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Chunk #5 — Method — Participants

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Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study.
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during the first visit (mean age: 17.69±3.11) and diagnosed as unaffected both at that visit and during a follow-up visit (mean number of years between visits=6.64±3.35) (Figure 1). In a series of analyses, the groups were further divided according to ancestry (EA, AA), age (early adolescence: 12–15 years old, late adolescence: 16–19 years old, and adults: 20–30 years old) 27, 28 and gender (male, female). All groups were matched on age. Ancestry, gender, age and missing values dictated a series of analyses that included different subsets of subjects. Full description of each of the groups can be found in Supplementary Tables 1 & 2.