Gelman & Hill (2006) say:
In Bugs, missing outcomes in a regression can be handled easily by simply including the data vector, NA’s and all. Bugs explicitly models the outcome variable, and so it is trivial to use this model to, in eﬀect, impute missing values at each iteration.
This sounds like an easy way to use JAGS to do prediction. But do the observations with the missing outcomes also affect parameter estimates? If so, is there an easy way to keep these observations in the dataset that JAGS sees, but to not have them affect the parameter estimates? I was thinking about the cut function, but that's only available in BUGS, not JAGS.