It looks like ESRI has purposefully removed p-values from the software due to the dubious nature of a p-value when it comes to GWR.
"I do know that our consultant's GWR software (Fotheringham, Charlton and Martin) does compute p-values for each coefficient in every one of the local linear equations. However, [we've removed it] because doing so is really not appropriate (and we've discussed this with our consultants and they agree with that assessment)..." - emphasis and context added
You can always calculate a local or pseudo t-value by
- Adding a Field
- Using Field Calculator: divide the local Coefficient by the local Standard Error.
Estimating a local p-value:
If you want to estimate a p-value, the GWModel R Package uses this formula.
tvals is effectively your psuedo-t-score.
enp is the effective number of parameters or EffectiveNumber in the ArcGIS output (see my post). pt is a function that estimates the p-value.
pvals <- round(2 * (1 - pt(abs(tvals), enp)), 3)(line 31)
(this Mathematics question would give you the necessary sources to calculate a p-value), note that the authors of the GWR Model used the Effective Number of parameters
enp here instead of Effective Degrees of Freedom
1-pt() gives you the estimate of the p-value, and then it is multiplied by 2 to represent the two-tailed distribution.
I would say depending on how likely it is absolutely necessary for you to have p-values, I would suggest using a cut-off from a T-distribution for general exploratory understanding.
The above formula came from the
gwr.t.adjust() function from the GWModel Package, which can be used to apply adjustments to the raw t-values to attempt to accommodate for increased chances of a Type I error based on sampling the same data over and over again. See this paper pg 25 for more details on this topic.