Variables order in proc mixed

[GDAL]

Hello,

When using different variables order in proc mixed, I get different results. For example with the following SAS program:

proc mixed data=table;

     class trt center study visit subject;

     model change = baseline visit trt center*study trt*visit baseline*visit;

     repeated visit / type=un subject=subject;

     lsmeans trt*visit / pdiff cl alpha = 0.05;

run;

the model doesn't converge, whereas if the variables in the model statement are in the following order: model change = visit trt center*study trt*visit baseline baseline*visit; (the only difference is the order of the baseline variable) then the model converges .

How this could be explained as the variables order should not impact the results?

Many thanks for your help.

Kind regards,

[SteveDenham]

The sweep operator.  During the multiple matrix inversions, the order of columns can affect many of the calculations, especially if there is collinearity (which is to be expected, at least a bit, with baseline and baseline*visit in the model).  I have found it always seems like a good idea to list any continuous variables last in the model statement to try to get around this kind of behavior.

Steve Denham

[Manjusha_Gondil]

Hi,

Always put categorical variables first and then continuous in model.

Thanks,

Manjusha