Polish Statistical Association
Central Statistical Office of Poland
Subject: Economics , Statistics & Probability
ISSN: 1234-7655
eISSN: 2450-0291
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W. B. Molefe * / D. K. Shangodoyin * / R. G. Clark *
Keywords : composite estimation, mean squared error, sample design, small area estimation, sample size allocation, Taylor approximation.
Citation Information : Statistics in Transition New Series. Volume 16, Issue 2, Pages 163-182, DOI: https://doi.org/10.21307/stattrans-2015-009
License : (CC BY 4.0)
Published Online: 31-October-2017
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.