title: Spatial heterogeneity of type I error for local cluster detection tests.
abstract: BACKGROUND
  Just as power, type I error of cluster detection tests (CDTs) should be spatially assessed. Indeed, CDTs' type I error and power have both a spatial component as CDTs both detect and locate clusters. In the case of type I error, the spatial distribution of wrongly detected clusters (WDCs) can be particularly affected by edge effect. This simulation study aims to describe the spatial distribution of WDCs and to confirm and quantify the presence of edge effect.
  
  
  METHODS
  A simulation of 40 000 datasets has been performed under the null hypothesis of risk homogeneity. The simulation design used realistic parameters from survey data on birth defects, and in particular, two baseline risks. The simulated datasets were analyzed using the Kulldorff's spatial scan as a commonly used test whose behavior is otherwise well known. To describe the spatial distribution of type I error, we defined the participation rate for each spatial unit of the region. We used this indicator in a new statistical test proposed to confirm, as well as quantify, the edge effect.
  
  
  RESULTS
  The predefined type I error of 5% was respected for both baseline risks. Results showed strong edge effect in participation rates, with a descending gradient from center to edge, and WDCs more often centrally situated.
  
  
  CONCLUSIONS
  In routine analysis of real data, clusters on the edge of the region should be carefully considered as they rarely occur when there is no cluster. Further work is needed to combine results from power studies with this work in order to optimize CDTs performance.
authors.affiliation: Department of Biostatistics, Medical Informatics and Communication Technologies, Clermont University Hospital, Clermont-Ferrand F-63000, France. aline.guttmann@udamail.fr.
authors.forename: Aline
authors.initials: A
authors.lastname: Guttmann
authors.forename: Xinran
authors.initials: X
authors.lastname: Li
authors.forename: Jean
authors.initials: J
authors.lastname: Gaudart
authors.forename: Yan
authors.initials: Y
authors.lastname: Gérard
authors.forename: Jacques
authors.initials: J
authors.lastname: Demongeot
authors.forename: Jean-Yves
authors.initials: JY
authors.lastname: Boire
authors.forename: Lemlih
authors.initials: L
authors.lastname: Ouchchane
mesh_terms: D016000:Cluster Analysis; D000013:Congenital Abnormalities / Q000175:diagnosis / Q000453:epidemiology*; D016208:Databases, Factual / Q000592:standards; D005602:France / Q000453:epidemiology; D006801:Humans; D012107:Research Design / Q000592:standards; D012307:Risk Factors; D062206:Spatial Analysis