dc.contributor.author | Pietrzak, Michał | de |
dc.date.accessioned | 2021-12-30T12:34:01Z | |
dc.date.available | 2021-12-30T12:34:01Z | |
dc.date.issued | 2020 | de |
dc.identifier.issn | 2353-7663 | de |
dc.identifier.uri | https://www.ssoar.info/ssoar/handle/document/76579 | |
dc.description.abstract | The aim of this article is to analyse the possibility of applying selected perturbative masking methods of Statistical Disclosure Control to microdata, i.e. unit‑level data from the Labour Force Survey. In the first step, the author assessed to what extent the confidentiality of information was protected in the original dataset. In the second step, after applying selected methods implemented in the sdcMicro package in the R programme, the impact of those methods on the disclosure risk, the loss of information and the quality of estimation of population quantities was assessed. The conclusion highlights some problematic aspects of the use of Statistical Disclosure Control methods which were observed during the conducted analysis. | de |
dc.language | en | de |
dc.subject.ddc | Sozialwissenschaften, Soziologie | de |
dc.subject.ddc | Social sciences, sociology, anthropology | en |
dc.subject.other | Statistical Disclosure Control; perturbative methods; PRAM; Additive Noise; Rank Swapping; microdata; Labour Force Survey; sdcMicro package | de |
dc.title | Statistical Disclosure Control Methods for Microdata from the Labour Force Survey | de |
dc.description.review | begutachtet (peer reviewed) | de |
dc.description.review | peer reviewed | en |
dc.source.journal | Acta Universitatis Lodziensis. Folia Oeconomica | |
dc.source.volume | 3 | de |
dc.publisher.country | POL | de |
dc.source.issue | 348 | de |
dc.subject.classoz | Erhebungstechniken und Analysetechniken der Sozialwissenschaften | de |
dc.subject.classoz | Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods | en |
dc.subject.thesoz | Methodenforschung | de |
dc.subject.thesoz | methodological research | en |
dc.subject.thesoz | Datenverarbeitung | de |
dc.subject.thesoz | data processing | en |
dc.subject.thesoz | Datenschutz | de |
dc.subject.thesoz | data protection | en |
dc.subject.thesoz | Datenaufbereitung | de |
dc.subject.thesoz | data preparation | en |
dc.subject.thesoz | Datensicherheit | de |
dc.subject.thesoz | data security | en |
dc.identifier.urn | urn:nbn:de:0168-ssoar-76579-7 | |
dc.rights.licence | Creative Commons - Namensnennung 4.0 | de |
dc.rights.licence | Creative Commons - Attribution 4.0 | en |
ssoar.contributor.institution | FDB | de |
internal.status | formal und inhaltlich fertig erschlossen | de |
internal.identifier.thesoz | 10052193 | |
internal.identifier.thesoz | 10040567 | |
internal.identifier.thesoz | 10040560 | |
internal.identifier.thesoz | 10040524 | |
internal.identifier.thesoz | 10057861 | |
dc.type.stock | article | de |
dc.type.document | Zeitschriftenartikel | de |
dc.type.document | journal article | en |
dc.source.pageinfo | 7-24 | de |
internal.identifier.classoz | 10105 | |
internal.identifier.journal | 2167 | |
internal.identifier.document | 32 | |
internal.identifier.ddc | 300 | |
dc.identifier.doi | https://doi.org/10.18778/0208-6018.348.01 | de |
dc.description.pubstatus | Veröffentlichungsversion | de |
dc.description.pubstatus | Published Version | en |
internal.identifier.licence | 16 | |
internal.identifier.pubstatus | 1 | |
internal.identifier.review | 1 | |
dc.subject.classhort | 10100 | de |
internal.pdf.wellformed | true | |
internal.pdf.encrypted | false | |