The reason for the differences has to do with the fact that all of the variables are standardized using all of the observations prior to fitting the imputation model.  Adding observations changes the mean and variance and thus the standardized values.  These values are then used in the imputation model, which is built only on one of the groups, which leads to slightly different estimates.   To see this more explicitly, look at the example below.  Notice how the "obs-data" estimates change slightly because all the observations are standardized.  This can be readily verified using Proc STANDARD and Proc REG. data Mono1; do Trt=0 to 1; do j=1 to 5; y0=10 + rannor(999); y1= y0 + Trt + rannor(999); if (ranuni(999) < 0.3) then y1=.; output; end; end; do Trt=0 to 1; do j=1 to 45; y0=10 + rannor(999); y1= y0 + Trt + rannor(999); if (ranuni(999) < 0.3) then y1=.; output; end; end; drop j; run; proc mi data=Mono1 seed=14823 nimpute=1 out=outex15; class Trt; monotone reg (/details); mnar model( y1 / modelobs= (Trt='0')); var y0 y1; ods select MonoReg; run; proc standard data=mono1 mean=0 std=1 out=out1; var y0 y1; run; proc reg data=out1; where trt=0; model y1=y0; ods select ParameterEstimates; run; data add; trt=1; do j=1 to 45; y0=10 + rannor(1); y1= y0 + Trt + rannor(999); if (ranuni(999) < 0.3) then y1=.; output; end; drop j; run; data mono2; set mono1 add; run; proc mi data=Mono2 seed=14823 nimpute=15 out=outex15; class Trt; monotone reg (/details); mnar model( y1 / modelobs= (Trt='0')); var y0 y1; ods select MonoReg; run; proc standard data=mono2 mean=0 std=1 out=out2; var y0 y1; run; proc reg data=out2; where trt=0; model y1=y0; ods select ParameterEstimates; run; ... View more

Below is an example that shows the necessary syntax for combining the Proc TTEST results. /*Create a sample data set to work with*/ data test; do grp=1 to 2; do rep=1 to 25; if rand('UNIFORM')>.7 then y=.; else y=rand('NORMAL',.66*grp,1); output; end; end; run; proc mi data=test out=mi_test seed=1; class grp; var grp y; monotone regression; run; /*This code would work for the difference in two means*/ proc ttest data=mi_test; class grp; by _imputation_; var y; ods output statistics=ttest_ds; run; proc sort data=ttest_ds; by class _imputation_; run; proc mianalyze data=ttest_ds; by class; modeleffects mean; stderr stderr; run; ... View more