Hi, I am conducting hierarchical generalized linear model with a dichotomous (1/0) and polytomous (large/median/small) outcome variables, using the code below separately:
proc glimmix data= one method=laplace noclprint;
class id group;
model dich_outcome (event='1') = group|time / dist=binary link=logit solution oddsratio;
random intercept/ subject=ID cl type=vc solution cl;
run;
proc glimmix data= two method=laplace noclprint;
class id group;
model poly_outcome (event='large') = group time / dist=multi link=clogit solution oddsratio;
random intercept/ subject=ID cl type=vc solution cl;
run;
Since the interaction for dichotomous outcome is significant, I keep it in the model. And interaction for polytomous outcome is not significant, I removed it from the model.
Below output is for dichotomous:
Solutions for Fixed Effects
Standard
Effect Group Estimate Error DF t Value Pr > |t|
Intercept 1.6820 0.6270 78 2.68 0.0089
Group 0 -2.1304 0.7764 256 -2.74 0.0065
group 1 0 . . . .
time -0.6136 0.2006 256 -3.06 0.0025
time*group 0 0.5303 0.2399 256 2.21 0.0279
time*group 1 0 . . . .
Odds Ratio Estimates
95% Confidence
Group time group _time Estimate DF Limits
0 2 0 2 0.311 256 0.088 1.094
0 3 0 2 0.920 256 0.708 1.196
1 3 0 2 0.541 256 0.365 0.804
Below output is for polytomous outcome:
Solutions for Fixed Effects
Standard
Effect UPCR Group Estimate Error DF t Value Pr > |t|
Intercept large -1.9201 0.7731 71 -2.48 0.0154
Intercept median 2.4002 0.7877 71 3.05 0.0032
Group 0 1.2784 0.8877 136 1.44 0.1521
Group 1 0 . . . .
time -0.7128 0.1790 136 -3.98 0.0001
Odds Ratio Estimates
95% Confidence
Group time Group _time Estimate DF Limits
0 1.5 1 1.5 3.591 136 0.621 20.780
2.5 1.5 0.490 136 0.344 0.698
My questions are:
1. I understand how to interpret the odds ratio for dichotomous outcome, I am not sure, why there is no odds ratios for 'time' alone?
2. In the solutions for fix effect, there is a p value for group, time, and interaction, but in the odds ratio, we only have two odds ratio for time and group interaction: 0.920[0.708, 1.196],0.541[0.365,0.804] , if I need to report p value and odds ratio, should I put the p value of interaction for both odds ratio, or the p value for time is one of them?
3. Since the polytomous outcome is a three-level categorical outcome, why in the odds ratio output, there is only one odds ratio for group and time each? In this case, how to interpret the 'median', and 'low' using odds ratio? For example, comparing group 1, group 0 was 3 times more likely be in the 'large'. But how to find out the odds ratio for 'median'/'low'?
