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These dimensions of variance explain the latitudinal dependence.
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The interregional correlations and PCA showed that almost all variability between ROIs, including denominator ROIs, is attributable to a single underlying dimension of variance.
Discrimination measures show the correlation (-1 to 1) of each variable with a dimension, and inertia measures the proportion of variance of the original variables explained by each dimension.
The proportion of variance (inertia) explained by each dimension is given in Table 5. Dimension 1 explained 19.2% of the total variance and included one risk factor ("poor general health status").
The dendrograms in Figure 1 show block structure, and suggest how the variables could be partitioned into clusters representing dimensions of significant variance.
PCA analysis performed using presence and absence of OTUs suggested that the first dimension of 21.6% variance could not be related to eczema, but was instead age-mediated (Figure 4A).
Using the entire data set as the initial "bin", data were adaptively binned by splitting the data in each bin at the median of the dimension of highest variance.
We then identified the dimension of highest variance in the response-weighted stimulus ensemble by principle components analysis and separated response-weighted stimulus segments in two groups based on their projection onto this first principle component (positive = ON, negative = OFF).
In contrast, the less complex models, GMAKr and GMMr, showed several dimensions of almost no variance.
In this way, we attempt to avoid overlooking any dimensions of expression profile variance.
While performance on time perception was found to be unrelated to basic dimensions of personality, analysis of variance and correlational analyses revealed that performance on time estimation was significantly associated with the personality dimension of psychoticism (P).
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