The MIANALYZE Procedure

This example creates data sets that contains parameter estimates computed by a logistic regression 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 LOGISTIC to generate the parameter estimates for each imputed data set:

ods select none;
proc logistic data=outfish2;
   class Species;
   model Species= Length Width / covb;
   by _Imputation_;
   ods output ParameterEstimates=lgsparms;
run;
ods select all;

Because of the ODS SELECT statements, no output is displayed. The following statements display (in Output 76.7.1) the output logistic regression coefficients from PROC LOGISTIC for the first two imputed data sets:

proc print data=lgsparms (obs=6);
   title 'LOGISTIC Model Coefficients (First Two Imputations)';
run;

The following statements displays the covariance matrices associated with parameter estimates derived from the first two imputations in Output 76.7.2:

The following statements use the MIANALYZE procedure with input PARMS= data set:

proc mianalyze parms=lgsparms;
   modeleffects Intercept Length Width;
run;

The "Variance Information" table in Output 76.7.2 displays the between-imputation, within-imputation, and total variances for combining complete-data inferences.

The "Parameter Estimates" table in Output 76.7.3 displays the combined parameter estimates with associated standard errors.