An Approximation To The Optimal Subsample Allocation For Small Areas

• Authors: Molefe W. B. , Shangodoyin D. K. , Clark R. G.

Abstracts

EN

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.

Keywords

EN

composite estimation; mean squared error; sample design; small area estimation; sample size allocation; Taylor approximation

• Publisher: Główny Urząd Statystyczny
• Journal: Statistics in Transition new series
• Year: 2015
• Volume: 16
• Issue: 2
• Pages: 163-182

Contributors

author

Molefe W. B.

• Department of Statistics, University of Botswana

author

Shangodoyin D. K.

• Department of Statistics, University of Botswana

author

Clark R. G.

• National Institute for Applied Statistics Research Australia, University of Wollongong

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