Results of principal components analysis (PCA) for public and private sector models.^*

Abstract

<p>*The PCA-generated weights are the eigenvectors of the first principal component; eigenvectors were derived from the correlation matrix in Stata 12.0 [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0130845#pone.0130845.ref012" target="_blank">12</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0130845#pone.0130845.ref013" target="_blank">13</a>]. The first principal component explained 32% and 33% of the variance in the data for the public and private sector knowledge indexes, respectively.</p><p>Results of principal components analysis (PCA) for public and private sector models.^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0130845#t003fn001" target="_blank">*</a>}</p