Example 55.6 Reading GLM Results from PARMS= and XPXI= Data Sets
This example creates data sets containing parameter estimates and corresponding
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
matrix for each imputed data set:
proc glm data=outmi;
model Oxygen= RunTime RunPulse/inverse;
by _Imputation_;
ods output ParameterEstimates=glmparms
InvXPX=glmxpxi;
quit;
The following statements display (in Output 55.6.1) the output parameter estimates and standard errors from PROC GLM for the first two imputed data sets:
proc print data=glmparms (obs=6);
var _Imputation_ Parameter Estimate StdErr;
title 'GLM Model Coefficients (First Two Imputations)';
run;
Output 55.6.1
PROC GLM Model Coefficients
1 |
Intercept |
86.5440339 |
10.00726811 |
1 |
RunTime |
-2.8223108 |
0.32824165 |
1 |
RunPulse |
-0.0587292 |
0.05854109 |
2 |
Intercept |
83.0207303 |
8.88996885 |
2 |
RunTime |
-3.0002288 |
0.33847204 |
2 |
RunPulse |
-0.0249103 |
0.05137859 |
The following statements display (in Output 55.6.2)
matrices from PROC GLM for the first two imputed data sets:
proc print data=glmxpxi (obs=8);
var _Imputation_ Parameter Intercept RunTime RunPulse;
title 'GLM X''X Inverse Matrices (First Two Imputations)';
run;
Output 55.6.2
PROC GLM
Matrices
1 |
Intercept |
12.696250656 |
-0.067849956 |
-0.069826009 |
1 |
RunTime |
-0.067849956 |
0.0136594055 |
-0.000436938 |
1 |
RunPulse |
-0.069826009 |
-0.000436938 |
0.0004344762 |
1 |
Oxygen |
86.544033929 |
-2.822310769 |
-0.058729234 |
2 |
Intercept |
10.784620785 |
-0.091107072 |
-0.057201387 |
2 |
RunTime |
-0.091107072 |
0.0156332765 |
-0.000426902 |
2 |
RunPulse |
-0.057201387 |
-0.000426902 |
0.0003602208 |
2 |
Oxygen |
83.020730343 |
-3.000228818 |
-0.024910305 |
The standard errors for the estimates in the output glmparms data set are needed to create the covariance matrix from the
matrix. The following statements use the MIANALYZE procedure with input PARMS= and XPXI= data sets to produce the same results as displayed in Output 55.3.2 and Output 55.3.3 in Example 55.3:
proc mianalyze parms=glmparms xpxi=glmxpxi edf=28;
modeleffects Intercept RunTime RunPulse;
run;