x*******i
发帖数: 1590 | 1 my sas codes:
PROC genmod data=xx;
class provfs b;
model outcome=a b a*b;
repeated subject=provfs;
weight c;
CONTRAST 'test equal slopes'
a*b 1 -1 0 0 0 0,
a*b 0 1 -1 0 0 0,
a*b 0 0 1 -1 0 0,
a*b 0 0 0 1 -1 0,
a*b 0 0 0 0 1 -1;
run;
a is continuous. b is categorical with 6 groups,
thanks,
effect |
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j*****e
发帖数: 182 | 2 Try this.
PROC genmod data=xx;
class provfs b/param=ref ref=last;
model outcome=a b a*b;
repeated subject=provfs;
weight c;
CONTRAST 'test equal slope'
a*b 1 -1 0 0 0 ;
run;
For simultanous testing, just use the p-vale for the a*b term(5 df).
By the way, it seems like you don't understand the model parameterization. |
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x*******i
发帖数: 1590 | 3 楼上各位，那我这个non-estimable问题是不是data的问题呀？
另外，jsdagre (na), 用了你的code后（class provfs b/param=ref ref=last;），出
现了out of memory的问题。如果没有/param=ref ref=last，则还好。 |
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j*****e
发帖数: 182 | 4 First of all, you did not tell the whole story.
What kind of outcome do you have? What is the modeling distribution and what
is the link function here? By default, it is normal with identity link. Is
this what you want? If so, what not use proc mixed?
Second, what does weight=c means?
Third, you can write two class statements, one with provfs and one with b
using the options that I gave.
You have to understand the parameterization of linear models before you use
SAS. Otherwise, it will be a disa |
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