MANY-TO-ONE INDIRECT SAMPLING WITH APPLICATION TO THE FRENCH POSTAL TRAFFIC ESTIMATION
成果类型：
Article
署名作者：
Medous, Estelle; Goga, Camelia; Ruiz-Gazen, Anne; Beaumont, Jean-Francois; Dessertaine, Alain; Puech, Pauline
署名单位：
Universite de Toulouse; Universite Toulouse 1 Capitole; Toulouse School of Economics; Universite Marie et Louis Pasteur; Statistics Canada
刊物名称：
ANNALS OF APPLIED STATISTICS
ISSN/ISSBN：
1932-6157
DOI：
10.1214/22-AOAS1653
发表日期：
2023
页码：
838-859
关键词：
摘要：
In social and economic surveys, it can be difficult to directly reach units of the target population, and indirect sampling is often advocated to solve this issue. In indirect sampling, the sample is drawn from a frame population that is linked to the target population, and estimation of target population pa-rameters is typically achieved through the generalized weight share method (GWSM). This method provides a weight, for every unit of the target popu-lation, that depends on the one hand, on the sampling weights in the frame population and, on the other hand, on the link weights between the frame population and the target population. In the present study, we focus on the situation in which the units from the frame population are linked to one and only one unit from the target population (Many-to-One case). This situation is encountered at the French postal service where addresses are sampled instead of postman rounds. We aim at understanding of the impact of the link weights on the efficiency of the GWSM estimators. We derive variance expressions and optimality results for a large class of sampling designs. Moreover, we note that the Many-to-One case can lead to too many links to observe. We alleviate the problem by introducing an intermediate population and double indirect sampling. The question of the loss of precision in this situation is dis-cussed in detail through theoretical results and simulations. These findings help to explain the loss of precision of double GWSM estimators observed recently at the French postal service.
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