Mar 21, 2017 · OK, so in this example we are able to get to the posterior with simply adding values into the parameters of the Beta distribution, but let’s now see how to get to this problem using brms. library(brms) First, here’s the brms formula of the model: s | trials(k) ~ 0 + intercept, family=binomial(link="identity"), data = d

In the paper that was discussed on Friday, the authors had used a Beta-Binomial regression and were claiming that the results were more reasonable than when using standard linear regression $-$ which is probably sensible, given that these measures are far from symmetrical or "normally distributed" (in fact the EQ5D is defined between $-\infty ...

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