"Enforce the Principle of Marginality" random slopes option for BRM ANOVA

johan_achard

Hi,

I am working with the Bayesian RM ANOVA function in JASP, I noticed the option "Enforce the Principle of Marginality", with separate checkboxes for fixed effects and random slopes.

Here is what I have understood so far:

• The principle of marginality states that if a model includes an interaction term (e.g., A × B), it must also include the corresponding main effects (A and B) to maintain a coherent hierarchical structure.
• Applying this principle to fixed effects seems both logical and necessary for proper model interpretation.
• Applying it to random slopes it seems similar, but I assume that the option is not checked by default for random slopes because enforcing it would make the models more complex (increasing the risk of convergence issues, longer computation times, and possible overparameterization).

Is this understanding correct?

Additionally, I am working with EEG data, where inter-subject variability is often quite important. In this context, would it make particular sense to enforce marginality for random slopes to better account for individual differences? (we have around 150 trials per condition per subject, so the dataset is fairly reasonable for estimating random slopes.)

Do you have any recommendations or best practices regarding the use of this option?

Thank you very much for your help and suggestions!

Johan

EJ

I've commented here already: https://forum.cogsci.nl/discussion/9837/enforce-the-principle-of-marginality-for-random-slopes-brm-anova#latest