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dc.contributor.authorSchmid, Matthiasen_US
dc.description.abstractMicroaggregation is one of the most important 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. In this paper, we consider single-axis sorting, a frequently applied microaggregation technique where the formation of groups depends on the magnitude of a sorting variable related to the variables in the data set. The paper deals with the impact of this technique on a linear model in continuous variables. We show that parameter estimates are asymptotically biased if the sorting variable depends on the response variable of the linear model. 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.en_US
dc.publisher|aTechn. Univ.; Sonderforschungsbereich 386, Statistische Analyse Diskreter Strukturen|cMünchenen_US
dc.relation.ispartofseries|aDiscussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München|x472en_US
dc.subject.keywordAsymptotic varianceen_US
dc.subject.keywordconsistent estimationen_US
dc.subject.keyworddisclosure controlen_US
dc.subject.keywordlinear modelen_US
dc.subject.keywordsorting variableen_US
dc.titleThe effect of single-axis sorting on the estimation of a linear regressionen_US
dc.type|aWorking Paperen_US

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