Detecting Spatial Autocorrelation for a Small Number of Areas: a practical example

Abstract

Abstract Moran’s I is commonly used to detect spatial autocorrelation in spatial data. However, Moran’s I may lead to underestimating spatial dependence when used for a small number of areas. This led to the development of Modified Moran’s I , which is designed to work when there are few areas. In this paper, both methods will be presented. Many R programs enable calculating Moran’s I , but to date, none have been available for calculating Modified Moran’s I . This paper aims to present both methods and provide the R code for calculating Modified Moran’s I , with an application to a case study of dengue fever across 14 regions in Makassar, Indonesia.