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| The MI Procedure |
This example uses the MCMC method with multiple chains as specified in Example 9.4. It saves the parameter values used for each imputation in an output data set of type EST. This output data set can then be used to impute missing values in other similar input data sets. The following statements invoke the MI procedure and specify the MCMC method with multiple chains to create three imputations.
proc mi data=FitMiss seed=55417 nimpute=3 mu0=50 10 180 noprint;
mcmc chain=multiple outest=miest;
var Oxygen RunTime RunPulse;
run;
The following statements list the parameters used for the imputations. Note that the data set includes observations with _TYPE_=`SEED' containing the seed to start the next random number generator.
proc print data=miest;
title 'Parameters for the Imputations';
run;
Output 9.8.1: OUTEST Data Set
proc mi data=FitMiss;
mcmc inest=miest;
var Oxygen RunTime RunPulse;
run;
Output 9.8.2: Model Information
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The remaining tables for the example are identical to the tables in Example 9.4.
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