How to model interaction between ordinal predictors

I have an ordinal response variable and a bunch of predictors, some of them are ordinal.
What is the best way to model the interaction between two ordinal variables, taking into account the monotonic effect?
I would use brms because the monotonic effect is already built-in thanks to the mo() function


If I understand it correctly, what you want is a matrix of coefficients that increase in all rows and columns. That actually sounds like a quite complex structure and I am not sure how I would go about implenting it. I would expect brms to not support this directly, but I am on mobile and can’t check. I think something like mo(a) + mo(b) + a:mo(b) should work and is the closest you can get easily to the desired structure.

Tagging @paul.buerkner to check my reasoning…

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I a is also monotonic, we should probably use mo(a) + mo(b) + mo(a):mo(b) or equivalenlty just mo(a)*mo(b).

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