# Are pooled results from multiple imputation equivalent to a posterior mean?

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?