Hi everyone, apologies if this has been asked but I couldn't find an answer for my specific question. I wanted to get confirmation that what I am doing is appropriate. I have 20 imputed datasets. The grouping variable (2 groups) is called "condition". To compute pooled means across the imputed datasets I used the estimate statement in PROC MIXED for each level of condition: ODS TRACE ON; ODS OUTPUT SolutionF=solutionf Estimates =est3; PROC MIXED data=data noclprint covtest method=ml; class tid pid condition (ref='0'); model totalscore=condition/solution ddfm=bw; random intercept/sub=tid type=un; estimate "Intercept: 0" intercept 1 condition 0 1; estimate "Intercept: 1" intercept 1 condition 1 0 ; estimate "Intercept: 1-0" intercept 0 condition 1 -1 ; store out=model; by _Imputation_; run;  proc mianalyze data=est3; modeleffects Estimate; stderr stderr; run; For example, let's say this procedure gave me pooled estimates (means) of 8 for condition=0 and 7 for condition=1.   Then I calculated pooled SD using proc ttest and mianalyze: proc ttest data=data; class condition; var totalscore; by _Imputation_; ods output statistics=ttest_ds run; proc sort data=ttest_ds; by class _Imputation_; run; /*The dataset ttest_ds has Class variables of 0 and 1 (for the groups) and "Diff (1-2)" Pooled and Satterthwaite. It also has columns for StdDev and StdErr by Imputation for the two classes.*/   data subset; set ttest_ds; where Class='0'; /*switch to 1 for condition=1*/ run; proc mianalyze data=subset; by class; modeleffects stddev; stderr stderr; run;   This gave me pooled SDs of, for example, 5.8 for condition=0 and 5.6 for condition=1.   Then I calculated Cohen's d: data cd; mean_diff_rand1 = 8 - 7; /* pooled means for conditions = 0 and 1*/ pooled_std_dev_rand1 = sqrt((5.8**2 + 5.6**2) / 2); /* pooled SDs for conditions = 0 and 1 */ d_rand1 = mean_diff_rand1 / pooled_std_dev_rand1; run; proc print data=cd; /*printing result*/ run;   I hope this is enough information. Thank you kindly in advance! ... View more