Hi SAS experts, My research involves simultaneously measuring IBP and NIBP in 157 dogs.Some discrepancies occur during the measurements, we define a discrepancy as a difference >10 mmHg (match_S = 0), and no discrepancy as a difference <10 mmHg (match_S = 1). The factors I want to analyze include: catagorical variables:  gender, breed, asa, bcs, disease, surgerytype, duration, sirs, qsofa, na, alb, cuffsite, IBPICsize, IBPsite, perianalgesia, dexcri, local, anticholinergic, inotrope, other continuous variables:  weight, age, pcv   The current code is: proc glimmix data=one order=data; class gender breed asa bcs disease surgerytype duration sirs qsofa na alb cuffsite IBPICsize IBPsite perianalgesia dexcri local anticholinergic inotrope other; model match_S(event='0') = gender breed asa bcs disease surgerytype duration sirs qsofa na alb cuffsite IBPICsize IBPsite perianalgesia dexcri local anticholinergic inotrope other weight age pcv / solution dist=binary link=logit; random intercept / subject=No solution; run;   But the results do not converge, and no p-values are generated. However, when No is not set as a random variable, p-values are generated. How can I improve my results? ... View more