Optimal allocation for equal probability two-stage design

• Authors: Wilford Molefe

Abstracts

EN

This paper develops optimal designs when it is not feasible for every cluster to be represented in a sample as in stratified design, by assuming equal probability two-stage sampling where clusters are small areas. The paper develops allocation methods for two-stage sample surveys where small-area estimates are a priority. We seek efficient allocations where the aim is to minimize the linear combination of the mean squared errors of composite small area estimators and of an estimator of the overall mean. We suggest some alternative allocations with a view to minimizing the same objective. Several alternatives, including the area-only stratified design, are found to perform nearly as well as the optimal allocation but with better practical properties. Designs are evaluated numerically using Switzerland canton data as well as Botswana administrative districts data.

Keywords

EN

sample designs; optimal allocation; composite estimation; mean squared error; two-stage sampling; simple random sampling without replacement

• Publisher: Główny Urząd Statystyczny
• Journal: Statistics in Transition new series
• Year: 2022
• Volume: 23
• Issue: 4
• Pages: 129-148

Dates

published

2022

Contributors

author

Wilford Molefe

• University of Botswana, Botswana

• https://orcid.org/0000000176742244

References

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Identifiers

DOI

10.2478/stattrans-2022-0046

Biblioteka Nauki

2156993