<p>VIP>1, identifying variables most relevant for explaining BPC, are shown in bold. The direction of the association between BPC and the explanatory variables is deduced from scaled and centered coefficients (CoeffCS) and given in parenthesis. R2X is the proportion of variation in the explanatory data set explained by the latent factor(s), and R2Y is the proportion of variation in BPC explained by the latent factor(s) from the explanatory data set.</p><p>VIP values from PLS analysis between BPC and the explanatory variables for the data sets.</p
<p>In the row for each variable, numbers indicate the strength of correlation of that variable with ...
data In this article, we introduce a procedure for selecting variables in principal components analy...
Exons farthest from the origin are the most differentially expressed transcripts. Note that positive...
<p>A VIP score is a measure of a variable’s importance in the PLS-DA model. It summarizes the contr...
<p>Pearson correlation coefficients between BCC measures (in parenthesis) with VIP-values>1 from the...
<p>Variable Importance in the Projection (VIP) for the separate PLS analyses of the three different ...
<p>The variable importance in projection (VIP) denotes the degree of contribution to the PLS regress...
<p>Colored boxes on right indicate relative concentration of corresponding metabolite for samples bi...
<p>The VIP plot shows the importance of each variable when explaining X and the correlation to Y. Th...
<p>Pearson correlations between OP and EVAL components (bolded values correspond to statistically si...
<p>The predicted variables were regressed on the proportions of each component separately. The table...
<p>We dichotomised the study population in 600 participants with normal LV function and 182 with sub...
<p>Pearson's correlation coefficients for model variables. Coefficients shown in bold represent sign...
<p>Plot of variables importance for the projection (VIP) summarizes the importance of the variables ...
<p>Pearson correlation coefficients (r) for each variable for each comparison at the two time points...
<p>In the row for each variable, numbers indicate the strength of correlation of that variable with ...
data In this article, we introduce a procedure for selecting variables in principal components analy...
Exons farthest from the origin are the most differentially expressed transcripts. Note that positive...
<p>A VIP score is a measure of a variable’s importance in the PLS-DA model. It summarizes the contr...
<p>Pearson correlation coefficients between BCC measures (in parenthesis) with VIP-values>1 from the...
<p>Variable Importance in the Projection (VIP) for the separate PLS analyses of the three different ...
<p>The variable importance in projection (VIP) denotes the degree of contribution to the PLS regress...
<p>Colored boxes on right indicate relative concentration of corresponding metabolite for samples bi...
<p>The VIP plot shows the importance of each variable when explaining X and the correlation to Y. Th...
<p>Pearson correlations between OP and EVAL components (bolded values correspond to statistically si...
<p>The predicted variables were regressed on the proportions of each component separately. The table...
<p>We dichotomised the study population in 600 participants with normal LV function and 182 with sub...
<p>Pearson's correlation coefficients for model variables. Coefficients shown in bold represent sign...
<p>Plot of variables importance for the projection (VIP) summarizes the importance of the variables ...
<p>Pearson correlation coefficients (r) for each variable for each comparison at the two time points...
<p>In the row for each variable, numbers indicate the strength of correlation of that variable with ...
data In this article, we introduce a procedure for selecting variables in principal components analy...
Exons farthest from the origin are the most differentially expressed transcripts. Note that positive...