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Statistical Disclosure Control Methods for Microdata from the Labour Force Survey
[Zeitschriftenartikel]
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 prot... mehr
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.... weniger
Thesaurusschlagwörter
Methodenforschung; Datenverarbeitung; Datenschutz; Datenaufbereitung; Datensicherheit
Klassifikation
Erhebungstechniken und Analysetechniken der Sozialwissenschaften
Freie Schlagwörter
Statistical Disclosure Control; perturbative methods; PRAM; Additive Noise; Rank Swapping; microdata; Labour Force Survey; sdcMicro package
Sprache Dokument
Englisch
Publikationsjahr
2020
Seitenangabe
S. 7-24
Zeitschriftentitel
Acta Universitatis Lodziensis. Folia Oeconomica, 3 (2020) 348
DOI
https://doi.org/10.18778/0208-6018.348.01
ISSN
2353-7663
Status
Veröffentlichungsversion; begutachtet (peer reviewed)