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Adjusting Moran's I for population density.

N Oden
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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.

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Analysis of VarianceCluster AnalysisGeorgiaHumansIncidenceLyme DiseaseModels, StatisticalPopulation DensityRandom AllocationRisk FactorsSpace-Time ClusteringComparative StudyJournal ArticleResearch Support, U.S. Gov't, P.H.S.

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N Oden. 1995-01-15. Adjusting Moran's I for population density.. https://doi.org/10.1002/sim.4780140104

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