Dear SAS community, Me and my project partner are SAS and statistics newbies. We are working on a project in which we fertilize ryegrass in pots with different 5 fertilizer treatments. We positioned them in a randomized 5x5 Latin Square (5 treatments with each 5 repetitions).  We evaluated height (Hohe), Carbon (C), Nitrogen (N), Carbon/Nitrogen Ratio (CN), fresh matter (FM) and dry matter (DM). The tricky thing is that there were two cuts, one after about a 6 weeks, and the second one about 10 weeks after sowing. Each time all six parameters named before were measured. We got the code below from a statistician of our university, but we are not sure how to describe it and we don´t really understand it. For your understanding: Variante = fertilizer treatment, Zeile = line, Spalte = column, Schnitt = cut The ods and mult statements are due to a macro, which creates letter displays, so you can probably ignore that.   We could use two different models.This is the first one: (which is a bit easier but I think it does not allow comparisons between cuts, all I can say is if values for height are significantly different from each other within the same cut between different fertilizers?)   proc mixed data=Tofuversuch; by Schnitt; class Variante Zeile Spalte Schnitt; model Hohe=Zeile Spalte Variante/ddfm=kr outp=r residual; lsmeans Variante/pdiff; ods output lsmeans=lsmeans1 diffs=diffs1; run; data lsmeans;set lsmeans1;where Schnitt=1;run; data diffs;set diffs1;where Schnitt=1;run; %mult(trt=variante); data lsmeans;set lsmeans1;where Schnitt=2;run; data diffs;set diffs1;where Schnitt=2;run; %mult(trt=variante);     This is the second model: proc mixed data=Tofuversuch; class Variante Zeile Spalte Schnitt; model Hohe=Zeile Zeile*Schnitt Spalte Spalte*Schnitt Variante Variante*Schnitt Schnitt/ddfm=kr outp=r residual; repeated Schnitt/subject=Zeile*Spalte type=arh(1); lsmeans Variante*Schnitt/pdiff; ods output lsmeans=lsmeans diffs=diffs; %mult(trt=variante, by=Schnitt); %mult(trt=Schnitt, by=variante); run;   For the second model we do not understand the whole repeated statement. We also are not sure about the meaning of the * signs between the explanatory variables. We are thankful for any kind of interpretation of the code and help to describe code 2 for our methods part (a two-fold ANOVA?). Let me know if you need more information in order to help.   Many thanks in advance, Theresa     ... View more