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. 2016 Jan 7;13:1. doi: 10.1186/s12982-015-0038-3

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© Grajeda et al. 2016

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Fig. 4 — Subject-specific distributions of the square root MSEs for the entire growth curve for linear splines (black) versus cubic splines (red). Dashed lines correspond to the estimated median, 25 %, and 75 % percentiles of the subject-specific MSE distribution. Cubic regression splines outperformed piecewise linear splines: the median square root subject-specific MSE for linear regression splines was 0.65 vs. 0.51 for cubic regression splines. The Kolmogorov–Smirnov test indicates that the two distributions are significantly different (D = 0.19, p = 0.001)