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Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
07:57

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Published on: April 29, 2014

Measuring the spatial accuracy of the spatial scan statistic.

Simon Read1, Peter Bath, Peter Willett

  • 1Information School, University of Sheffield, Sheffield S1 4DP, UK. simon.read@sheffield.ac.uk

Spatial and Spatio-Temporal Epidemiology
|July 4, 2012
PubMed
Summary

This study introduces a new framework and measure (Ω) to objectively assess spatial scan statistic accuracy in spatial epidemiology. Findings suggest filtering overlapping clusters may reduce accuracy, recommending visualization instead.

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Area of Science:

  • Spatial epidemiology
  • Geospatial statistics
  • Disease cluster detection

Background:

  • Spatial scan statistic is crucial in spatial epidemiology for identifying disease clusters.
  • Existing studies on spatial accuracy are infrequent and use varied, complex measures, hindering objective comparisons.
  • Lack of a standardized, comprehensive measure complicates ranking different implementations of the spatial scan statistic.

Purpose of the Study:

  • To develop a modular framework for comparing and hybridizing spatial accuracy definitions.
  • To derive a novel, single measure (Ω) for spatial accuracy that accounts for all cluster types without arbitrary weightings.
  • To evaluate existing spatial scan statistic implementations using the new measure and existing ones.

Main Methods:

  • Development of a flexible, modular framework for spatial accuracy assessment.
  • Derivation of a new, comprehensive accuracy measure, Ω, integrating true and detected clusters.
  • Application and comparison of Ω and existing measures to SaTScan™ output filter options.

Main Results:

  • The proposed framework allows for standardized comparison of spatial accuracy metrics.
  • The new measure Ω provides a unified assessment of spatial accuracy.
  • Filtering overlapping clusters in SaTScan™ output was found to potentially reduce spatial accuracy.

Conclusions:

  • The developed framework and Ω measure offer a standardized approach to evaluating spatial scan statistic accuracy.
  • Visualizing overlapping clusters may be superior to filtering them for maintaining spatial accuracy.
  • The framework and Ω are potentially extendable to spatio-temporal accuracy assessments.