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Probability sampling designs: Balancing and principles for choice of design
Date de parution
2017-12-20
In
Statistical Science
Vol.
2
No
32
De la page
176
A la page
189
Revu par les pairs
1
Résumé
In this paper, we first aim to formalize the choice of the sampling design for a particular estimation problem. Next several principles are proposed: randomization, over-representation and restriction. These principles are fundamental to assist in the determination of the most appropriate design.
A priori knowledge of the population can be also formalized by modelling the population, which can be helpful when choosing the sampling design. We present a list of sampling designs by specifying their corresponding models and the principles used to derive them. Emphasis is placed on new spatial sampling methods and their related models. A simulation shows the advantages of the different methods.
A priori knowledge of the population can be also formalized by modelling the population, which can be helpful when choosing the sampling design. We present a list of sampling designs by specifying their corresponding models and the principles used to derive them. Emphasis is placed on new spatial sampling methods and their related models. A simulation shows the advantages of the different methods.
Autre version
https://arxiv.org/abs/1612.04965
Type de publication
Resource Types::text::journal::journal article
