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

Artikel

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¨¸ve 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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Statistics in Transition New Series ; ISSN: 2450-0291 ; Volume: 21 ; Year: 2020 ; Issue: 4 ; Pages: 103-122 ; New York: Exeley

Classification and Topics

• Subject: linear mixed models ; data integration ; linkage errors

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Consiglio, Loredana Di ; Tuoto, Tiziana
• Event: Veröffentlichung
• (who): Exeley
• (where): New York
• (when): 2020

Further information

• DOI: doi:10.21307/stattrans-2020-033
• Handle: http://hdl.handle.net/10419/236783
• Last update: 10.03.2025, 11:43 AM CET