818 subjects had a valid Height measure.
Multivariate prediction (GLM-based, automatic feature selection, leave-one-family-out prediction)
Original data space: r=0.54 CoD=-0.03 Deconfounded space: r=-0.05 CoD=0.00
Scatterplot shows predicted-Height vs measured-Height (in original and deconfounded data space).
Univariate regression (regressing each netmat element independently against Height, correcting for multiple comparisons across elements, using PALM permutation testing, taking into account family structure).
Number of significantly correlated edges at p<0.05 (two-tailed, FWE corrected) = 2 (minimum corrected p = 0.0004)
Number of significantly correlated edges at p<0.05 (two-tailed, uncorrected) = 1514 (995 expected by chance)
Image shows edges (node-pairs) whose connection most strongly correlates with Height (in decreasing order), with t-statistic listed at the top of each node-pair.
