A comparison of area level and unit level small area models in the presence of linkage errors


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Statistics in Transition New Series

Polish Statistical Association

Central Statistical Office of Poland

Subject: Economics, Statistics & Probability


ISSN: 1234-7655
eISSN: 2450-0291





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VOLUME 21 , ISSUE 4 (August 2020) > List of articles

Special Issue

A comparison of area level and unit level small area models in the presence of linkage errors

Loredana Di Consiglio / Tiziana Tuoto

Keywords : linear mixed models, data integration, linkage errors

Citation Information : Statistics in Transition New Series. Volume 21, Issue 4, Pages 103-122, DOI: https://doi.org/10.21307/stattrans-2020-033

License : (CC BY-NC-ND 4.0)

Received Date : 31-January-2020 / Accepted: 30-June-2020 / Published Online: 15-September-2020



In Official Statistics, interest in data integration has grown enormously, but the effect of integration procedures on statistical analysis has not yet been sufficiently developed. Data integration is not an error-free procedure and linkage errors, as false links and missed links can invalidate standard estimates. Recently, increasing attention has been paid to the effect of linkage errors on the statistical analyses and on statistical predictions. Recently, methods to adjust the unit level small area estimators for linkage errors have been proposed when the domains are correctly specified. In this paper we compare the na¨ıve and the adjusted unit level estimators with the area level estimators that are not affected by the linkage errors. The comparison encourages the use of the adjusted unit level estimator.

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