Abstract
Factor loadings optimally account for the non-diagonal elements of the covariance matrix of observed variables. Principal component analysis leads to components accounting for a maximum of the variance of the observed variables. Retained-components factor transformation is proposed in order to combine the advantages of factor analysis and principal component analysis.
DOI
10.22237/jmasm/1414814700
Included in
Applied Statistics Commons, Social and Behavioral Sciences Commons, Statistical Theory Commons
