Ranta J, Pitkäniemi J, Karvonen M, Virtala E, Rusanen J, Colpaert A, Naukkarinen A, Tuomilehto J
National Public Health Institute, Department of Epidemiology and Health Promotion, Helsinki, Finland.
Stat Med. 1996 Dec 15;15(23):2561-72. doi: 10.1002/(SICI)1097-0258(19961215)15:23<2561::AID-SIM370>3.0.CO;2-M.
We developed a test statistic based on an approach of Whittemore et al. (1987) to detect space-time clustering for non-infectious diseases. We extended the spatial test of Whittemore et al. by deriving conditional probabilities for Poisson distributed random variables. To combine spatial and time distances we defined a distance matrix D, where dij is the distance between the ith and jth cell in a three-dimensional space-time grid. Spatial and temporal components are controlled by a weight. By altering the weight, both marginal tests and the intermediate test can be reached. Allowing a continuum from a pure spatial to a pure temporal test, the best result will be gained by trying different weights, because the occurrence of a disease might show some temporal and some spatial tendency to cluster. We examined the behaviour of the test statistic by simulating different distributions for cases and the population. The test was applied to the incidence data of insulin-dependent diabetes mellitus in Finland. This test could be used in the analysis of data which are localized according to map co-ordinates, by addresses or postcodes. This information is important when using the Geographical Information System (GIS) technology to compute the pairwise distances needed for the proposed test.
我们基于惠特莫尔等人（1987年）的方法开发了一种检验统计量，用于检测非传染性疾病的时空聚集性。我们通过推导泊松分布随机变量的条件概率，扩展了惠特莫尔等人的空间检验。为了结合空间和时间距离，我们定义了一个距离矩阵D，其中dij是三维时空网格中第i个和第j个单元格之间的距离。空间和时间成分由一个权重控制。通过改变权重，可以得到边际检验和中间检验。允许从纯空间检验到纯时间检验的连续变化，通过尝试不同的权重可以获得最佳结果，因为疾病的发生可能表现出一些时间和空间上的聚集趋势。我们通过模拟病例和总体的不同分布来检验检验统计量的行为。该检验应用于芬兰胰岛素依赖型糖尿病的发病率数据。此检验可用于分析根据地图坐标、地址或邮政编码定位的数据。在使用地理信息系统（GIS）技术计算所提出检验所需的成对距离时，此信息很重要。
