Survey Methodology
Adaptive cluster sampling, a quasi Bayesian approach

by Glen Meeden and Muhammad Nouman QureshiNote 1

  • Release date: December 20, 2024
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Abstract

Adaptive cluster sampling designs were proposed as a method that could be used when sampling rare populations whose units tend to appear in clusters. The resulting estimator is not based on any model assumptions and is design unbiased. It can have smaller variance than the standard estimator which does not incorporate the fact that one is dealing with a rare population. Here we will demonstrate that, when adaptive cluster sampling is appropriate, its estimator does not take into account all the available information in the design. We present a quasi Bayesian approach which incorporates the information which is now ignored. We will see that the resulting estimator is a significant improvement over the current methods.

Key Words:    Adaptive cluster sampling; Bayesian inference; Finite population sampling; Prior information.

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How to cite

Meeden, G., and Qureshi, M.N. (2024). Adaptive cluster sampling, a quasi Bayesian approach. Survey Methodology, 50(2), 209-234. Paper available at http://www.statcan.gc.ca/pub/12-001-x/2024002/article/00014-eng.pdf.

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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.

© His Majesty the King in Right of Canada, as represented by the Minister of Industry, 2024

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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