Oden N, Jacquez G, Grimson R
Applied Biomathematics, Inc., Setauket, N.Y., 11733, USA.
Stat Med. 1996;15(7-9):783-806. doi: 10.1002/(sici)1097-0258(19960415)15:7/9<783::aid-sim249>3.0.co;2-o.
One can roughly divide disease cluster tests into area-based (using regional data) and point-based (using exact locations). We have compared the power of two area-based methods (Moran's I and I* (pop), a new method) to that of two point-based methods (the Cuzick-Edwards test and Grimson's test), using three realistic simulations of disease (fox rabies in England, childhood leukaemia in North Humberside, England, and Lyme disease in Georgia). The naive belief that point-based methods should be better is not supported: for the complex data simulated here, I* (pop) and the Cuzick-Edwards test had higher power than Grimson's method or Moran's I. I* (pop) capitalizes on high inter-region variability, while Moran's I cannot.
疾病聚集性检验大致可分为基于区域的(使用地区数据)和基于点的(使用精确位置)。我们使用三种疾病的实际模拟数据(英国的狐狸狂犬病、英国北亨伯赛德郡的儿童白血病以及佐治亚州的莱姆病),将两种基于区域的方法(莫兰指数I和I*(人口),一种新方法)的检验效能与两种基于点的方法(库齐克 - 爱德华兹检验和格里姆森检验)的检验效能进行了比较。那种认为基于点的方法应该更好的天真想法是没有依据的:对于此处模拟的复杂数据,I*(人口)和库齐克 - 爱德华兹检验比格里姆森方法或莫兰指数I具有更高的检验效能。I*(人口)利用了区域间的高变异性,而莫兰指数I则不能。