Approximate Solution for Heteroscedasticity Problem
{"Image DocumentName": "Approximate Solution for Heteroscedasticity Problem", "Image ImageDescription": "proc glimmix data=het; if (g > 3) then y2=y/20; else y2=y; /  overcomes scaling problem  / class g; model y2 = g/noint ddfm=satterth; random _residual_ / group=g ; estimate g , 1 -3 g , 1 -4 g , 1 -5 g , 2 -3 g , 2 -4 g , 2 -5 g , 3 -4 g , 3 -5 g , 4 -5 g /adjust=simulate(nsamp = ) stepdown(type=logical) adjdfe=row; run; /  MCMT (1999) solution using macro code  / /  define all pairwise contrasts / %MakeGLMStats(dataset=het, classvar=g, yvar=y, model=g, contrasts=all(g)); /  calculate and output ests, cov matrix and Satterthwaite dendf. from heteroscedastic fit  / ods output Tests3=Tests3 SolutionF=SolutionF CovB=CovB; proc mixed data=het method=ml; class g; model y = g/ddfm=satterth solution covb; repeated/group=g; run; /  Prepare to use %SimTests  / %macro Estimates; use Tests3; read all var {DenDf} into df; use CovB; read all var ( Col1 : Col6 ) into cov; use SolutionF; read all var {Estimate} into EstPar; %mend; %SimTests(nsamp=100000, seed=121211, type=LOGICAL);", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}