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. 2011 Apr 11;32(5):784–799. doi: 10.1002/hbm.21066

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Copyright © 2010 Wiley‐Liss, Inc.

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Figure A1 — Determination of the primary clusters using the two dominant eigenvectors (with the two highest eigenvalues) of the PCA. These two dominant eigenvectors are used to select three primary clusters based on the following decision rules: Group 1: (which is the most condensed cluster region with 32 data points); Group 2: (with 10 data points); Group 3: (with five data points). The undecided region, with 75 data points, is the remaining region outside these three clusters. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Inline graphic — Determination of the primary clusters using the two dominant eigenvectors (with the two highest eigenvalues) of the PCA. These two dominant eigenvectors are used to select three primary clusters based on the following decision rules: Group 1: (which is the most condensed cluster region with 32 data points); Group 2: (with 10 data points); Group 3: (with five data points). The undecided region, with 75 data points, is the remaining region outside these three clusters. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]