Thanks, a lot for your advice. I did the;   proc glm data=work.log; class Kon treat; by kon; model PostDD= PreDD Kon treat/solution clparm; lsmeans Kon treat/tdiff cl; run;   And it worked for me. I got the outcomes adjusted for baseline differences and sorted by gender. Thanks a lot:-) BW, Sophie ... View more

Thanks a lot, both of you. I tried the LSmeans statement, but I need to adjust for the baseline value also  (Theres some clinical important baseline differences, that might impact the potential reduction)   I was told that the statement below gives the mean for the overall group differences on Diabetes distress (DD). Now I want to know if the overall differnce is driven by a better effect in men or women.   I attach my outcome table, which might give you an idea of what I need. (The results on sex are not correct).   Proc glm data=work.log; class treat; Model PostDD = PreDD/solution clparm; run;   I think it might be a quite simple procedure - to you;-) I'm just a novice in SAS..   Is I should use lsmeans, where in the statement should I put it. But importantly, I need to adjust for the baseline (preDD). Thanks Again. BW. Anne Sophie ... View more

Dear DWilson. Thanks for your comprehensive reply.   By differences in gender I mean; If the effect of the intervention differs between men and women on all outcomes. I need a mean + CL + p-value in the output for men AND women separately. (As the intervention had previously been reported to have a better effect in women) (Kon = gender)   Would this code give me that:   Proc glm data=work.log_new; class treat Kon; Model PostDD = treat kon PreDD/solution clparm; run;   However, I'm not sure how to interpret the outcome?     Parameter Estimate   StandardError t Value Pr > |t| 95% Confidence Limits Intercept -7.857818524 B 9.06399018 -0.87 0.4006 -27.29814401 11.582506960 Treat Cont 8.641893762 B 6.20797873 1.39 0.1856 -4.672896387 21.956683911 Treat Int 0.000000000 B . . . . . Kon F -3.063476648 B 6.43129427 -0.48 0.6412 -16.85723099 10.730277699 Kon M 0.000000000 B . . . . . PreDD 0.878227976   0.18708534 4.69 0.0003 0.476969834 1.279486118   ... View more

Dear Paige Miller.   Thanks for your quick reply!   The GLM statement works, however, the difference for the two genders; men respectively women, seems to be missing in the output? Or I might not interpret correctly..   Source DF Type I SS Mean Square F Value Pr > F Kon 1 126.0250000 126.0250000 0.80 0.3852 Treat 1 387.6568182 387.6568182 2.46 0.1376   Source DF Type III SS Mean Square F Value Pr > F Kon 1 84.6568182 84.6568182 0.54 0.4748 Treat 1 387.6568182 387.6568182 2.46 0.1376   I also get a Interaction plot for DDdif   ... View more