Using higher order factor models, this article illustrates latent curve analysis for the purpose of modeling longitudinal change directly in a latent construct. Provides examples with simultaneous estimation of covariance and mean structures for a single-group and two-group structure. (SLD)

An expression is given for weighted least squares estimators of oblique common factors of factor analyses, constrained to have the same covariance matrix as the factors they estimate. A proof of the uniqueness of the solution is given. (Author/JKS)

A general statistical model for the multivariate analysis of mean and covariance structures is described. Matrix calculus is used to develop the statistical aspects of one new special case in detail. This special case separates the confounding of principal components and factor analysis. (DEP)

Focus of this paper is on the logic of the model rather than the estimation of parameters or testing the fit of the model to data. (Authors/MB)

This paper demonstrates the feasibility of using the penalty function method to estimate parameters that are subject to a set of functional constraints in covariance structure analysis. Both types of inequality and equality constraints are studied. The approaches of maximum likelihood and generalized least squares estimation are considered.…

The mathematical derivation of the statistics used for inference in some linear models assumes that values of the independent variables are pre-selected such that these variables can be treated as fixed rather than random variables. This assumption is often disregarded when these models are utilized in research. This study is an investigation of…

Factor analysis in several populations, covariance structure models, three-mode factor analysis, structural equations systems with measurement model, and analysis of covariance with measurement model are all shown to be specializations of a general moment structure model. Some new structured linear models are also described. (Author/CTM)

A statistical model for relating latent variables from manifest variables, called a linear structural equation model, is presented. The approach is illustrated by a test theory model and longitudianl study of intelligence. (Author/JKS)

Demonstrates how perspectives from covariance structural modeling and generalizability theory can be combined for a comprehensive assessment of latent constructs. This approach to examining variance components is illustrated by one- and two- facet designs, and can be extended to more complex designs. (MAK)

A variety of path models involving unmeasured variables are formulated in terms of Joreskog's general model for the analysis of covariance structures. (Author)

Current practice in structural modeling of variables is limited to means and covariances based on multivariate normality assumptions. This article extends structural equation models to higher order product moments and to non-normal distributions. Areas of possible research are described. (Author/JKS)

A method for the estimation of covariance structure models under polynomial constraints (such as quadratic constraints) is presented. Estimation is on maximum likelihood principles, and the test statistics, parameter estimates, and standard errors are based on a statistical theory which takes the constraints into account. (Author/JKS)

The inter-battery factor analysis model for predictive systems appears to offer a useful formalization of these systems and provides some guides for the development of the system. (Author)