Wednesday, February 14, 2018
Andrew Wheeler, Wouter Steenbeek and Martin A Andresen (University of Texas at Dallas - School of Economic, Political and Policy Sciences, Nederlands Studiecentrum Criminaliteit en Rechtshandhaving NCSR and Simon Fraser University) have posted Testing for Similarity in Area-Based Spatial Patterns: Alternative Methods to Andresen's Spatial Point Pattern Test on SSRN. Here is the abstract:
Andresen’s spatial point pattern test (SPPT) compares two spatial point patterns on defined areal units: it identifies areas where the spatial point patterns diverge and aggregates these local (dis)similarities to one global measure. We discuss the limitations of the SPPT and provide two alternative methods to calculate differences in the point patterns. In the first approach we use differences in proportions tests corrected for multiple comparisons. We show how the size of differences matter, as with large point patterns many areas will be identified by SPPT as statistically different, even if those differences are substantively trivial. The second approach uses multinomial logistic regression, which can be extended to identify differences in proportions over continuous time. We demonstrate these methods on identifying areas where pedestrian stops by the New York City Police Department are different from violent crimes from 2006 through 2016.