Hello,
Please I need help with using proc GLIMMIX for binary outcome. My outcome variable is Adherence to safety guidelines (Adherence) which is binary. This was measured weekly over a 15-week period. My independent variables include job title , race, ethnicity etc. which are all categorical. I am interested in seeing if adherence changed over time. I am using the following codes for my analysis but the model did not converge. Please find also the SAS log information.
PROC GLIMMIX DATA=COVERED.Demographics;
CLASS primary_job_cat week record_id;
MODEL complete_adherence = primary_job_cat week primary_job_cat*week/SOLUTION DIST=bin LINK=Logit DDFM=BW;
RANDOM week/SUB=record_id TYPE =AR(1) RESIDUAL;
lsmeans primary_job_cat week primary_job_cat*week/ diff e cl;
run;
Thank you.
That is not a G-side random effect model. Use this instead --
random int / subject=record_id;
And the METHOD=QUAD option must be used with G-side model, not the R-side model as you did.
You might try the PARMS statement to specify different starting values; Also try a different TYPE= option for the R-side random effect to see if that helps.
Did you get the table - covariance parameter estimates at the last iteration? If so, what does it look like?
Jill
Below is what the covariance parameter estimate shows
How many levels for week?
What if you try a G-side random effect model --
random int / subject=record_id;?
You could also add method=quad in the PROC GLIMMIX statement for this G-side random effect model to see if that helps.
Week has 20 levels.
I tried the G-side effect model but got an error message but it did not converge.
I also added the method=quad but got an error message
PROC GLIMMIX DATA=COVERED.Demographics;
CLASS primary_job_cat week record_id ;
MODEL complete_adherence = primary_job_cat week primary_job_cat*week/SOLUTION DIST=bin LINK=Logit oddsratio;
RANDOM int/SUB=record_id TYPE =AR(1) RESIDUAL;
lsmeans primary_job_cat week primary_job_cat*week/ diff e cl;
run;
PROC GLIMMIX DATA=COVERED.Demographics method=quad(qpoints=19);
CLASS primary_job_cat week record_id ;
MODEL complete_adherence = primary_job_cat week primary_job_cat*week/SOLUTION DIST=bin LINK=Logit oddsratio;
RANDOM int/SUB=record_id TYPE =AR(1) RESIDUAL;
lsmeans primary_job_cat week primary_job_cat*week/ diff e cl;
run;
That is not a G-side random effect model. Use this instead --
random int / subject=record_id;
And the METHOD=QUAD option must be used with G-side model, not the R-side model as you did.
Thank you so much for your assistance.
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