res_pca_rotation is the rotation matrix that arose from a principal components analysis on our publication data from 2012-2017; it contains information about the correlation structure of each variable and each principal component. res_pca_summary contains information about the std. dev and cumulative variance for each component. This is the information we used to threshold our choice of components to 4
Principal components analysis (PCA) is a multivariate data analysis technique whose main purpose is ...
The .plot functionality will show the total explained variance across the components when selecting ...
<p>Component correlation matrix of principal component analysis (PCA) used to determine relationship...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
PCA (Principal Component Analysis ) are statistical techniques applied to a single set of variables ...
<p>After varimax raw rotation, highly significant loading factors of the variables on the PCA axes a...
<p>Principal components analysis (PCA) of three factors and of one factor. Matrix of items.</p
<p>In the row for each variable, numbers indicate the strength of correlation of that variable with ...
Each symbol represents an individual. (a) Shows the population structure of investigated major regio...
Principal Component Analysis (PCA) is one of the most popular techniques in multivariate statistica...
<p>Cumulative explained variance and the number of principal components are shown for each movement ...
<p>Principal components analysis with varimax rotation for BFI-10 Study 2d, and for all BFI-10 data ...
Principal Component Analysis (PCA from now on) is a multivariate data analysis technique used for ma...
Principal Component Analysis (PCA) is one of the most popular techniques in multivariate statistica...
Principal Component Analysis (PCA from now on) is a multivariate data analysis technique used for ma...
Principal components analysis (PCA) is a multivariate data analysis technique whose main purpose is ...
The .plot functionality will show the total explained variance across the components when selecting ...
<p>Component correlation matrix of principal component analysis (PCA) used to determine relationship...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
PCA (Principal Component Analysis ) are statistical techniques applied to a single set of variables ...
<p>After varimax raw rotation, highly significant loading factors of the variables on the PCA axes a...
<p>Principal components analysis (PCA) of three factors and of one factor. Matrix of items.</p
<p>In the row for each variable, numbers indicate the strength of correlation of that variable with ...
Each symbol represents an individual. (a) Shows the population structure of investigated major regio...
Principal Component Analysis (PCA) is one of the most popular techniques in multivariate statistica...
<p>Cumulative explained variance and the number of principal components are shown for each movement ...
<p>Principal components analysis with varimax rotation for BFI-10 Study 2d, and for all BFI-10 data ...
Principal Component Analysis (PCA from now on) is a multivariate data analysis technique used for ma...
Principal Component Analysis (PCA) is one of the most popular techniques in multivariate statistica...
Principal Component Analysis (PCA from now on) is a multivariate data analysis technique used for ma...
Principal components analysis (PCA) is a multivariate data analysis technique whose main purpose is ...
The .plot functionality will show the total explained variance across the components when selecting ...
<p>Component correlation matrix of principal component analysis (PCA) used to determine relationship...
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