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An Approximation to the Optimal Subsample Allocation for Small Areas

Author

Listed:
  • Molefe W. B.

    (Department of Statistics, University of Botswana, Gaborone, ; Botswana)

  • Shangodoyin D. K.

    (Department of Statistics, University of Botswana, Gaborone, ; Botswana)

  • Clark R. G.

    (National Institute for Applied Statistics Research Australia, University of Wollongong, Wollongong, ; Australia)

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

  • Molefe W. B. & Shangodoyin D. K. & Clark R. G., 2015. "An Approximation to the Optimal Subsample Allocation for Small Areas," Statistics in Transition New Series, Polish Statistical Association, vol. 16(2), pages 163-182, June.
    • Handle: RePEc:vrs:stintr:v:16:y:2015:i:2:p:163-182:n:2
    DOI: 10.21307/stattrans-2015-009
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