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Categorical variables while using Geographically Weighted Regression (GWR)

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03-05-2020 07:39 AM
NaziaNawrin
Emerging Contributor

Hello!
I have a question regarding Geographically Weighted Regression (GWR) in ArcGIS. So, I am using ArcMap 10.2 version. I have a large dataset of different parameters of groundwater geochemical constituents and physiography. In GWR model, my dependent variable is chemical concentration (continuous variable) and one of my explanatory variables is Physiography (categorical variable). I have classified eight physiography into 8 classes by numbering them from 1 to 8 and ran GWR model. My aim was to establish relationship between groundwater quality and physiography, i.e., to measure the R2 value.
Recently I have tried the same number of classes (8) in different order and found slightly low R2 value.

I have found in literature that “Dependent and Explanatory variables should be numeric fields containing a variety of values. Linear regression methods, like GWR, are not appropriate for predicting binary outcomes (e.g., all of the values for the dependent variable are either 1 or 0).”

So, my question is – Since one of my explanatory variable, Physiography, has dummy variables i.e. 1 to 8, Can GWR model run properly for this type of variables?

And why the R2 value was changed when I randomly changed the order of class for physiography?

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2 Replies
DanPatterson_Retired
MVP Emeritus

Geographically Weighted Regression (GWR)—ArcGIS Pro | Documentation 

has a caution about using nominal/categorical data which you may be running into.  Read the help documentation to ensure that there aren't others that may be affecting your results.

Use caution when including nominal or categorical data in a GWR model. Where categories cluster spatially, there is strong risk of encountering local multicollinearity issues.

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NaziaNawrin
Emerging Contributor

Regarding local multicollinearity, it has been said to check the condition number - "The condition number included in the GWR output indicates when local collinearity is a problem (a condition number less than zero, greater than 30, or set to Null)". I have checked the condition numbers from my GWR results and the numbers were in between 0 to 30. 
In that case are you thinking the GWR model ran properly???

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