Spatially Balanced Sampling: A Review and A Reappraisal. (4th April 2017)

• Record Type: Journal Article
• Authors: Benedetti, Roberto; Piersimoni, Federica; Postiglione, Paolo
• Is Part Of: International statistical review. Volume 85:Number 3(2017)
• Page Start: 439
• Page End: 454
• Publication Date: 2017-04-04
• Subjects: design‐based inference -- spatial units -- finite populations -- spatial dependence -- spatial statistics; Statistics -- Periodicals; Statistics -- Bibliography -- Periodicals; Statistics -- Bibliography; Statistics -- Periodicals; Statistique; Statistique -- Périodiques; Statistique -- Bibliographie -- Périodiques; Statistique -- Étude et enseignement -- Périodiques; Statistique -- Étude et enseignement -- Bibliographie -- Périodiques; Ressource Internet (Descripteur de forme); Périodique électronique (Descripteur de forme); 519.2
• DOI: 10.1111/insr.12216
• Languages: English
• ISSNs: 0306-7734

Abstract

Summary: Spatially distributed data exhibit particular characteristics that should be considered when designing a survey of spatial units. Unfortunately, traditional sampling designs generally do not allow for spatial features, even though it is usually desirable to use information concerning spatial dependence in a sampling design. This paper reviews and compares some recently developed randomised spatial sampling procedures, using simple random sampling without replacement as a benchmark for comparison. The approach taken is design‐based and serves to corroborate intuitive arguments about the need to explicitly integrate spatial dependence into sampling survey theory. Some guidance for choosing an appropriate spatial sampling design is provided, and some empirical evidence for the gains from using these designs with spatial populations is presented, using two datasets as illustrations.