Almost all modern rotation of factor loadings is based on optimizing a criterion, for example, the quartimax criterion for quartimax rotation. Recent advancements in numer-ical methods have led to general orthogonal and oblique algorithms for optimizing essen-tially any rotation criterion. All that is required for a specific application is a definition of the criterion and its gradient. The authors present the implementations of gradient projec-tion algorithms, both orthogonal and oblique, as well as a catalogue of rotation criteria and corresponding gradients. Software for these is downloadable and free; a specific ver-sion is given for each of the computing environments used most by statisticians. Exam-ples of rotation methods are present...
Component loss functions (CLFs) similar to those used in orthogonal rotation are introduced to defin...
A new method to represent and approximate rotation matrices is introduced. The method represents app...
Factor rotation is widely used to interpret the estimated factor loadings from latent variable model...
A simple modification substantially simplifies the use of the gradient projection (GP) rotation algo...
Gradient methods are employed in orthogonal oblique analytic rotation. Constraints are imposed on th...
This paper addresses the problem of rotating a factor matrix obliquely to a least squares fit to a ...
A method for evaluating results of Procrustean rotation to a target factor pattern matrix in explora...
The asymptotic standard errors of the estimates of rotated factor loadings and factor correlations a...
The rotation problem in factor analysis consists in finding an orthogonal transformation of the init...
The asymptotic standard errors of the estimates of rotated factor loadings and factor correlations a...
Matrices of factor loadings are often rotated to simple structure. When more than one loading matrix...
FACTOR analysis is used for two different theoretical purposes: to search for structure among correl...
Rotated ASK-G scale factor loadings for exploratory factor analysis with Kaiser-Varimax rotations.</...
factor analysis, quartimax, varimax, orthomax, simultaneous rotation, simultaneous diagonalization, ...
Gradient projection rotation (GPR) is an openly available and promising tool for factor and componen...
Component loss functions (CLFs) similar to those used in orthogonal rotation are introduced to defin...
A new method to represent and approximate rotation matrices is introduced. The method represents app...
Factor rotation is widely used to interpret the estimated factor loadings from latent variable model...
A simple modification substantially simplifies the use of the gradient projection (GP) rotation algo...
Gradient methods are employed in orthogonal oblique analytic rotation. Constraints are imposed on th...
This paper addresses the problem of rotating a factor matrix obliquely to a least squares fit to a ...
A method for evaluating results of Procrustean rotation to a target factor pattern matrix in explora...
The asymptotic standard errors of the estimates of rotated factor loadings and factor correlations a...
The rotation problem in factor analysis consists in finding an orthogonal transformation of the init...
The asymptotic standard errors of the estimates of rotated factor loadings and factor correlations a...
Matrices of factor loadings are often rotated to simple structure. When more than one loading matrix...
FACTOR analysis is used for two different theoretical purposes: to search for structure among correl...
Rotated ASK-G scale factor loadings for exploratory factor analysis with Kaiser-Varimax rotations.</...
factor analysis, quartimax, varimax, orthomax, simultaneous rotation, simultaneous diagonalization, ...
Gradient projection rotation (GPR) is an openly available and promising tool for factor and componen...
Component loss functions (CLFs) similar to those used in orthogonal rotation are introduced to defin...
A new method to represent and approximate rotation matrices is introduced. The method represents app...
Factor rotation is widely used to interpret the estimated factor loadings from latent variable model...