covariance structure analysis, factor analysis, Gauss-Newton, Newton-Raphson, Fisher Scoring, Fletcher-Powell, Fletcher-Reeves, maximum likelihood, weighted least squares, Hessian matrix, Fisher information matrix,
A new factor analysis (FA) procedure has recently been proposed which can be called matrix decomposi...
The fundamental mathematical model of Thurstone’s common factor analysis is reviewed. The basic co...
ABSTRACT. Despite known shortcomings of the procedure, exploratory factor analysis of dichotomous te...
A model, in which the means and the variance-covariance matrix of observed variables change with an ...
generalized least squares, asymptotic distributions, goodness-of-fit test, multiplier method, repara...
Factor analysis is a multivariate statistical method for data reduction that originated in psychomet...
Factor analysis aims to describe high dimensional random vectors by means of a small number of unkno...
summary:The problem of decomposing a given covariance matrix as the sum of a positive semi-definite ...
factor analysis, structural models ABSTRACT. This paper provides methods for the estimation of covar...
A classical advantage of factor analysis is its provision for possible generalizability of the &...
The consequences of factoring alternative correlation matrices are investigated assuming ordinal sca...
Compares 4 models of calculating standard errors (SEs) in the analysis of covariance (ANCOVA) struct...
Factor analysis, a statistical method for modeling the covariance structure of high dimensional data...
A procedure similar to an analysis of variance is presented for examining the structure in correlati...
A covariance analysis procedure which compares multiple linear regression equations is developed by ...
A new factor analysis (FA) procedure has recently been proposed which can be called matrix decomposi...
The fundamental mathematical model of Thurstone’s common factor analysis is reviewed. The basic co...
ABSTRACT. Despite known shortcomings of the procedure, exploratory factor analysis of dichotomous te...
A model, in which the means and the variance-covariance matrix of observed variables change with an ...
generalized least squares, asymptotic distributions, goodness-of-fit test, multiplier method, repara...
Factor analysis is a multivariate statistical method for data reduction that originated in psychomet...
Factor analysis aims to describe high dimensional random vectors by means of a small number of unkno...
summary:The problem of decomposing a given covariance matrix as the sum of a positive semi-definite ...
factor analysis, structural models ABSTRACT. This paper provides methods for the estimation of covar...
A classical advantage of factor analysis is its provision for possible generalizability of the &...
The consequences of factoring alternative correlation matrices are investigated assuming ordinal sca...
Compares 4 models of calculating standard errors (SEs) in the analysis of covariance (ANCOVA) struct...
Factor analysis, a statistical method for modeling the covariance structure of high dimensional data...
A procedure similar to an analysis of variance is presented for examining the structure in correlati...
A covariance analysis procedure which compares multiple linear regression equations is developed by ...
A new factor analysis (FA) procedure has recently been proposed which can be called matrix decomposi...
The fundamental mathematical model of Thurstone’s common factor analysis is reviewed. The basic co...
ABSTRACT. Despite known shortcomings of the procedure, exploratory factor analysis of dichotomous te...
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