I’m wondering if there is some other way to impute missing values within a brms call besides mice, since apparently the mice package does not support poisson-distributed variables. My response variable (NumARTR) is missing some values that I would like to impute. Here is my model form:
ARTRform <-bf(NumARTR|mi() ~ s(YrsSinceFire) + offset(log(PlotSizeM2))
+ ElevScale + SandScale + ClayScale +
(1|Site), family = poisson())
model1artrimp <-brm(ARTRform, data = denscover,
inits = “random”, prior = partr,
chains = 8, iter = 5000, future = TRUE,
warmup = 500, seed = 342, autocor = cor_arr(~ YearID|Plot),
control=list(max_treedepth = 13, adapt_delta=0.96))
- Operating System: Linux
- brms Version: 2.7.0
I get the following error: Error: Argument ‘mi’ is not supported for family ‘poisson(log)’.
I know I could impute the data prior to running the model but if there is anyway to impute it within the model run, this would be my preference.