Abstract
Microaggregation is one of the most frequently applied statistical disclosure control techniques for continuous data. The basic principle of microaggregation is to group the observations in a data set and to replace them by their corresponding group means. However, while reducing the disclosure risk of data files, the technique also affects the results of statistical analyses. The paper deals with the impact of microaggregation on a linear model in continuous variables. We show that parameter estimates are biased if the dependent variable is used to form the groups. Using this result, we develop a consistent estimator that removes the aggregation bias. Moreover, we derive the asymptotic covariance matrix of the corrected least squares estimator.
| Item Type: | Paper |
|---|---|
| Keywords: | Asymptotic variance, consistent estimation, disclosure control, linear model, microaggregation |
| Faculties: | Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386 Special Research Fields > Special Research Field 386 |
| Subjects: | 500 Science > 510 Mathematics |
| URN: | urn:nbn:de:bvb:19-epub-1831-0 |
| Language: | English |
| Item ID: | 1831 |
| Date Deposited: | 11. Apr 2007 |
| Last Modified: | 04. Nov 2020 12:45 |

