Simulations in SAS

Nested Design

%let CovBlock=0.000819;
%let CovPen=0.001557;
%let CovResidual=0.03129;
data sim;
array trtmean{4} _temporary_ (2.1223 2.1046 2.0919 2.0773);
array covpen{4} _temporary_ (0.001361 0.000012 0.002008 0.002880);
do blocknum=12;
	do animalnum=2 to 25 by 2;
		do sim=1 to 1000 by 1;
			do block=1 to blocknum;																							
			rndblock=rand("Normal",0,sqrt(&CovBlock));
				do i=1 to dim(trtmean);
				TT=i;
				Mean=trtmean{i};
					do Pen=rand("Uniform");								/* Get unique pen identifiers to mimic original dataset */	
					if tt=i then rndpen=rand("Normal",0,sqrt(covpen{i}));
						do animal=1 to animalnum;
							Ind_BW_kg=Mean+rndblock+rndpen+rand("Normal",0,sqrt(&CovResidual));
							output;
						end;
					end;
				end;
			end;
		end;
	end;
end;
proc sort data=sim;
by animalnum sim tt;
run;
proc summary data=sim var mean;
class animalnum sim tt;
var ind_bw_kg;
output out=simsummary mean=mean var=variance;
run;
ods graphics / outputfmt=svg;
proc sgpanel data=simsummary;
panelby tt / novarname columns=4 uniscale=colum;
vbox mean / category=animalnum group=tt;
run;
proc univariate data=simsummary;
class animalnum tt;
var mean;
output out=simsumunivariate mean=mean var=variance;
run;
proc sort data=simsumunivariate;
by tt;
proc print data=simsumunivariate;
run;