Please also provide the following information in addition to your question:
- Operating System: Windows 10
- brms Version: 2.6
I am still fairly new to brms. I am attempting to conduct a multivariate, multi level meta-analysis (mostly for educational purposes). I came across this Google group discussion: https://groups.google.com/forum/#!topic/brms-users/KPQaLs-PU4s
I am curious if someone can help me understand the syntax. Normally, brms uses the cbind() function to indicate multiple response variables. And for meta analysis, I have seen examples of mod = brms(yi|se~…). However, since the data structure in this example is “yi” with a dichotomous “outcome” variable, does the coefficient represent mu for the second level in this outcome variable? This does not seem to match the typical syntax of for a meta-analysis in brms.
My confusion is trying to figure out how to analyze 42 studies, each with 1-4 outcomes, and conduct moderator analyses at the same time (e.g., incorporate a study quality rating scale). My initial guess was something like this (assuming a known variance-covariance matrix V, setting outcome 1 as referent group):
brm_mod<- brm(yi ~ 1 + outcome2 + outcome3 + outcome4 + SQuality + SQuality:outcome2 + SQuality:outcome3 + SQuality:outcome4+ (1|study),
prior = set_prior(“uniform(0, 1000)”, class = “sd”),
autocor = cor_fixed(V),
data = dat, iter = 5000, warmup = 2000, cores = 4)
But this doesn’t really capture multivariate since the outcomes are all modeled separately and I have to use interactions to estimate moderation on each outcome, which means if I want an additional moderator I would be adding 4 more parameters. Is there a better way to do this?