proc mi
Handling Missing Data with SAS
2- •The new SAS procedure, PROC MI, is a multiple imputation procedure that creates mimputed data sets for incomplete p-dimensional multivariate data.
- 􀂾 This procedure assumes multivariate normality for the parametric regression method, and for the nonparametric method, propensity scores.
- 􀂾 For data sets with arbitrary missing patterns, a MCMC method that assumes multivariate normality is used.
- •Using the MCMC method we can impute all missing values or just enough missing values to make the imputed data sets have monotone missing patterns.
- 􀂉 Once the mcomplete data sets are analyzed by using standard procedures, another new procedure, PROC MIANALYZE, can be used to generate valid statistical inferences about these parameters by combining results from the mcomplete data sets.