Download full text
(external source)
Citation Suggestion
Please use the following Persistent Identifier (PID) to cite this document:
https://doi.org/10.18148/srm/2017.v11i1.7149
Exports for your reference manager
Bias and efficiency loss in regression estimates due to duplicated observations: a Monte Carlo simulation
[journal article]
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... view more
"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)... view less
Keywords
survey research; data quality; regression; estimation
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
duplicated observations; estimation bias; Monte Carlo simulation; inference
Document language
English
Publication Year
2017
Page/Pages
p. 17-44
Journal
Survey Research Methods, 11 (2017) 1
ISSN
1864-3361
Status
Published Version; peer reviewed
Licence
Deposit Licence - No Redistribution, No Modifications