Boscoe Francis P, McLaughlin Colleen, Schymura Maria J, Kielb Christine L
SEER Program, National Cancer Institute, Bethesda, Maryland, MD, USA.
Health Place. 2003 Sep;9(3):273-7. doi: 10.1016/s1353-8292(02)00060-6.
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.
我们提出了一种用于展示库尔朵夫空间扫描统计及相关聚类检测方法结果的技术，该技术能提供更高程度的信息含量。通过同时考虑似然比和相对风险，在更广泛的区域超额或不足情况中识别出相对风险较高（或较低）的集中子聚类是有可能的。结果是得到一幅具有嵌套或等高线外观的地图。在此，该技术被应用于1970 - 1994年期间美国本土各县的前列腺癌死亡率数据。所得地图展示了超额和不足的广泛及局部模式，这对相同数据的分级统计图起到了补充作用。
