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Continuous glucose monitoring (CGM) is a minimally invasive technology that allows continuous monitoring of an individual's blood glucose. We focus on a large clinical trial that collected CGM data every few minutes for 26 weeks and assumes that the basic observation unit is the distribution of CGM observations in a four-week interval. The resulting data structure is multilevel (because each individual has multiple months of data) and distributional (because the data for each four-week interval is represented as a distribution). The scientific goals are to: (1) identify and quantify the effects of factors that affect glycemic control in type 1 diabetes (T1D) patients; and (2) identify and characterize the patients who respond to treatment. To address these goals, we propose a new multilevel functional model that treats the CGM distributions as a response. Methods are motivated by and applied to data collected by The Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Group. Reproducible code for the methods introduced here is available on GitHub.
Matabuena et al. (Fri,) studied this question.