I have unequal observations, because I look at response time data based on response accuracy (and only trials where a participant actually responds.
For example, one person could have 300 correct trials and 20 error trials and another could have 290 correct trials and 25 error trials (with 5 discarded non-response trials).
@paul.buerkner you actually helped me with a similar problem before (Modeling unbalanced multivariate outcomes in brms), which was referenced above.
My hope is to get an identical output to using
bf(congruent ~ 0 + (1+trial|p|id)) +
bf(incongruent ~ 0 + (1+trial|q|id) + rescor(TRUE)
In this case it would be something like
bf(correct ~ 0 + (1+trial|p|id)) +
bf(error ~ 0 + (1+trial|q|id) + rescor(TRUE)
That output of this brms fit has all of the (co)variance components that I need, and none that I don’t :) I don’t know if that helps to clarify what I’m after… I can only get it to work if I have the same number of correct and error trials across participants.