jamovi

I am using Generalized Mixed Models in GAMLj.
I want to plot interactions between a metric and a binary predictor when using a Logit link.
This works in principle, but as soon as my model contains a binary predictor, I cannot plot Random Effects any more. I always get the error "contrasts apply only to factors". Since the same is very well possible in a normal mixed model, I would guess that this is a bug - at least when plotting the logit ("linear predictor) on Y, also plotting random effects should always be possible.

Hi shabde
could you post an example of the issue so I can reproduce it and fix it?
thanks
mc

Hi,
sorry my late reply, but I was a bit busy...
You can see an example in the attached file, but it also appears with other multi-level datasets.

So I have a dichotomous variable "Hall" which is a median split from the continuous variable "Halligkeit".
I have cluster sampling (variable "subject") , so I am using Mixed Models to predict both by T30 (Continuous) and Position (Binary/Factor).

As you can see in the output, in the continuous case ("Halligkeit"), I am able to plot fixed and random effects from the estimated model as charme. In the binary case ("Hall" with LogitLink), I am only able to plot random effects when I take "Position" out of the model. If I leave it in the model, I receive an error ("contrasts apply only to factors"),even when I just want to Plot T30 against Hall (actually I want to plot the interaction, but even the main effect fails). Apart from that, model estimation etc. works. So there seems to be a bug in the plot function for random effects. Or am I missing something?

Cheers,
Shabde

Hi
I think you found a bug. I'm going to fix it within this week,
thanks

In the meantime, you can use a dataset in which "Hall" is coded (not computed) and it should work

version 2.0.2 should fix this issue. It's out

mcfanda@gmail.com wrote:version 2.0.2 should fix this issue. It's out

Hi, Marcello.

[SO: Win10pro (Ita), jamovi: 1.2.2.0, GAMLj: 2.0.0]

I wanted to point out that at the moment jamovi library, sees and updates GAMLj to version 2.0.1.
To test version 2.0.2 (it works well) I downloaded it from github and compiled locally from RStudio.
Thanks for your work of updating and improving the module.

Cheers,
Maurizio

Well, thanks. However, I noticed that there is a bug in lme4::predict.glmer such that if you plot the random effects of a continuous variable estimated in a model with also a categorical variable, the plot of the random effects is meaningless. This is because lme4::predict.glmer() predicted values cannot be computed keeping constant the other variables in the model (as the other R predict() functions do). I'M working on it now

The issue comes about when the categorical variable is not balanced across groups of the cluster variable

Thank you very much for fixing the issue in 2.0.2 - some of my students were very happy with finally being able to see their random effects also in the plot!
Thankfully, I just donated via Paypal 50 Dollars to you guys, because this is really a great feature that only few GUI-based software packages do so far! Congrats!

One other question, because I only just noticed it:
Is there a specific statistical reason that there is no LRT test for random effects in the GLMM, while in normal mixed model it is possible? Because I would think that in principle, LRT should also be feasible for GLMMs.