In this paper we consider the well-known Thurstone box problem in exploratory factor analysis. Initial loadings and components are extracted using principal component analysis. Rotating the components towards independence rather than rotating the loadings towards simplicity allows one to accurately recover the dimensions of each box and also produce simple loadings. It is shown how this may be done using an appropriate rotation criterion and a general rotation algorithm. Methods from independent component analysis are used, and this paper may be viewed as an introduction to independent component analysis from the perspective of factor analysis
The principal-factor solution is probably the most widely used technique in factor analysis and a re...
Under the null hypothesis, component loadings are linear combinations of factor loadings, and vice v...
Independent component analysis (ICA) is a modern factor analysis tool de- veloped in the last two de...
Noisy independent component analysis (ICA) is viewed as a method of factor rotation in exploratory f...
In the statistical literature on factor analysis many ingenious graphical and analytical procedures ...
Component loss functions (CLFs) are used to generalize the quartimax criterion for orthogonal rotati...
Procedures for oblique rotation of factors or principal components typically focus on rotating the p...
<p>Extraction Method: Principal Component Analysis.</p><p>Rotation Method: Oblimin with Kaiser Norma...
Both factor analysis and principal component analysis are very popular among social researchers. Th...
<p>*Factor loads are determined by the pearson correlation coefficient of the marker on the componen...
The independent exploratory factor analysis method is introduced for recovering independent latent s...
In this paper we compare and contrast the objectives of principal component analysis and explanatory...
In this paper, we extend the use of disjoint orthogonal components to three-way table analysis with ...
Photocopy of typescript.Thesis (Ph. D.)--University of Hawaii at Manoa, 1978.Bibliography: leaves 16...
Factor analysis, component loss criteria, gradient projection, hyperplane count methods, quartimax, ...
The principal-factor solution is probably the most widely used technique in factor analysis and a re...
Under the null hypothesis, component loadings are linear combinations of factor loadings, and vice v...
Independent component analysis (ICA) is a modern factor analysis tool de- veloped in the last two de...
Noisy independent component analysis (ICA) is viewed as a method of factor rotation in exploratory f...
In the statistical literature on factor analysis many ingenious graphical and analytical procedures ...
Component loss functions (CLFs) are used to generalize the quartimax criterion for orthogonal rotati...
Procedures for oblique rotation of factors or principal components typically focus on rotating the p...
<p>Extraction Method: Principal Component Analysis.</p><p>Rotation Method: Oblimin with Kaiser Norma...
Both factor analysis and principal component analysis are very popular among social researchers. Th...
<p>*Factor loads are determined by the pearson correlation coefficient of the marker on the componen...
The independent exploratory factor analysis method is introduced for recovering independent latent s...
In this paper we compare and contrast the objectives of principal component analysis and explanatory...
In this paper, we extend the use of disjoint orthogonal components to three-way table analysis with ...
Photocopy of typescript.Thesis (Ph. D.)--University of Hawaii at Manoa, 1978.Bibliography: leaves 16...
Factor analysis, component loss criteria, gradient projection, hyperplane count methods, quartimax, ...
The principal-factor solution is probably the most widely used technique in factor analysis and a re...
Under the null hypothesis, component loadings are linear combinations of factor loadings, and vice v...
Independent component analysis (ICA) is a modern factor analysis tool de- veloped in the last two de...