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LucyB
Obsidian | Level 7

I have some one group pre-post data and I am looking at differences between a group variable (binary) and the pre post change in the score outcome.

My code for the analysis is below:

 

proc glm data=data;
    class group;
    model pre post = group / nouni;
    repeated time 2 (1 2) / printe;
    lsmeans group / stderr;
run;

3 REPLIES 3
Ksharp
Super User

I would try PROC MIXED instead of PROC GLM.

Check GLM documenation to see how to transform Repeated Measure from GLM into MIXED.

 

change your data structure as

 

data have;

 set x;

sub+1;

 time=1;value=pre;output;

time=2;value=post;output;

run;

 

 

proc mixed data=have;

class group time;

model value=group;

repeated time/type=un solution subject=sub;

lsmean group/pdiff cl;

run;

 

LucyB
Obsidian | Level 7

but does this still not make the same assumptions? my outcome is skewed.

Ksharp
Super User
If you are trying to do Repeated Measure,
I suggest you use PROC MIXED , not GLM .
GLM can't do the real mixed model .


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