jamovi

Since missing data is the problem, I'd encourage you to consider imputation, and determine if it's appropriate for your use case. Both the jamovi modules BSS and jYS offer an imputation feature which might be useful to you.

Understood, thank you for following up and the explanation. Trust me, I'm well aware of the major update of GAMLj. I check the jamovi modules everyday for that update, because I use GAMLj more than anything else. Thank you so much for continuing to develop GAMLj!

These trainings sound like they could be treated as ordinal data, in which case a cumulative link mixed model would be appropriate.

Certainly! I did some more testing, and the failure seems to only occur when correlation by blocks is used. Adding a second random effect to a second block breaks the analysis. As you can see from the attached screenshot, "math | school" is never added to the model; the analysis stalls ins...

The Generalized Mixed Model test is no longer functioning as expected following the latest jamovi update (v. 2.4.2). However, the General Linear Model, Mixed Model, and Generalized Linear Model tests are functioning as expected. Can anyone else verify please?

Very glad to hear it! Thank you for continuing to develop GAMLj; it has been of great use to my research.

Thank you for replying! I can't speak for how others might use it, but I can give you an example of how I would. Sometimes I model the height of animals in trees. In a complete data set, the height of the animal and the tree is available, so then the exact animal height can be modelled while tree he...

Is jamovi able to model beta-distributed dependent variables, e.g. , rates and proportions? I looked in both the base jmv and the GAMLj module, but couldn't find the option. I then searched for the solution on these forums, but the search terms are ignored because the words "beta regression&quo...

Jonathon,

Thank you so much! That's honestly a great relief to me. Some chapters of my dissertation are built atop jamovi, so I'm greatly relieved to hear that. Thank you!