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[journal article]

dc.contributor.authorPlewis, Ian
dc.contributor.authorCalderwood, Lisa
dc.contributor.authorMostafa, Tarek
dc.date.accessioned2017-01-30T14:22:42Z
dc.date.available2017-01-30T14:22:42Z
dc.date.issued2017
dc.identifier.issn2190-4936de
dc.identifier.urihttp://www.ssoar.info/ssoar/handle/document/50212
dc.description.abstract"Interviewers made four observations related to future participation, respondent cooperation, enjoyment and whether the respondent found the questions difficult, for a large sample of face-to-face interviews at wave four of the UK Millennium Cohort Study (MCS). The focus of the paper is on predicting response behavior in the subsequent wave of MCS, four years later. The two most predictive observations are whether the respondent is likely to participate in the next wave and whether they enjoyed the interview. Not only do these predict non-response at the next wave, they do so after controlling for other explanatory variables from earlier waves in a response propensity model. Consequently, these two interviewer observations improve discrimination between respondents and non-respondents at wave five as estimated by Gini coefficients generated by a Receiver Operating Characteristic curve analysis. The predicted probabilities of responding at wave five are also used to estimate R-indicators, particularly to address the question of whether, hypothetically, conversion of 'frail' respondents would lead to improved representativity and reduced bias in longitudinal estimates of interest. The evidence from the R-indicators and partial -Rindicators suggests that successful conversions could achieve those aims although the cost of so doing might outweigh the benefits." (author's abstract)en
dc.languageen
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.otherMillennium Cohort Study; non-response; response propensity models; ROC curve
dc.titleCan interviewer observations of the interview predict future response?de
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalMethods, data, analyses : a journal for quantitative methods and survey methodology (mda)
dc.source.volume11
dc.publisher.countryDEU
dc.source.issue1
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.subject.thesozAntwortverhaltende
dc.subject.thesozInterviewde
dc.subject.thesozrepresentativityen
dc.subject.thesozsampleen
dc.subject.thesozlongitudinal studyen
dc.subject.thesozRepräsentativitätde
dc.subject.thesozresponse behavioren
dc.subject.thesozStichprobede
dc.subject.thesozLängsschnittuntersuchungde
dc.subject.thesozinterviewen
dc.rights.licenceCreative Commons - Namensnennungde
dc.rights.licenceCreative Commons - Attributionen
ssoar.contributor.institutionGESIS
internal.statusformal und inhaltlich fertig erschlossen
internal.identifier.thesoz10035808
internal.identifier.thesoz10037472
internal.identifier.thesoz10037913
internal.identifier.thesoz10056653
internal.identifier.thesoz10050423
dc.type.stockarticle
dc.type.documentjournal articleen
dc.type.documentZeitschriftenartikelde
dc.source.pageinfo29-44
internal.identifier.classoz10105
internal.identifier.journal614
internal.identifier.document32
internal.identifier.ddc300
dc.identifier.doihttps://doi.org/10.12758/mda.2016.010
dc.description.pubstatusPublished Versionen
dc.description.pubstatusVeröffentlichungsversionde
internal.identifier.licence1
internal.identifier.pubstatus1
internal.identifier.review1
ssoar.wgl.collectiontrue
internal.pdf.version1.4
internal.pdf.validfalse
internal.pdf.wellformedfalse
internal.check.abstractlanguageharmonizerCERTAIN
internal.check.languageharmonizerCERTAIN_RETAINED


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