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| The MIANALYZE Procedure |
This example creates data sets containing parameter estimates and corresponding (X'X)-1 matrices computed by a general linear model analysis for a set of imputed data sets. These estimates are then combined to generate valid statistical inferences about the model parameters.
The following statements use PROC GLM to generate the parameter estimates and (X'X)-1 matrix for each imputed data set:
proc glm data=outmi;
model Oxygen= RunTime RunPulse/inverse;
by _Imputation_;
ods output ParameterEstimates=glmparms
InvXPX=glmxpxi;
run;
proc print data=glmparms (obs=6);
var _Imputation_ Parameter Estimate;
title 'GLM Model Coefficients (First Two Imputations)';
run;
proc print data=glmxpxi (obs=8);
var _Imputation_ Parameter Intercept RunTime RunPulse;
title 'GLM X''X Inverse Matrices (First Two Imputations)';
run;
Output 10.5.1: PROC GLM Model CoefficientsOutput 10.5.2: PROC GLM (X'X)-1 Matrices
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The following statements use the MIANALYZE procedure with PARMS= and XPXI= input data sets to produce the same results as in Example 10.2:
proc mianalyze parms=glmparms xpxi=glmxpxi edf=28;
var Intercept RunTime RunPulse;
run;
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