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Design-based Estimators Calibrated on Estimated Totals from Multiple Surveys

Auteur(s)
Guandalini, Alessio
TillĂ©, Yves 
Institut de statistique 
Date de parution
2017-8-1
In
International Statistical Review
Vol.
2
No
85
De la page
250
A la page
269
Résumé
The use of auxiliary variables to improve the efficiency of estimators is a well-known strategy in survey sampling. Typically, the auxiliary variables used are the totals of appropriate measurement that are exactly known from registers or administrative sources. Increasingly, however, these totals are estimated from surveys and are then used to calibrate estimators and improve their efficiency. We consider different types of survey structures and develop design-based estimators that are calibrated on known as well as estimated totals of auxiliary variables. The optimality properties of these estimators are studied. These estimators can be viewed as extensions of the Montanari generalised regression estimator adapted to the more complex situations. The paper studies interesting special cases to develop insights and guidelines to properly manage the survey-estimated auxiliary totals.
Lié au projet
Convention UniversitĂ© de Neuchâtel/Office fĂ©dĂ©ral de la statistique 
Identifiants
https://libra.unine.ch/handle/123456789/20141
_
10.1111/insr.12160/abstract
Type de publication
journal article
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