Add to ORKGThe association structure between manifest variables arising from the single-factor model is investigated using partial correlations. The additional insights to the practitioner provided by partial correlations for detecting a single-factor model are discussed. The parameter space for the partial correlations is presented, as are the patterns of signs in a matrix containing the partial correlations that are not compatible with a single-factor model. Key words: anti-image correlation matrix, elliptical tetrahedron, factor analysis, factor partial correlation, manifest partial correlation
A correlation is a measure of the linear relationship between two variables. It is used when aresear...
A correlation is a measure of the linear relationship between two variables. It is used when aresear...
Common factor analysis (FA) and principal component analysis (PCA) are commonly used to obtain lower...
The association structure between manifest variables arising from the single-factor model is investi...
The association structure between manifest variables arising from the single-factor model is investi...
The association structure between manifest variables arising from the single-factor model is investi...
anti-image correlation matrix, elliptical tetrahedron, factor analysis, factor partial correlation, ...
The classical single-factor model is parametrized as a graphical Gaussian model. The relationship be...
The correlational structure of a set of variables is often conveniently described by the pairwise pa...
This paper shows how to compute multiple correlation coefficients, partial correlation coefficients,...
Connections between graphical Gaussian models and classical single-factor models are obtained by par...
It is often of interest to estimate partial or semipartial correlation coefficients as indexes of th...
It is often of interest to estimate partial or semipartial correlation coefficients as indexes of th...
Partial correlations quantify linear association between two variables while adjusting for the influ...
Abstract: Multivariate approach to generate variance covariance and partial correlation coefficients...
A correlation is a measure of the linear relationship between two variables. It is used when aresear...
A correlation is a measure of the linear relationship between two variables. It is used when aresear...
Common factor analysis (FA) and principal component analysis (PCA) are commonly used to obtain lower...
The association structure between manifest variables arising from the single-factor model is investi...
The association structure between manifest variables arising from the single-factor model is investi...
The association structure between manifest variables arising from the single-factor model is investi...
anti-image correlation matrix, elliptical tetrahedron, factor analysis, factor partial correlation, ...
The classical single-factor model is parametrized as a graphical Gaussian model. The relationship be...
The correlational structure of a set of variables is often conveniently described by the pairwise pa...
This paper shows how to compute multiple correlation coefficients, partial correlation coefficients,...
Connections between graphical Gaussian models and classical single-factor models are obtained by par...
It is often of interest to estimate partial or semipartial correlation coefficients as indexes of th...
It is often of interest to estimate partial or semipartial correlation coefficients as indexes of th...
Partial correlations quantify linear association between two variables while adjusting for the influ...
Abstract: Multivariate approach to generate variance covariance and partial correlation coefficients...
A correlation is a measure of the linear relationship between two variables. It is used when aresear...
A correlation is a measure of the linear relationship between two variables. It is used when aresear...
Common factor analysis (FA) and principal component analysis (PCA) are commonly used to obtain lower...