Survey Methodology
A method to find an efficient and robust sampling strategy under model uncertainty

by Edgar Bueno and Dan HedlinNote 1

  • Release date: June 24, 2021
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Abstract

We consider the problem of deciding on sampling strategy, in particular sampling design. We propose a risk measure, whose minimizing value guides the choice. The method makes use of a superpopulation model and takes into account uncertainty about its parameters through a prior distribution. The method is illustrated with a real dataset, yielding satisfactory results. As a baseline, we use the strategy that couples probability proportional-to-size sampling with the difference estimator, as it is known to be optimal when the superpopulation model is fully known. We show that, even under moderate misspecifications of the model, this strategy is not robust and can be outperformed by some alternatives.

Key Words:   Sampling design; GREG estimator; Risk Measure.

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How to cite

Bueno, E., and Hedlin, D. (2021). A method to find an efficient and robust sampling strategy under model uncertainty. Survey Methodology, Statistics Canada, Catalogue No. 12-001-X, Vol. 47, No. 1. Paper available at http://www.statcan.gc.ca/pub/12-001-x/2021001/article/00002-eng.htm.

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ISSN : 1492-0921

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Survey Methodology publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves. All papers will be refereed. However, the authors retain full responsibility for the contents of their papers and opinions expressed are not necessarily those of the Editorial Board or of Statistics Canada.

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Published by authority of the Minister responsible for Statistics Canada.

© Her Majesty the Queen in Right of Canada as represented by the Minister of Industry, 2021

Use of this publication is governed by the Statistics Canada Open Licence Agreement.

Catalogue No. 12-001-X

Frequency: Semi-annual

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Table of contents

Abstract - Article main page
Section 1. Introduction
Section 2. Optimal strategy under the superpopulation model
Section 3. Robustness under a misspecified model
Section 4. Guiding the choice of sampling design with the help of a risk measure
Section 5. The risk measure under the Generalized Regression Estimator
Section 6. Numerical examples
Section 7. Conclusions
Appendix
References

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