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dc.contributor.authorStark, Tobias H.de
dc.contributor.authorStocké, Volkerde
dc.date.accessioned2024-02-23T07:39:47Z
dc.date.available2024-02-23T07:39:47Z
dc.date.issued2022de
dc.identifier.issn0378-8733de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/92401
dc.description.abstractEgocentric network studies and many general population surveys rely on proxy reports about network contacts of study participants that are asked in name interpreter questions. A central concern is the extent to which proxy reports match the answers these contacts would give themselves if they would be directly interviewed. Based on the theory of survey satisficing, the present research proposes a theoretical framework that allows predicting when proxy reports are likely to match self-reports. Congruence is higher if respondents possess the motivation and ability to answer a proxy question effortfully, and if the task is not too difficult. Moreover, the theory of survey satisficing states that motivation, abilities, and task difficulty are not independent of each other, which provides an explanation for inconsistent findings in the literature. Results from two egocentric network studies study among German adults (N = 756) and among Dutch middle school students (N = 679), in which network contacts were also interviewed, are in line with these hypotheses. Design recommendations for egocentric network studies are provided.de
dc.languageende
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.otheregocentric network study; proxy reporting; congruence; name interpreter question; survey satisficing; ZIS 136de
dc.titleReprint of: Predicting data quality of proxy reports in egocentric network studiesde
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalSocial Networks
dc.source.volume69de
dc.publisher.countryNLDde
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.subject.thesozNetzwerkanalysede
dc.subject.thesoznetwork analysisen
dc.subject.thesozDatenqualitätde
dc.subject.thesozdata qualityen
dc.subject.thesozNetzwerkde
dc.subject.thesoznetworken
dc.subject.thesozBefragungde
dc.subject.thesozsurveyen
dc.subject.thesozKontaktde
dc.subject.thesozcontacten
dc.identifier.urnurn:nbn:de:0168-ssoar-92401-2
dc.rights.licenceCreative Commons - Namensnennung 4.0de
dc.rights.licenceCreative Commons - Attribution 4.0en
ssoar.contributor.institutionFDBde
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10053147
internal.identifier.thesoz10055811
internal.identifier.thesoz10053141
internal.identifier.thesoz10037910
internal.identifier.thesoz10049667
dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo251-262de
internal.identifier.classoz10105
internal.identifier.journal2382
internal.identifier.document32
internal.identifier.ddc300
dc.identifier.doihttps://doi.org/10.1016/j.socnet.2022.01.007de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence16
internal.identifier.pubstatus1
internal.identifier.review1
internal.pdf.validfalse
internal.pdf.wellformedtrue
internal.pdf.encryptedfalse


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