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Scan Statistic Cluster Detection/Evidence
Method evidence record

Scan Statistic Cluster Detection

The spatial scan statistic, introduced by Martin Kulldorff in 1997, is a method for detecting and testing the significance of spatial clusters of events such as disease cases. It moves windows of many sizes and positions across the study region, treating each window as a candidate cluster, and scores it by a likelihood ratio comparing the rate of events inside the window to the rate outside. The window with the highest score is the most likely cluster, and its significance is assessed by Monte Carlo simulation, giving a principled answer to the recurring question of whether an apparent hotspot is real or chance.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Spatial Scan Statistic for Cluster Detection
Taxonomic method record · process-pipeline / human-geography
  • Kulldorff, M. (1997). A spatial scan statistic. Communications in Statistics – Theory and Methods, 26(6), 1481–1496. · DOI 10.1080/03610929708831995
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Curated claims

Claims persisted in the evidence ledger, each with its own assessment.

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyAccessibility Analysismachine-suggested · Relational suggestion, not evidence.Same method familyNearest Neighbour Indexmachine-suggested · Relational suggestion, not evidence.Same method familySpatial Exposure Indexmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

1 recorded citation, copied from the method source record.

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