Testing for similarity in area-based spatial patterns: Alternative methods to Andresen's spatial point pattern test
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Accepted Manuscript (AM)
Author(s)
Wheeler, Andrew Palmer
Steenbeek, Wouter
Andresen, Martin A
Griffith University Author(s)
Year published
2018
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Show full item recordAbstract
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 matters, as with large point patterns many areas will be identified by SPPT as statistically different, even if those differences are ...
View more >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 matters, 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 by identifying areas where pedestrian stops by the New York City Police Department are different from violent crimes for 2006–2016.
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View more >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 matters, 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 by identifying areas where pedestrian stops by the New York City Police Department are different from violent crimes for 2006–2016.
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Journal Title
Transactions in GIS
Volume
22
Issue
3
Copyright Statement
© 2018 John Wiley & Sons Ltd. This is the peer reviewed version of the following article: Testing for similarity in area‐based spatial patterns: Alternative methods to Andresen's spatial point pattern test, Transactions in GIS, 2018, 22 (3), pp. 760-774, which has been published in final form at https://doi.org/10.1111/tgis.12341. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving (http://olabout.wiley.com/WileyCDA/Section/id-828039.html)
Subject
Geomatic engineering
Human geography
Social Sciences
Geography
CONFIDENCE-INTERVALS
CRIME SEASONALITY
POLICE