BRMS: Can I fit only random effects for a subset of data, and not have this data impact the remaining parameter estimates?

If I fit the model with the real data and only one hypothetical observation, the posterior would be conditional on observing the hypothetical event (which is perfect). However, that solution would require fitting nearly the same model a lot (hundreds) of times.