Three Questions about a Matrix of Coefficient Plots
It's Independence Day in the U.S., so I am taking the day off, but I received the following request for advice and thought I'd pass it along to my readers.
I wonder if you could help – I am trying to create 9 different coefficient plots , which represent 9 different GLMs. In each of the 9 models, I have retained only those explanatory variables which were statistically significant. I want the plots to make clear which variables were retained and which were not.
The specifics of the situation are as follows: 9 models, 4 total covariates with 2-3 usually significant.
This leads me to throw three questions out to my readers.
- What approach would you take to present (graphically, of course) several models that include different, but overlapping sets of covariates?
- From your perspective, what are the benefits and costs of excluding covariates with insignificant coefficients, especially in this situation?
- Is there an efficient way in R to skip variables in the plotting script that are not included in models? The code I've written (here and here) doesn't handle this situation well at all.
I look forward to your ideas!