I am using GLIMMIX to estimate predicted probabilities of a binary outcome in 2 groups. I can get the predicted probabilities for each group (and subtract them to get the difference) but how do I compute the 95% CI for the difference of the predicted probabilities. I know that I can not use the Difference of LSMEANS as the inverse link is not linear.
PROC GLIMMIX DATA=multicenter ;
CLASS center group pt;
MODEL SideEffect/n = group / solution;
RANDOM center / solution;
LSMEANS group/ cl diff ilink;
run;
Predicted Probability for Group A is 0.2147
Predicted Probability for Group B is 0.3085.
Difference would be 0.0938, but how to get the CI of the difference?
If you really want to stick with a model-based approach, you can use the NLMeans macro as discussed and illustrated in this note. But since your data can be summarized simply as a 2x2 table, you could take a non-modeling approach and simply use the RISKDIFF option in the TABLES statement of PROC FREQ after setting it up to show the 2x2 table.
If you really want to stick with a model-based approach, you can use the NLMeans macro as discussed and illustrated in this note. But since your data can be summarized simply as a 2x2 table, you could take a non-modeling approach and simply use the RISKDIFF option in the TABLES statement of PROC FREQ after setting it up to show the 2x2 table.
Thanks so much! The NLMeans macro provides exactly what I need.
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