jamovi

Hi there was an issue with the module. Update to next version (1.2.2) and it will work (it coming up tomorrow). In the meantime, you can run your analyses selecting "Missing pairwise" in "Model Options". In your data this option does not change anything (you do not have missing) ...

1. sure, that is the default. With mixed model is always a good idea to center the covariates (although not necessary)
2. any factor is transformed in contrast variables and their coding is mean-centered (if do not select "dummy" as a coding system)
3. yes

Here is jamovi to R:

General Linear Model-> lm()
Generalized Liner Models -> glm() (plus some specific commands)
Mixed Models -> lmer() and lme()
Generalized Mixed Models -> glmer()

Gamlj uses a lot of other R packages to accomplish specific tasks, but these are the basic R commands.

That would be a very strange default setting. By default all continuous variables are grand mean centered. You can choose "centered clusterwise" in the "covariates scaling" panel if you want to center level 1 predictors at group means.

Hi GAMLj3 implements posthoc tests for beta models (following R emmeans package) testing differences in probabilities (o proportions). So, the posthoc values are basically marginal effects for categorical independent factors. As such, the exp(b) would not make much sense. However, you can always get...

We are investigating this. Thanks for sharing

General Linear Model by default centers the covariates to their mean, whereas Linear Regression does not. So, when your variables are entered as covariates and there is an interaction in the model, the first order effects are different. If you center your variables or in GLM set the scale to "n...

Could you tell us the jamovi version and the version of GAMLj you work with?

If you are interested, Jn plot will be in gamlj3 in next version