thesozsocioeconomic factorsen
dc.subject.thesozsoziale Herkunftde
dc.subject.thesozsocial backgrounden
dc.subject.thesozHaushaltseinkommende
dc.subject.thesozhousehold incomeen
dc.subject.thesozDatengewinnungde
dc.subject.thesozdata captureen
dc.subject.thesozLängsschnittuntersuchungde
dc.subject.thesozlongitudinal studyen
dc.subject.thesozAntwortverhaltende
dc.subject.thesozresponse behavioren
dc.subject.thesozDatenqualitätde
dc.subject.thesozdata qualityen
dc.rights.licenceCreative Commons - Namensnennung 4.0de
dc.rights.licenceCreative Commons - Attribution 4.0en
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10039336
internal.identifier.thesoz10046740
internal.identifier.thesoz10042102
internal.identifier.thesoz10041153
internal.identifier.thesoz10053635
internal.identifier.thesoz10046548
internal.identifier.thesoz10041647
internal.identifier.thesoz10040547
internal.identifier.thesoz10050423
internal.identifier.thesoz10035808
internal.identifier.thesoz10055811
dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo80-89de
internal.identifier.classoz10208
internal.identifier.classoz10105
internal.identifier.journal786
internal.identifier.document32
internal.identifier.ddc301
internal.identifier.ddc300
dc.source.issuetopicInequalities in Access to Higher Education: Methodological and Theoretical Issuesde
dc.identifier.doihttps://doi.org/10.17645/si.v7i1.1631de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence16
internal.identifier.pubstatus1
internal.identifier.review1
internal.dda.referencehttps://www.cogitatiopress.com/socialinclusion/oai/@@oai:ojs.cogitatiopress.com:article/1631
ssoar.urn.registrationfalsede


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