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An approximation to the optimal subsample allocation for small areas

Author

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  • W. B. Molefe
  • D. K. Shangodoyin
  • R. G. Clark

Abstract

This paper develops allocation methods for stratified sample surveys in which small area estimation is a priority. We assume stratified sampling with small areas as the strata. Similar to Longford (2006), we seek efficient allocation that minimizes a linear combination of the mean squared errors of composite small area estimators and of an estimator of the overall mean. Unlike Longford, we define mean-squared error in a model-assisted framework, allowing a more natural interpretation of results using an intra-class correlation parameter. This allocation has an analytical form for a special case, and has the unappealing property that some strata may be allocated no sample. We derive a Taylor approximation to the stratum sample sizes for small area estimation using composite estimation giving priority to both small area and national estimation.

Suggested Citation

  • W. B. Molefe & D. K. Shangodoyin & R. G. Clark, 2015. "An approximation to the optimal subsample allocation for small areas," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 16(2), pages 163-182, June.
    • Handle: RePEc:csb:stintr:v:16:y:2015:i:2:p:163-182
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    Cited by:

    1. Molefe Wilford, 2022. "Optimal allocation for equal probability two-stage design," Statistics in Transition New Series, Polish Statistical Association, vol. 23(4), pages 129-148, December.

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