title: Visualization of the spatial scan statistic using nested circles.
abstract: We propose a technique for the display of results of Kulldorff's spatial scan statistic and related cluster detection methods that provides a greater degree of informational content. By simultaneously considering likelihood ratio and relative risk, it is possible to identify focused sub-clusters of higher (or lower) relative risk among broader regional excesses or deficits. The result is a map with a nested or contoured appearance. Here the technique is applied to prostate cancer mortality data in counties within the contiguous United States during the period 1970-1994. The resulting map shows both broad and localized patterns of excess and deficit, which complements a choropleth map of the same data.
authors.affiliation: SEER Program, National Cancer Institute, Bethesda, Maryland, MD, USA.
authors.forename: Francis P
authors.initials: FP
authors.lastname: Boscoe
authors.forename: Colleen
authors.initials: C
authors.lastname: McLaughlin
authors.forename: Maria J
authors.initials: MJ
authors.lastname: Schymura
authors.forename: Christine L
authors.initials: CL
authors.lastname: Kielb
mesh_terms: D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000453:epidemiology / Q000401:mortality*; D012306:Risk; D013223:Statistics as Topic / Q000379:methods*; D014481:United States / Q000453:epidemiology