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In order to evaluate the significance of this three-way classification, we performed unsupervised k-means analysis on the same standardized data from the 20 GBM samples and evaluated the fit and stability over a range of cluster sizes.
In the K-means analysis on N = 4,467, all clustering variables significantly contributed to the solution (P < 0.001).
Experimental results are based on a mean analysis of 10,000 events and error bars represent standard error of the mean.
The interviews were analyzed using manifest content analysis that means the analysis has focused on what the text said, i.e. visible and obvious content [ 44].
That means the analysis based on s. 3(1) is the same whether the reproduction is made from the original work or from a copy.
We only found one study in chest pain which performed a k-means cluster analysis on variable level to determine whether there are characteristic patterns in chest pain locations described by patients [ 6].
Fast and delayed inhibitory responses were identified with K-means cluster analysis on onset latency and latency to peak (Supplementary Figure 1).
We also carried out a K-means clustering analysis on the GWR coefficients to derive location-sensitive policies that would, if employed, enhance community resilience.
Compared with traditional ROI-based volumetric and mean FA analysis on the white matter tracts, the regionally-specific pattern of FA reduction and shape abnormalities would potentially increase statistical power for differentiating AD from healthy aging, which would be beneficial to clinical diagnosis.
A k-means cluster analysis on patient level with all variables of our case report form resulted in a three cluster solution with a small F value of 46.8 and an eta2 of.073.
This conclusion is supported by Eslick [ 6] who performed a k-means cluster analysis on variable level to determine whether there are characteristic patterns in chest pain locations described by patients.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com