Hi, I am trying to run an ERGM but the size of coefficient for the edges term is super big. I know there is something wrong but have no idea of how to find or fix the error. Will appreciate all your help
Below is the summary of my model:
Have you checked the density of your network? Can you post the output of a call to summary: summary( IL2013.n1 ~ edges)
An edges term this large suggests either you have a very dense network, and/or that the edges term is compensating for a large negative coefficient on some other covariate. Depending on the values of the age nodal attribute, e.g., if the values are large, the negative coef on nodecov(age) could be driving the edges coef up.
when i am running this command
filter(mpg, year==2002)
i got this error
Error in filter(mpg, year == 2002) : object 'year' not found
what is the issue?
Is my RStudio is currpt???
Thank you very much, Martina! You were totally right. The network is not very dense (0.047) , so the problem was with the age variable. When I removed the nodecov (age) term from the model the size of the edges term goes down to -5, which I think is something normal, right? Is there a rule of thumb for a relatively normal coefficient for edges?
There's no rule of thumb -- it's both density and model specific. A coef value of 0 means that logit(p(tie)) = 0, and implies density is 50%. Most social nets have density well below 50%, so edge coefs are generally negative.
For age, you might consider centering the value of the variable on 0. If it's a substantively important covariate, it should be included in the model. And it's also good to include the "main effect" of age if you have the "interaction effect" of absdiff(age) in the model.
Thank you so much, this is really helpful. I will follow your advice and center the age variable to understand the main effect. I really appreciate your help
Best,
Ale
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