- Operating System: Windows 10 64-bit
- brms Version: 2.4.0

I’ve fit a model of the form

`y ~ s(x1) + x2 + (1|g1) + (1|g2) + (1|g3)`

and I want to make predictions by including only specific terms in the model. I know that the group-level terms can be specified with `re_formula`

, but is there a straightforward way to do this for the population-level terms `s(x1)`

and `x2`

?

Specifically, I want to visualize the predictions for `s(x1)`

independently of all other terms, and then do the same for `x2`

. Since `x2`

is a continuous effect, it’s easy enough to calculate the prediction manually for different values of `x2`

just by multiplying the value by the posterior parameter distribution. But for the spline term `s(x1)`

I’m not sure how to do this. Is there a simple built-in way to do this?