currently, if you model your data and you have some missed trials, you remove them from the data before modelling which is projected in the prep data by
Tsubj being less than
T. Then in the predictions STAN gives, it adds
T-Tsubj rows of value -1 for each subject. I would like to ask if there is a plan to add those -1 values to where they actually belong, where they are missing, and not to the end.
So for example, if I have trials 1,2,5 it will not give me y1,y2,y3,-1-1 but rather y1,y2,-1,-1,y5.
I guess it is quite a complex task but it would be very helpful.