Adjusting Moran's I for population density.
Publication Type
Journal Article
Year of Publication
1995
Authors
Oden, N
Secondary
Stat Med
Volume
14
Pagination
17-26
Date Published
1995 Jan 15
Keywords
Analysis of Variance; Cluster Analysis; Georgia; Humans; Incidence; Lyme Disease; Models, Statistical; Population Density; Random Allocation; Risk Factors; Space-Time Clustering
Abstract
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.