SAS/STAT Software

MI Procedure

The MI procedure is a multiple imputation procedure that creates multiply imputed data sets for incomplete p-dimensional multivariate data. It uses methods that incorporate appropriate variability across the m imputations. The imputation method of choice depends on the patterns of missingness in the data and the type of the imputed variable. The following are highlights of the MI procedure's features:

  • creates multiple imputed data sets for incomplete multivariate data
  • applies parametric and nonparametric methods for data sets with monotone missing values:
    • continuous variables:
      • regression method
      • predictive mean matching method
      • propensity score method
    • classification variables:
      • logistic regression method
      • discriminant function method
  • enables you to specify a multivariate imputation that uses fully conditional specification (FCS) methods
  • applies a Markov chain Monte Carlo (MCMC) method for data sets with arbitrary missing patterns
  • uses the EM algorithm to compute the MLE for (μ,Σ), the means and covariance matrix, of a multivariate normal distribution from the input data set with missing values
  • provides the following transformation methods for data that do not satisfy the assumption of multivariate normality:
    • Box-Cox
    • exponential
    • logarithmic
    • logit
    • power
  • performs sensitivity analysis by generating multiple imputations for different scenarios under the assumption that the data are missing not at random
  • performs BY group processing, which enables you to obtain separate analyses on grouped observations
  • creates a SAS data set that corresponds to any output table
  • automatically creates graphs by using ODS Graphics

Once the m complete data sets are analyzed using standard SAS procedures, the MIANALYZE procedure can be used to generate valid statistical inferences about these parameters by combining results from the m analyses.

For further details see the SAS/STAT User's Guide: The MI Procedure
( PDF | HTML )