Sampling from Correlated Populations: Optimal Strategies and Comparison Study

Ioulia Papageorgiou ()
Additional contact information
Ioulia Papageorgiou: Athens University of Economics and Business

Sankhya B: The Indian Journal of Statistics, 2016, vol. 78, issue 1, No 6, 119-151

Abstract: Abstract The problem of sampling from a population with correlated units is considered. The presence of correlation affects all stages of a survey, from the choice of the sampling scheme to the statistical inference. Ignoring or failing to identify the existing correlation can lead to incorrect inference, such as invalid standard errors, since standard sampling techniques are no longer appropriate. In this direction, several sampling methodologies have been proposed in the literature, aiming to accommodate the correlation in both the sampling and the estimation procedure. The problem can be quite difficult when the type of correlation is completely general and existing methods rely on either restricted assumptions about the population structure or limitations to practical implementation. We provide a review of currently available methodologies, drawing attention to the properties of the derived estimates, the assumptions made, the robustness of the methods under different types of correlation and the practical limitations. A question of how these methodologies compare arises because they differ on the optimality criterion they assume towards the solution. Some methodologies are even not theoretically justified, but they are commonly used as known superior in situations of correlated measurements. The comparison study is conducted on a basis of the relative efficiencies among the competing methodologies by using simulated and real data sets.

Keywords: Superpopulation; Systematic sampling; Model-based sampling; Best unbiased predictor; Optimal sampling strategy; Optimal sampling allocation; Spatial sampling.; Primary 62D05; Secondary 62M10 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s13571-015-0111-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:sankhb:v:78:y:2016:i:1:d:10.1007_s13571-015-0111-5

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/13571

DOI: 10.1007/s13571-015-0111-5

Access Statistics for this article

Sankhya B: The Indian Journal of Statistics is currently edited by Dipak Dey

More articles in Sankhya B: The Indian Journal of Statistics from Springer, Indian Statistical Institute
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().