Add to ORKGIntroduction Factor Analysis and Structural Theories Brief History of Factor Analysis as a Linear Model Example of Factor AnalysisMathematical Foundations for Factor Analysis Introduction Scalar AlgebraVectorsMatrix AlgebraDeterminants Treatment of Variables as Vectors Maxima and Minima of FunctionsComposite Variables and Linear Transformations Introduction Composite Variables Unweighted Composite VariablesDifferentially Weighted Composites Matrix EquationsMult
structural equations, simultaneous equations, linear relations, covariance structures, latent variab...
Objectives of factor analysis To reduce the number of variables (indictors) to the smallest number o...
Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces...
Comprehensive and comprehensible, this classic covers the basic and advanced topics essential for us...
Factor analysis is a statistical technique, the aim of which is to simplify a complex data set by re...
AbstractThe principal components of a vector of random variables are related to the common factors o...
Un dels resultats principals de l'anàalisi factorial afirma que si el model factorial sesatis...
summary:The author shows that a decomposition of a covariance matrix $\bold{\sum = AA'}$ implies the...
Factor analysis is all about constructing measurement scales, that is trying to get at subtle, compl...
provides a concise (162 pages of text) and basic overview of two disciplines of assessing structure:...
A new factor analysis (FA) procedure has recently been proposed which can be called matrix decomposi...
AbstractWe report a matrix expression for the covariance matrix of MLEs of factor loadings in factor...
Under the null hypothesis, component loadings are linear combinations of factor loadings, and vice v...
Factor Analysis (FA) is a multivariate statistical technique that is often used to create new variab...
This is the first textbook that allows readers who may be unfamiliar with matrices to understand a v...
structural equations, simultaneous equations, linear relations, covariance structures, latent variab...
Objectives of factor analysis To reduce the number of variables (indictors) to the smallest number o...
Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces...
Comprehensive and comprehensible, this classic covers the basic and advanced topics essential for us...
Factor analysis is a statistical technique, the aim of which is to simplify a complex data set by re...
AbstractThe principal components of a vector of random variables are related to the common factors o...
Un dels resultats principals de l'anàalisi factorial afirma que si el model factorial sesatis...
summary:The author shows that a decomposition of a covariance matrix $\bold{\sum = AA'}$ implies the...
Factor analysis is all about constructing measurement scales, that is trying to get at subtle, compl...
provides a concise (162 pages of text) and basic overview of two disciplines of assessing structure:...
A new factor analysis (FA) procedure has recently been proposed which can be called matrix decomposi...
AbstractWe report a matrix expression for the covariance matrix of MLEs of factor loadings in factor...
Under the null hypothesis, component loadings are linear combinations of factor loadings, and vice v...
Factor Analysis (FA) is a multivariate statistical technique that is often used to create new variab...
This is the first textbook that allows readers who may be unfamiliar with matrices to understand a v...
structural equations, simultaneous equations, linear relations, covariance structures, latent variab...
Objectives of factor analysis To reduce the number of variables (indictors) to the smallest number o...
Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces...