Best way to visualize (in figures) the results from a non-normal GLM?


I've got a zero inflated, negative binomial GLM that I'm using and am curious what the best way to visually represent my results in figures would be. My model doesn't have a ton of factors; I'm looking at a blocking factor, a continuous predictor, the interaction between the two and two additional covariates.

Thoughts? Suggestions?


Less is more. Stay pure. Stay poor.
I believe relative risks plotted as points with whiskers. Though if you have interactions, just the unique and higher ordered terms. It would help if you posted your output.
Of course. So, this model here is actually just a negative binomial GLM (non-ZI) with a blocking factor, a continuous predictor (proportion of males), the interaction, and two additional covariates (male and female size). Here is the full model:

ScreenHunter_392 Jul. 19 11.35.jpg

And the reduced model:

ScreenHunter_393 Jul. 19 11.36.jpg

Here's a link to the outputs if the above images don't work. Prior to using penalized regression techniques (I used adaptive lasso in this case), I was just removing factors that I didn't think were necessarily relevant (in the context of this model) and that improved the AICc. I don't have a ton of experience with shrinkage and selection techniques but have been screwing around with lasso/elastic net techniques. Ultimately they both arrive at the same conclusion that the best model is the one with only the proportion of males as the predictor.

For such a simple model, what would be the best way to graph the results? Thank you!
So, I've tried to find the best way to graph these. As far as I can tell, the two programs that I'm familiar with (JMP and SigmaPlot) don't have an option to fit a negative binomial curve. Any other programs you'd recommend I check out?