Survey Methodology
Sample allocation for efficient model-based small area estimation

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by Mauno Keto and Erkki PahkinenNote 1

  • Release date: June 22, 2017
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Abstract

We present research results on sample allocations for efficient model-based small area estimation in cases where the areas of interest coincide with the strata. Although model-assisted and model-based estimation methods are common in the production of small area statistics, utilization of the underlying model and estimation method are rarely included in the sample area allocation scheme. Therefore, we have developed a new model-based allocation named g1-allocation. For comparison, one recently developed model-assisted allocation is presented. These two allocations are based on an adjusted measure of homogeneity which is computed using an auxiliary variable and is an approximation of the intra-class correlation within areas. Five model-free area allocation solutions presented in the past are selected from the literature as reference allocations. Equal and proportional allocations need the number of areas and area-specific numbers of basic statistical units. The Neyman, Bankier and NLP (Non-Linear Programming) allocation need values for the study variable concerning area level parameters such as standard deviation, coefficient of variation or totals. In general, allocation methods can be classified according to the optimization criteria and use of auxiliary data. Statistical properties of the various methods are assessed through sample simulation experiments using real population register data. It can be concluded from simulation results that inclusion of the model and estimation method into the allocation method improves estimation results.

Key Words: Optimal area sample size; Criteria; Auxiliary information; Measure of homogeneity.

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How to cite

Keto, M., and Pahkinen, E. (2017). Sample allocation for efficient model-based small area estimation. Survey Methodology, Statistics Canada, Catalogue No. 12-001-X, Vol. 43, No. 1. Paper available at http://www.statcan.gc.ca/pub/12-001-x/2017001/article/14817-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.

© Minister of Industry, 2017

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. Allocations which utilize the model
Section 3. Some model-free area allocations
Section 4. Comparison of performances of allocations
Section 5. Concluding remarks
Acknowledgements
References

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