Categorical variables while using Geographically Weighted Regression (GWR)

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03-05-2020 10:19 AM
NaziaNawrin1
New 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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DawnWright
Esri Regular Contributor

cc Spatial StatisticsGregory BrunnerKevin ButlerData Science

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Dawn Wright (she/her/hers), Ph.D. & GISP | Esri Chief Scientist
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