Hi friends, I am trying to estimate a linear mixed model for treatments arranged in CRD using SAS using proc 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. ... View more

Helo family!   I am looking for a code to specify arh(1) covariance structure in the PROC IML simulation procedure. I saw the IML code for specifying the R-side ar(1)  covariance structure by Gibbs & Kiernan (2020), but I am struggling to figure out how to capture arh(1) instead and generate my simulation samples. Here is the code below by Gibbs & Kiernan (2020), when the R-side covariance structure is ar(1): proc iml worksize=100; resid=2; rho=0.8; m=5; /* m = number of time points */ cov=j(m,m,1); do i=1 to m; do j=1 to m; cov=[i, j]=resid*rho**abs(i-j); end; end; mean={0 0 0}; n=200; call randseed(61345); z=RandNormal(n, mean, cov); create AR1Errors from z; append from z; quit; Kindly assist with the parameters (code) required for arh(1) structure in a similar code as given above. Alternative approaches (codes) are most welcome.   Thank you for your assistance.   ... View more