Hi, I am very new to brms and am having trouble getting a result which makes sense for my data (which I can’t provide unfortunately). I have a model something like:
survival ~ fin.length + head.depth + tail.length + (1|Species), family = bernoulli(), prior=prior(normal(0,5),“b”), control = list(adapt_delta = 0.99)
where all my measurements are very small continuous measurements of different fish species and survival is a simple yes/no. I have 12 survivors and 44 non-survivors, so I didn’t think sample size would be an issue. Regardless of what I set my prior to, the posterior seems to follow it very closely with almost no influence from my actual data. I know from other analyses of my data (decision trees, PCA) that this is unlikely. What does it mean if my data have little influence on the posterior?
- Operating System: MacOS Mojave 10.14.5
- brms Version: 2.9.0