The mice package

The mice package provides an alternative approach to imputation, being based on a Bayesian procedure without assuming multivariate normality. The approach used by mice relies upon a procedure known as "chained equations". The basic operation goes as follows:

1. Some preliminary starting imputation values are filled in for all missing data.
2. The imputation starts for some particular variable, which we will call X. Starting imputation values are removed from X and missing data in X is, once again, treated as missing. Preliminary imputations are left in place of all other variables. Observed elements of X are regressed on, or somehow matched to the other variables (values of these other variables may be observed or imputed). Based on this regression or matching, the missing values of X are filled in.
3. Step 2 is then repeated for the next variable in line Y. Step 2 is then repeated for variable Z, and this goes on until the imputation has been done for all variables.
4. Steps...