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Variables order in proc mixed

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Variables order in proc mixed

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,

Respected Advisor
Posts: 2,655

Re: Variables order in proc mixed

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

Occasional Learner
Posts: 1

Re: Variables order in proc mixed

Hi,

Always put categorical variables first and then continuous in model.

Thanks,

Manjusha

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