Hi friends,
I am trying to estimate a linear mixed model in SAS using prc mixed or proc glimmix. I have 3 categorical factors A, B and C where factor C is assumed random, and A,B are fixed. My data set looks like this:
The syntaxes that I am exploring are:
a) PROC GLIMMIX
proc glimmix data=FFRgroup outdesign=XZ;;
class factorA factorB factorC groupA groupB groupC rep;
model yield= groupA | groupB / ddfm=satterthwaite;
random factorC factorA*factorC factorB*factorC factorA*factorB*factorC / V;
lsmeans groupA | groupB / pdiff cl alpha=0.05 ;
Title "FFR Model";
run;
whch displays the following V matrix,
b) PROC MIXED:
proc mixed data=FFRgroup ;
class factorA factorB factorC groupA groupB groupC rep;
model yield= groupA | groupB / ddfm=satterthwaite;
random factorC factorA*factorC factorB*factorC factorA*factorB*factorC / V;
lsmeans groupA | groupB / pdiff cl alpha=0.05 ;
Title "FFR Model";
run;
displays the following V matrix,
What could be the problem with these two approaches not producing the covariance structure that aligns with the model in question (block diagonal)?
Thank you in advance for your assistance folks.
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