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https://doi.org/10.18148/srm/2017.v11i1.7149
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Bias and efficiency loss in regression estimates due to duplicated observations: a Monte Carlo simulation
[Zeitschriftenartikel]
Abstract "Recent studies documented that survey data contain duplicate records. We assess how duplicate records affect regression estimates, and we evaluate the effectiveness of solutions to deal with duplicate records. Results show that the chances of obtaining unbiased estimates when data contain 40 double... mehr
"Recent studies documented that survey data contain duplicate records. We assess how duplicate records affect regression estimates, and we evaluate the effectiveness of solutions to deal with duplicate records. Results show that the chances of obtaining unbiased estimates when data contain 40 doublets (about 5% of the sample) range between 3.5% and 11.5% depending on the distribution of duplicates. If 7 quintuplets are present in the data (2% of the sample), then the probability of obtaining biased estimates ranges between 11% and 20%. Weighting the duplicate records by the inverse of their multiplicity, or dropping superfluous duplicates outperform other solutions in all considered scenarios. Our results illustrate the risk of using data in presence of duplicate records and call for further research on strategies to analyze affected data." (author's abstract)... weniger
Thesaurusschlagwörter
Umfrageforschung; Datenqualität; Regression; Schätzung
Klassifikation
Erhebungstechniken und Analysetechniken der Sozialwissenschaften
Freie Schlagwörter
duplicated observations; estimation bias; Monte Carlo simulation; inference
Sprache Dokument
Englisch
Publikationsjahr
2017
Seitenangabe
S. 17-44
Zeitschriftentitel
Survey Research Methods, 11 (2017) 1
ISSN
1864-3361
Status
Veröffentlichungsversion; begutachtet (peer reviewed)
Lizenz
Deposit Licence - Keine Weiterverbreitung, keine Bearbeitung