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The MI Procedure

Example 9.8: Saving and Using Parameters for MCMC

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
 
Parameters for the Imputations

Obs _Imputation_ _TYPE_ _NAME_ Oxygen RunTime RunPulse
1 1 SEED   2099769086.00 2099769086.00 2099769086.00
2 1 PARM   49.31 10.00 172.19
3 1 COV Oxygen 32.05 -7.47 -28.32
4 1 COV RunTime -7.47 2.41 6.75
5 1 COV RunPulse -28.32 6.75 128.61
6 2 SEED   419117425.00 419117425.00 419117425.00
7 2 PARM   47.49 10.43 171.58
8 2 COV Oxygen 41.02 -8.60 -34.29
9 2 COV RunTime -8.60 2.25 7.61
10 2 COV RunPulse -34.29 7.61 142.94
11 3 SEED   535522494.00 535522494.00 535522494.00
12 3 PARM   45.98 10.82 172.45
13 3 COV Oxygen 43.24 -9.90 8.14
14 3 COV RunTime -9.90 2.75 -2.72
15 3 COV RunPulse 8.14 -2.72 218.32

The following statements invoke the MI procedure and use the INEST= option in the MCMC statement.

   proc mi data=FitMiss;
      mcmc inest=miest;   
      var Oxygen RunTime RunPulse; 
   run;

Output 9.8.2: Model Information
 
The MI Procedure

Model Information
Data Set WORK.FITMISS
Method MCMC
INEST Data Set WORK.MIEST
Number of Imputations 3

The remaining tables for the example are identical to the tables in Example 9.4.

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