tests / p-values for groups of multiple variables in GLMMs

[qiuyugong-aifi]

Hi,

Thank you for this great package.

I am just wondering is there a way to get p value of the model like following?

Thank you!

Q

[fabsig]

By running the code as you do it you obtain p-values for individual variables. Anova-style p-values for multiple variables (e.g., all fixed effects dummies of a factorial variable) is currently not possible.

While being simple from a statistical point of view, the question is how to implement this consistently in both the R and the Python package. What is currently not yet entirely clear to me is how do we let the software (automatically) know which variables belong together (given that GPBoost does not use the R-style formula notation). I will think about it and let you know if there is an update.