Oden N
EMMES Corporation, Potomac, MD 20854.
Stat Med. 1995 Jan 15;14(1):17-26. doi: 10.1002/sim.4780140104.
I derive two new statistics, Ipop and Ipop*, that adjust Moran's I to study clustering of disease cases in areas (for example, counties) with different, known population densities. A simulation of Lyme disease in Georgia suggests that these new statistics can be more powerful than those currently in use. This is because they consider both spatial pattern and non-binomial variance in rates as evidence supporting disease clusters.
我推导出两个新的统计量，即Ipop和Ipop*，它们对莫兰指数（Moran's I）进行了调整，以研究在人口密度已知且不同的地区（如县）疾病病例的聚集情况。对佐治亚州莱姆病的模拟表明，这些新的统计量可能比目前使用的统计量更有效。这是因为它们既考虑了空间模式，又考虑了发病率中的非二项式方差，以此作为支持疾病聚集的证据。
