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[journal article]

dc.contributor.authorSchnell, Rainer
dc.contributor.authorNoack, Marcel
dc.contributor.authorTorregroza, Sabrina
dc.date.accessioned2017-10-23T10:39:43Z
dc.date.available2017-10-23T10:39:43Z
dc.date.issued2017
dc.identifier.issn1864-3361
dc.identifier.urihttp://www.ssoar.info/ssoar/handle/document/54378
dc.description.abstract"Web surveys have become popular in many fields of research. To compensate persisting undercoverage and nonresponse problems of web surveys, weighting strategies are used. However, the underlying assumptions of weighting are rarely tested. If the probability of missing data depends on the missing data itself (missing not at random, MNAR), no standard weighting method will correct for nonresponse or undercoverage bias. We postulate a MNAR selection effect due to health conditions. Using real data from large scale non-internet surveys in different countries (European Social Survey (ESS), n ca. 55,000, Behavioral Risk Factor Surveillance System (BRFSS), n ca. 492,000), large differences in general subjective health between Internet users and non-users can be observed. Weighting by calibration on age, gender, ethnic background, urban residence, education and household income does not eliminate the observed health differences. Therefore, the underlying missing data mechanism might be considered as an example of MNAR. If this holds, no weighting strategy will be able to eliminate health bias in web surveys." (author's abstract)en
dc.languageen
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.otherMNAR; Bias; ESS; BRFSS; Weighting; Calibration
dc.titleDifferences in General Health of Internet Users and Non-users and Implications for the Use of Web Surveys
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalSurvey Research Methods
dc.source.volume11
dc.publisher.countryDEU
dc.source.issue2
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.thesozDatengewinnungde
dc.subject.thesozMethodenvergleichde
dc.subject.thesozonline surveyen
dc.subject.thesozOnline-Befragungde
dc.subject.thesozweightingen
dc.subject.thesozcomparison of methodsen
dc.subject.thesozGesundheitszustandde
dc.subject.thesozhealth statusen
dc.subject.thesozresponse behavioren
dc.subject.thesozGewichtungde
dc.subject.thesozsurvey researchen
dc.subject.thesozdata captureen
dc.subject.thesozUmfrageforschungde
dc.rights.licenceDeposit Licence - Keine Weiterverbreitung, keine Bearbeitungde
dc.rights.licenceDeposit Licence - No Redistribution, No Modificationsen
internal.statusformal und inhaltlich fertig erschlossen
internal.identifier.thesoz10040714
internal.identifier.thesoz10040547
internal.identifier.thesoz10035808
internal.identifier.thesoz10052208
internal.identifier.thesoz10037911
internal.identifier.thesoz10045727
internal.identifier.thesoz10045579
dc.type.stockarticle
dc.type.documentjournal articleen
dc.type.documentZeitschriftenartikelde
dc.source.pageinfo105-123
internal.identifier.classoz10105
internal.identifier.journal674
internal.identifier.document32
internal.identifier.ddc300
dc.identifier.doihttps://doi.org/10.18148/srm/2017.v11i2.6803
dc.description.pubstatusPublished Versionen
dc.description.pubstatusVeröffentlichungsversionde
internal.identifier.licence3
internal.identifier.pubstatus1
internal.identifier.review1
internal.check.abstractlanguageharmonizerCERTAIN


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