Optimal allocation for equal probability two-stage design

Molefe Wilford ()
Additional contact information
Molefe Wilford: University of Botswana, Botswana .

Statistics in Transition New Series, 2022, vol. 23, issue 4, 129-148

Abstract: 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: sample designs; optimal allocation; composite estimation; mean squared error; two-stage sampling; simple random sampling without replacement (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/stattrans-2022-0046 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:23:y:2022:i:4:p:129-148:n:5

DOI: 10.2478/stattrans-2022-0046

Access Statistics for this article

Statistics in Transition New Series is currently edited by Włodzimierz Okrasa

More articles in Statistics in Transition New Series from Statistics Poland
Bibliographic data for series maintained by Peter Golla ().