Clarification needed for glimmix in ordinal regression testing

[Migueldoisa]

Hello,
I would like to ask for a clarification. If anyone could help me, I will be very much obliged. I have an experiment with five treatments (diets fed to animals in different parks), the response score was measured everyday, for 35 days. response variable is ordinal with three levels: 0 no effect, 1 mild effect, 2 high effect.

I have tried the following approach

proc glimmix data=score method=?;
class diet score;
model score = diet / link=cumlogit dist=multinomial;
random time / sub=park type=ar(1);

I have tried several 'method=' but would like advice which would best apply.

Also, in this paper with a similar approach, authors calculate the probability of score HIGH, which I would also like to apply here. Authors state the following formula but I'm not aware how to obtain the logit values in my case:

p = exp(logit)/(1 + exp(logit))

https://www.mdpi.com/2076-2615/13/21/3350

Any ideas appreciated.

[Migueldoisa]

For anyone who might see this,

I found this very nice tutorial on the subject

https://agstats.ca/2019/06/25/working-with-binary-and-multinomial-data-in-glimmix/

and am currently working with following script:

proc glimmix data=score method=laplace;

class diet;

model score = diet / link=cumlogit dist=multinomial oddsratio(diff=all);

random time / sub=park type=ar(1);

contrast "Control vs others" diet 4 -1 -1 -1 -1;

estimate "score 0,1 in Control" intercept 0 1 0 diet 1 0 0 0 0 /ilink;

I have removed score from class statement as it doesn't seem to make a difference.

I have added oddsratio although I don't think I'll need it seeing as I'm using contrasts?

And from that tutorial I also found I can use estimate to compute the probability of score 2, which is what I need. From what I understand, for diet 1, the statement "intercept 0 1 0 diet 1 0 0 0 0" would compute the cumulative probability of score 0 and 1. Thus, the probability of score 2 would be 1 minus that. Is this correct?

However, I'm getting a warning: 

"WARNING: More coefficients than levels specified for effect Intercept. Some coefficients will be ignored."

I have 3 coefficients, seeing as I have 3 levels of score (0, 1, 2). Am I misjudging something?

I still don't know how to determine/choose which method= statement to use.

Attentively,