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[journal article]

dc.contributor.authorVercruyssen, Aninade
dc.contributor.authorLoosveldt, Geertde
dc.date.accessioned2018-06-11T09:03:11Z
dc.date.available2018-06-11T09:03:11Z
dc.date.issued2017de
dc.identifier.issn1864-3361de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/57554
dc.description.abstractResearchers have been looking for easily accessible and straightforwardly useable paradata and auxiliary data to improve survey data. Lately, there is also attention for the evaluation and validation of this external data, such as the assessment of the quality of interviewer-generated paradata. For these purposes, we investigated how useful Google Street View can be as auxiliary data and whether it allows us to assess the quality of interviewer observations on the houses and neighbourhoods of sample units. Additionally, we test whether Google Maps can inform us about the reachability of sample units and which data can predict non-response better. Although it is rather simple to use Google Maps and Street View in daily life, using it to code auxiliary data for surveys is more challenging than expected. Hence, this paper also offers a thorough discussion of the pitfalls of coding these auxiliary data as well as their current solutions.en
dc.languageende
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.otherauxiliary data; paradata; interviewer observations; survey non-response; Google Street View; Google Mapsde
dc.titleUsing Google Maps and Google Street View to Validate Interviewer Observations and Predict Non-response: A Test Casede
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalSurvey Research Methods
dc.source.volume11de
dc.publisher.countryDEU
dc.source.issue3de
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.subject.thesozprognosisen
dc.subject.thesozAntwortverhaltende
dc.subject.thesozInterviewde
dc.subject.thesozDatengewinnungde
dc.subject.thesozdata qualityen
dc.subject.thesozresponse behavioren
dc.subject.thesozsurvey researchen
dc.subject.thesozinterviewen
dc.subject.thesozdata captureen
dc.subject.thesozPrognosede
dc.subject.thesozUmfrageforschungde
dc.subject.thesozDatenqualitätde
dc.rights.licenceDeposit Licence - Keine Weiterverbreitung, keine Bearbeitungde
dc.rights.licenceDeposit Licence - No Redistribution, No Modificationsen
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10040714
internal.identifier.thesoz10040547
internal.identifier.thesoz10055811
internal.identifier.thesoz10035808
internal.identifier.thesoz10036432
internal.identifier.thesoz10037913
dc.type.stockarticlede
dc.type.documentjournal articleen
dc.type.documentZeitschriftenartikelde
dc.source.pageinfo345-360de
internal.identifier.classoz10105
internal.identifier.journal674
internal.identifier.document32
internal.identifier.ddc300
dc.source.issuetopicUses of Geographic Information Systems Tools in Survey Data Collection and Analysisde
dc.identifier.doihttps://doi.org/10.18148/srm/2017.v11i3.6301
dc.description.pubstatusPublished Versionen
dc.description.pubstatusVeröffentlichungsversionde
internal.identifier.licence3
internal.identifier.pubstatus1
internal.identifier.review1
ssoar.urn.registrationfalsede
internal.check.abstractlanguageharmonizerCERTAIN


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