I am fairly new to multiple imputation and trying to be sure I understand the approach.
Say I have a data set with missing values, so I create 5 imputed data sets using multiple imputation by chained equations with the
mice package in R.
I then fit simple linear models with each imputed data set and average the coefficients.
Is it appropriate to think of this pooled result as a posterior mean?