空間群聚分析應用於流行病學已行之有年，但國內這方面的研究仍較缺乏，尤其在找出哪些地區有較高疾病發生率的群聚偵測。本文針對台灣鄉鎮市資料的特性，提出一套合適的群聚檢測方法，這個方法使用兩階段的電腦模擬，實證上更容易使用；這個方法除了可找出最大顯著群聚外，也能夠偵測出多個群聚的分佈。本文使用電腦模擬比較本文的方法與目前使用較為廣泛的方法(包括Kulldorff(1995)的spatial scan statistic和Tango(2005)的flexible scan statistic)，以型一誤差、型二誤差及錯誤率三種標準衡量方法的優劣。最後套用台灣癌症死亡率與健保就診次數資料，探討台灣癌症空間群聚與就診情形的變化。 / Spatial cluster analyses have applied in epidemiology for many years. In this topic there still are few researches in Taiwan, especially in detecting the areas which have higher disease intensity. In this paper, we proposed a new cluster detection method which is aimed at Taiwan counties’ data. This method which uses two-stage computer simulation procedures is useful in practice. This method can find the most likely cluster. Besides, it can find multiple clusters. We use computer simulations to compare our method with others (Kulldorff’s spatial scan statistic& Tango’s flexible scan statistic). Type-I error, Type-II error and error rate are criterions of measurement. At last, we use Taiwan cancer mortality data and all the people health insurance data to discuss Taiwan cancer spatial clusters and the change of diagnoses.