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When inspecting factor loadings of the three-factor model (Table 2), all of the items significantly loaded on the hypothesized dimension; whereas, when examining factor loadings of the bi-factor model, all the items more strongly loaded on the general factor than they did on the group factors.
Ions Mg2+ and Ca2+ are strongly loaded on factor 2 with positive values.
Factor 1 accounts for 34.09 % of the total variance and metals, i.e., Pb and Hg are strongly loaded with a positive value.
PC1, which explained 21% of the variation, was most strongly loaded on levels of leptin, TNFα, insulin, and aPAI1, and inversely with adiponectin.
PC1 (21%) was most strongly loaded on levels of leptin, TNFα, insulin, and aPAI1, and inversely with adiponectin, and showed a heritability of ∼50%, which is at least as large as that of the individual contributing hormones.
PC1 was most strongly loaded by peaks corresponding to C33 alkenes, whereas PC2 was most strongly loaded by peaks corresponding to C31 alkenes.
Similar(45)
The PCA with rotation was conducted to achieve simple structure in the data, with each item only loading on to a single factor and each factor determined by a number of strongly loading items [ 26, 27].
Five or more strongly loading items (0.5 or above) are desirable to create a solid factor [ 20].
PC2 is strongly positively loaded with Ca, Sr, and P and moderately negatively loaded with Al, indicating anthropogenic sources.
The first principal component (PC1) in the datasets explains 39.610%% of total variance and is strongly positively loaded with Fe, Al, Ti, and Rb and moderately positively loaded with Ba, indicating both natural and anthropogenic sources.
Posture strongly and load up for the worst.
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