Interpreting GWR Result - Issue

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I used GWR to find out which independent variables lead to crime and how they vary over the space.

After a literature review, I ran a global OLS model to find the most suitable set of independent variables, then used the local GWR method. For both the OLS and GWR model I then conducted the Moran's I for the standardized residuals, to be sure that they are not spatially autocorrelated. I used ArcGIS for the analysis.

When I investigated the coefficient values within the different regions in the study area, I came to an issue that is unclear for me: For example I have included the risk factor bus stop, given as density per square kilometers, to explain burglaries (given as crime rate per 100 000 inhabitants).

The values for C1_BusDen (Coefficient 1 for bus stop density) ranges from 21 to 39. One region has a very low value with a crime rate of 1100 and bus stop density of 4.5. Another region has a very high value with a crime rate of 1250 and bus stop density of 5.07.

If the density of bus stops is high in both regions and there is also a similar crime rate, shouldn't be the relationship (value) also the same - or at least similar, but not in the lowest and highest class? Also, the region with the highest density of bus stops has at the same time the highest crime rate - the GWR coefficient value is only 26 - shouldn't it be the highest?

Do I interpret the result in the correct way, because it would make sense that a higher value in the independent variable and a higher value in the dependent varialbe lead to a stronger relationship.

I appreciate any hlep, thx!



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