A Semi-Parametric Linear Mixed Models For Longitudinally Measured Fasting Blood Sugar Level Of Adult Diabetic Patients

This paper focused on longitudinal data analysis of fasting blood sugar (FBS) level of adult diabetic patients at Jimma University Specialized Hospital diabetic clinic using an application of semi-parametric mixed model. The study revealed that the rate of change in FBS level in diabetic patients, due to the clinic interventions, does not continue as a steady pace but changes with time and weight of patients. Furthermore, it clarified associations between FBS level and some characteristics of adult diabetic patients that weight of a diabetes patient has a significant negative effect whereas patient gender, age, type of diabetes and family history of diabetes did not have a significant effect on the change of FBS level. Under various variance structures of subject-specific random effects, the semi-parametric mixed models had better fit than linear mixed model. This was likely due to the localized splines, which captured more variability in FBS level than the linear mixed model.