Asymptotic properties of cross-classified sampling designs
Propriétés asymptotiques des plans produits
Résumé
We investigate the family of cross-classified sampling designs across an arbitrary number of
dimensions. We introduce a variance decomposition that enables the derivation of general
asymptotic properties for these designs and the development of straightforward and asymptot-
ically unbiased variance estimators. Additionally, we demonstrate the suitability of weighted
bootstrap techniques for CCS, given the availability of a weighted bootstrap technique in each
dimension. Our conclusions are supported by an extensive simulation study. Finally, we apply
the proposed methods to a French longitudinal survey conducted among children.
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