[R-sig-ME] glmmTMB question - diagnostic plots of model fit and effect sizes

[Ben Bolker]

On 2024-07-23 12:27 p.m., Luke D. Fannin wrote:
> Dear Dr. Bolker,
> 
> I hope this email finds you well. My name is Luke Fannin; I�m an EEB  graduate student at Dartmouth College. I am wondering if I can ask for your advice on some analyses I�ve been running with glmmTMB.
> 
> Specifically, I have two questions. Is there a way within the package to: plot a diagnostic plot of model predictions against data to evaluate performance? Also, is there a handy way to calculate parameter effect sizes? 

   The package itself doesn't have any built-in diagnostic plotting 
methods, but you can do something like

plot(fitted(m1), model.response(model.frame(m1)))

  If you're willing to use other packages, then 
performance::check_model() and the DHARMa packages generally are good 
places to start.


I�ve been working with the zero-inflated NB models specifically, but I 
wanted to make sure I hadn�t missed any references to these issues in 
your helpful GLMM FAQ online. Any help would be most appreciated. Thank 
you in advance and I look  forward to hearing from you.

   This depends very much what you mean by 'effect size'. I often like 
the scaled regression coefficients as a low-tech solution (e.g. see the 
`by_2sd()` function in the dotwhisker package, or you can scale your 
predictor variables yourself). Or take a look around at the helper 
packages listed at https://cran.r-project.org/web/views/MixedModels.html

   Ben Bolker
> 
> Best,  Luke
> 
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> 
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-- 
Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
(Acting) Graduate chair, Mathematics & Statistics
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