For variables J and K, where you only have one measurement per ID, you should not use the RANDOM ID; statement in there.   For variable BW, you would need to reconstruct your data -- data new;    set old;    bw=bw0; time=0; output;    bw=bw1; time=1; output;    bw=bw2; time=2; output;   drop bw0 bw1 bw2 j k; run; Then use PROC MIXED with a sample syntax as below -- proc mixed data=new;    class T1 T2;    model bw = T1 T2 T1*T2;    repeated time / subject=ID type=un; ** or type=ar(1) or cs or another covariance structure; run; Hope this helps, Jill ... View more

This goes back to hypothesis testing in statistical analysis. You want to test if in the population, group1 mean is the same as the group2 mean. When you collect your data, you might have a sample mean of 15 for group1, and a sample mean of 17 for group 2. The question is, is this observed difference enough evidence to say the two groups have different means in the population? Or is the observed difference due to randomness and it does not show enough evidence to say the population means are different? You need to enter the sample means (15 and 17) and also a measure of variation in the data (stddev) so the software can test this hypothesis for you. For more information about the computational details please refer to the documentation below -- https://go.documentation.sas.com/doc/en/pgmsascdc/v_017/statug/statug_power_details81.htm   Jill   ... View more

The (ref='4') option in the CLASS statement essentially puts 4 as the last level for GROUP. So in your ESTIMATE statement, you should put -1 as the last coefficient (the 6th one) --   estimate "slope difference for group 1, ref=group4" fu_year 0 group*fu_year 1 0 0 0 0 -1 /cl;   Please see if this helps.   Thanks, Jill ... View more