I have two identical studies that I am trying to meta-analyze using brms. These are basic regression models with two predictors and their interaction and I’d like to synthesize the evidence for each coefficient when taking into account both studies. I have seen several helpful posts on conducting meta-analyses on brms. However, these often have more than a few studies and I am interested in learning more about what I should do if I only have two studies. Should I just set a very constrained prior on the between study variance? Or since the studies are exact replications, would another option be to just use the “posterior_samples” command to then paste the posterior samples for each sample together? Wouldn’t this be equivalent to a fixed effects meta-analysis?

As an update, I think I can used this brms syntax to model the results for each coefficient:

**y | se(sqrt(v)) ~ 0 + intercept**

Where y is the regression coefficient for each study and v is the estimated error for each coefficient. However, I’m wondering if this is preferable than the method I mentioned in my previous post?

Do you have the raw data for both studies? If yes, I would simply merge the data sets and fit the models using all data (and perhaps include a study indicator as additional predictor).

Yes, I have the raw data. I did both of the studies and they are completely identical. I will merge the data then and then refit the model that I have already fit on each data set.