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Spatially Balanced Sampling: A Review and A Reappraisal
Authors:Roberto Benedetti  Federica Piersimoni  Paolo Postiglione
Affiliation:1. Department of Economic Studies, University of Chieti‐Pescara, Pescara, Italy;2. Directorate for Methodology and Statistical Process Design, ISTAT, Rome, Italy
Abstract: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.
Keywords:design‐based inference  spatial units  finite populations  spatial dependence  spatial statistics
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