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. 2014 Jul 7;5:116. doi: 10.3389/fneur.2014.00116

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Copyright © 2014 Irvine, Ferguson, Mitchell, Beattie, Lin, Stuck, Huie, Nielson, Talbott, Inoue, Beattie and Bresnahan.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Construct validity of the IBB Score. Principal component analysis (PCA) extracted three orthogonal multivariable principal component (PC) clusters that together accounted for 81.4% of the variance in outcome after SCI. (A) PC1, the largest cluster of variance (51.6%) reflects the relationship between forelimb function and histological outcome. Note the IBB score is the highest loading variable on PC1, providing evidence of construct validity. (B) PC2 (18.3% variance) reflected the relationship of forelimb weight support and gait. (C) PC3 (11.5% variance) reflects forelimb stride length. (D) PCA extracts the PCs through eigenvalue decomposition of the bivariate correlation matrix of all outcomes, here represented as a heat map of Pearson values. PCs are reflected as the Venn intersection (gray) across outcome domains and the PC loading values (correlation between each variable and the PC cluster) are represented as arrows where gage represents loading magnitude and heat reflects direction (red positive relationship, blue inverse relationship).