Let’s say we have a given dataset with 20 observations and we’ve fit a mixed-effects model, producing 2000 posterior samples. We want to generate 100 datasets of the same size as the given dataset for comparison.
Do we need to
take 100 of the 2000 samples (discarding the remaining 1900), and generate a single 20-obs dataset per sample, including drawing multiple random-effect levels from that single posterior sample, or
can we draw a single observation per sample for each of the 2000 samples, drawing only a single level per sample, and aggregate a 20-obs dataset by combining each block of 20 separate samples, resulting in 100 datasets?