Statistical analysis
REGRESSION
Due to the exploratory nature of this analysis, an unbiased approach with no pre-specified hypotheses was adopted to investigate associations between the brain/spinal cord regions and the digital measures obtained with the Floodlight PoC app (Table In the second analysis, the variance in the digital measures that can be explained by volumetric MRI data was estimated. Here, a Bayesian ridge regression model [Given the relatively short duration of the study (24 weeks) and the stability of the clinical and MRI measures over the study period (Fig. SI1), a data aggregation approach was followed to reduce variability and to deal more effectively with missing data. For both analyses, the data were aggregated as follows: for the digital measures, the median across all valid active tests was calculated; for the standard clinical measures and MRI outcomes, the mean of the three clinical visits (baseline, week 12, and week 24) and two MRI scans (baseline and week 24), respectively, were calculated.All statistical analyses were performed in Python 3.7.9 (