is sim_slopes supposed to work with brms?
I am getting the following error message when trying to use sim_slopes with a model fit using brm. But I don't know if it's supposed to work??
sorry - it didn't copy the error message. Here it is Error in terms.default(model) : no terms component nor attribute In addition: Warning message: Variable transformations in the model formula detected. Trying to use from global environment instead. This could cause incorrect results if has been altered since the model was fit. You can manually provide the data to the "data =" argument.
Great stuff, Jacob. Thanks for this super helpful package!
I also have a question about the sim_slopes function, but for use with class "glmmTMB". The interact_plot function still works great (warning messages, though), however the sim_slopes function gives me the following error:
Error in UseMethod("summ") : no applicable method for 'summ' applied to an object of class "glmmTMB"
It would be spectacular if you could point me in the direction of enabling this function for use with glmmTMB models.
All the best,
Scott Graupensperger
Hi @sag4040, you're not the first one to make that request. I will look into it.
@ebmtnprof, whether brms is supposed to work is a question I hadn't really considered one way or another. It appears that it might "work" (in that it wouldn't fail with errors) if it weren't for a technical glitch. I'd have to do some thinking about whether it makes sense statistically to do simple slopes with a Bayesian model, but empirically it is surely possible. I'll look into making that work in the next major update that I'm working on now, but as a forewarning it may be the case that the model will have to be re-fit several times to get the estimates.
Thanks! I really appreciate the great package :) Cheers, Emily
On Sun, Dec 9, 2018 at 3:50 PM Jacob Long [email protected] wrote:
Hi @sag4040 https://github.com/sag4040, you're not the first one to make that request. I will look into it.
@ebmtnprof https://github.com/ebmtnprof, whether brms is supposed to work is a question I hadn't really considered one way or another. It appears that it might "work" (in that it wouldn't fail with errors) if it weren't for a technical glitch. I'd have to do some thinking about whether it makes sense statistically to do simple slopes with a Bayesian model, but empirically it is surely possible. I'll look into making that work in the next major update that I'm working on now, but as a forewarning it may be the case that the model will have to be re-fit several times to get the estimates.
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/jacob-long/jtools/issues/43#issuecomment-445579478, or mute the thread https://github.com/notifications/unsubscribe-auth/AkNSOt5IXCUeIlzPt6JY9txdJxQMk_43ks5u3ZPCgaJpZM4XYjLv .
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Emily A. Butler
Professor & Graduate Director Family Studies and Human Development College of Agriculture & Life Sciences University of Arizona Tucson, AZ, 85721-0033
Hi Jacob,
Hopefully all is well - I am just wondering if you've had a chance to consider either an update or a potential work-around for using sim_slopes with class "glmmTMB". Unfortunately, my data are count-variables that are zero-inflated, requiring a negative binomial approach.
As always, I appreciate your work on this project. Package developers are the real MVP's of science :)
Scott
Bump^
Hi Jacob,
I am still holding out hope that it may be possible to calculate sim_slopes for glmmTMB objects. If not, I wonder if you've heard of an alternative option to calculate the estimates for the simple slopes at (-1/+1 SD)?
Many thanks!