Dear members of community!
Could you help me with the problem of providing an Ordinal Logistic Regression model with Random factor, please?
I have the following variables:
1. Resoult - outcome ordinal var with some kind of 7-levels scale (1-very bad, 2-bad, etc.);
2. Group - predictor var with 2 levels (fixed effect in the model);
3. Sequence - predictor var with 2 levels (fixed effect in the model);
4. Baseline - baseline var 100-levels scale (as I understand we can use this var like a continious var) as a covariate;
5. Site - random effect in the model.
6. Subject ID- uniq number of patient
The main problem is:
"The Resoult will be analysed using an Ordinal Logistic Regression model with Baseline as a covariate, Group and Sequence as fixed effects as well as Site as a random effect."
I think that we need to use Proc Glimmix because this procedure involve posibility to use it for Ordinal Logistic Regression with random factor as I have read, but I'm not a very native with the procedure.
So, how I can use Proc Glimmix insead of Proc Logistic for solving the problem?
Many thanks in advance!
Best Regards,
Andrey.
proc glimmix data=data method=laplace;
class Group Sequence Site;
model Result = Group Sequence Baseline / dist=multinomial link=cumlogit;
random Site/ solution;
run;
I would not specify anything having to do with denominator degrees of freedom (ddfm=) at this point. The default containment method should prove adequate.
Steve Denham
I think that I need to use the following code for solving my problem:
proc glimmix data=data method=laplace;
class Group Sequence Site;
model Result = Group Sequence Baseline /dist=??? link=??? ddfm=???;
random Site/ solution;
run;
I have read many similar questions here and find that "method=laplace" is often recommended method, is it applicable in my case?
Could you help me please with choosing distribution type and link function for 7-levels scale outcome and link-function? Is it multinomial distribution?
Is it correct using of random statement?
Best Regards,
Andrey.
proc glimmix data=data method=laplace;
class Group Sequence Site;
model Result = Group Sequence Baseline / dist=multinomial link=cumlogit;
random Site/ solution;
run;
I would not specify anything having to do with denominator degrees of freedom (ddfm=) at this point. The default containment method should prove adequate.
Steve Denham
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