EXACT DISEASE CLUSTER STATISTICS FOR STRUCTURED SETTINGS

卫生专业人员必须经常分析疾病集群的指控， 由关心的公民谁感觉到模式在小结构 环境. 例子包括家庭，家庭，兄弟姐妹，病房， 牢房区、教室、工作类型、年龄组和 建设 对于健康专业人士来说，了解哪些测试是至关重要的。 在这些小环境问题上是最好的。 一些大规模的方法可以修改以处理小环境 问题 然而，由于样本量很小，精确的方法可能是 好多了 我们已经扩展了以前的矩阵占用方法， 快速，准确的组合表达式，用于分析 生病的人。 我们建议调查这两种力量 以及其他先前公开的在结构化小环境中的方法。 据我们所知，没有进行过这种系统的调查。 我们期望许多测试方法在有限的范围内是最优的 但在其他地方并不理想。 我们的长远目标是 使用这种功率模拟的结果来选择方法， 纳入EXCLUDE，一个用户友好的PC程序，分析小 结构化的环境数据，并帮助专业人士选择 正确的测试方法。

Health professionals must often analyze disease cluster allegations made by concerned citizens who sense patterns within small structured environments. Examples include households, families, sibships, wards, cellblocks, classrooms, job types, age classes, and locations within a building. It is crucial for the health professional to know what tests are best in these small-environment problems. A few large-scale methods may be modified to handle small-environment problems. However, because sample sizes are small, exact methods may be better. We have extended previous matrix-occupancy methods to yield new, rapid, and exact combinatorial expressions for analysis of patterns of diseased individuals. We propose to investigate the power of both these and other previously-published methods in structured small environments. To our knowledge, no such systematic investigation has been carried out. We expect that many test methods will be optimal in a restricted range of the parameter space, but not ideal elsewhere. Our long-range goal is to use the results of this power simulation to choose methods for incorporation into EXCLUDE, a user-friendly PC program to analyze small structured environment data, and to help the professional choose the right test method.