Shaw G M, Selvin S, Swan S H, Merrill D, Schulman J
Health Assessment and Surveillance Unit, California Department of Health Services, Berkeley.
Int J Epidemiol. 1988 Dec;17(4):913-9. doi: 10.1093/ije/17.4.913.
Patterns of disease in space are often analysed to determine whether a relationship exists between a disease outcome and environmental exposures. This report examines the performance of three cluster analytical methods when applied to a single data set. These methods, designed to assess the purely spatial variation of events, have been examined to assess their ability to detect clustering in an area where disease rates have previously been shown to be significantly elevated. The ability of these methods to detect spatial clustering was also examined using simulation techniques. All three methods were found to be poor at detecting spatially localized disease rates which were approximately three time the expected rate, as measured by the relative risk.
通常会分析疾病在空间上的模式,以确定疾病结果与环境暴露之间是否存在关联。本报告考察了三种聚类分析方法应用于单个数据集时的性能。这些方法旨在评估事件的纯空间变化,已对其在先前已显示疾病发生率显著升高的区域检测聚类的能力进行了考察。还使用模拟技术检验了这些方法检测空间聚类的能力。结果发现,所有这三种方法在检测空间局部疾病发生率方面表现不佳,按照相对风险衡量,该发生率约为预期发生率的三倍。