Journal
STATISTICAL SCIENCE
Volume 26, Issue 2, Pages 240-256Publisher
INST MATHEMATICAL STATISTICS
DOI: 10.1214/10-STS346
Keywords
Bayesian pseudo-empirical likelihood; design-based approach; hierarchical Bayes methods; model-dependent approach; model-assisted methods; Polya posterior; small area estimation
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Funding
- Natural Sciences and Engineering Research Council of Canada
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According to Hansen, Madow and Tepping [J. Amer Statist. Assoc. 78 (1983) 776-793], Probability sampling designs and randomization inference are widely accepted as the standard approach in sample surveys. In this article, reasons are advanced for the wide use of this design-based approach, particularly by federal agencies and other survey organizations conducting complex large scale surveys on topics related to public policy. Impact of Bayesian methods in survey sampling is also discussed in two different directions: nonparametric calibrated Bayesian inferences from large samples and hierarchical Bayes methods for small area estimation based on parametric models.
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