I haven’t tried the Blackwell method. Of course I think brms is great but the me implementation is very top heavy and demanding with big data. Something that needs more work. Also not a lot of theory on what prior to use for measurement error (ie normal or something more flexible).
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In particular it would be interesting to discuss how in a Bayesian model the posterior distribution of the scores is different than the prior estimates.