Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/31046 
Year of Publication: 
2005
Series/Report no.: 
Discussion Paper No. 443
Publisher: 
Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen, München
Abstract: 
Microaggregation is a set of procedures that distort empirical data in order to guarantee the factual anonymity of the data. At the same time the information content of data sets should not be reduced too much and should still be useful for scientific research. This paper in- vestigates the effect of microaggregation on the estimation of a linear regression by ordinary least squares. It studies, by way of an extensive simulation experiment, the bias of the slope parameter estimator induced by various microaggregation techniques. Some microaggrega- tion procedures lead to consistent estimates while others imply an asymptotic bias for the estimator.
Subjects: 
microaggregation
disclosure control
simple linear model
bias
consistency
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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