Hi @paul.buerkner,
I’ve figured out my problem with the parameters - it was a lack of understanding on my part (deviation contrasts with 0.5, -0.5 gives me parameters that make sense which I can pass through the hypothesis function as required).
My question regarding ‘0 + intercept’ is about how the Intercept is parameterized. I have read the relevant documentation but am not sure I completely understand it so was wondering if y ~ 0 + Intercept + x1*x2*x3 would be any different from y ~ x1*x2*x3 when x1, x2, and x3, each, are two level factors? I ran a couple of tests and the parameters in summary didn’t seem to change.
Also, on another topic (based off here), I noticed slight variability when using the bayes_factor function (even with 40,000 post-warmup posterior samples) for model comparison. I thought of doing what the OP suggested (i.e., running the function a 100 times) but if I interpreted Henrik accurately, he said that because of how bridge sampling works, that would not be the way to go and that one would need at least 2 independent sets of posterior samples? Do I go about getting another independent set of posterior samples purely by running the model again via brm?
Thank you for all your help!