Analyzing multiple imputed datasets in brms

Hello, I am running a beta_binomial model in brms, and due to the mi() function not working when I use this format i opted for the Blimp Software created by Craig Enders to do the imputations.

I saved n = 10 datasets, and I now have 1 file in long format where all the information from the 10 datasets are stored. The dataset now contains 1 column indicating which of the 10 datasets the values are from, along with my imputed values.

I have seen the tutorial using the MICE package, but I am unsure of how I best should adapt the syntax given my data.

fit_binom ←
data = impute,
family = beta_binomial,
y | trials(27) ~ 1 + group*time + (time|ID),
prior = priors_list,
cores = 4, seed = 1

I think all you need to do is make a list of data.frames, where each list entry is one of your imputed datasets. You can create this list using:

df_list <- split(your_data, your_data$id_column)

Then use that list in the data argument to brm_multiple.

Thank you! This worked out really well.