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[journal article]

dc.contributor.authorCornesse, Carinade
dc.contributor.authorFelderer, Barbarade
dc.contributor.authorFikel, Marinade
dc.contributor.authorKrieger, Ulrichde
dc.contributor.authorBlom, Annelies G.de
dc.date.accessioned2023-02-08T12:58:49Z
dc.date.available2023-02-08T12:58:49Z
dc.date.issued2022de
dc.identifier.issn1552-8286de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/85098
dc.description.abstractOnce recruited, probability-based online panels have proven to enable high-quality and high-frequency data collection. In ever faster-paced societies and, recently, in times of pandemic lockdowns, such online survey infrastructures are invaluable to social research. In absence of email sampling frames, one way of recruiting such a panel is via postal mail. However, few studies have examined how to best approach and then transition sample members from the initial postal mail contact to the online panel registration. To fill this gap, we implemented a large-scale experiment in the recruitment of the 2018 sample of the German Internet Panel (GIP) varying panel recruitment designs in four experimental conditions: online-only, concurrent mode, online-first, and paper-first. Our results show that the online-only design delivers higher online panel registration rates than the other recruitment designs. In addition, all experimental conditions led to similarly representative samples on key socio-demographic characteristics.de
dc.languageende
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.otherconcurrent mode; mixed-mode; offline recruitment; online panels; probability sampling; push-to-web; German Internet Panel (GIP)de
dc.titleRecruiting a Probability-Based Online Panel via Postal Mail: Experimental Evidencede
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.identifier.urllocalfile:/var/tmp/crawlerFiles/deepGreen/19891b418e0c452485825b41b103d53a/19891b418e0c452485825b41b103d53a.pdfde
dc.source.journalSocial Science Computer Review
dc.source.volume40de
dc.publisher.countryUSAde
dc.source.issue5de
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.subject.thesozUmfrageforschungde
dc.subject.thesozsurvey researchen
dc.subject.thesozDatengewinnungde
dc.subject.thesozdata captureen
dc.subject.thesozOnline-Befragungde
dc.subject.thesozonline surveyen
dc.subject.thesozPanelde
dc.subject.thesozpanelen
dc.subject.thesozStichprobede
dc.subject.thesozsampleen
dc.subject.thesozRepräsentativitätde
dc.subject.thesozrepresentativityen
dc.subject.thesozWahrscheinlichkeitde
dc.subject.thesozprobabilityen
dc.subject.thesozpostalische Befragungde
dc.subject.thesozmail surveyen
dc.identifier.urnurn:nbn:de:0168-ssoar-85098-0
dc.rights.licenceCreative Commons - Namensnennung 4.0de
dc.rights.licenceCreative Commons - Attribution 4.0en
ssoar.contributor.institutionGESISde
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10040714
internal.identifier.thesoz10040547
internal.identifier.thesoz10037911
internal.identifier.thesoz10054018
internal.identifier.thesoz10037472
internal.identifier.thesoz10056653
internal.identifier.thesoz10061922
internal.identifier.thesoz10037912
dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo1259-1284de
internal.identifier.classoz10105
internal.identifier.journal645
internal.identifier.document32
internal.identifier.ddc300
dc.identifier.doihttps://doi.org/10.1177/08944393211006059de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence16
internal.identifier.pubstatus1
internal.identifier.review1
ssoar.wgl.collectiontruede
internal.dda.referencecrawler-deepgreen-188@@19891b418e0c452485825b41b103d53a


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