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.
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