Structural equation models require formidable computational techniques. Testing the goodness of fit involves discrepancies between original correlations among variables and correlations estimated by solved path coefficients. A BASIC computer program which solves these problems is presented and discussed. (Author/GDC)

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.…

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)

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 utility of several longitudinal data analysis models for use with educational attainment are discussed and illustrated on a large data set. Assumptions of the models, choice of scale units, and data transformations, as well as real-life implications are emphasized. (Author/JKS)

Covariance structures associated with linear structural equation models are discussed. Algorithms for computing maximum likelihood estimates (namely, the EM algorithm) are reviewed. An example of using likelihood ratio tests based on complete and incomplete data to improve the fit of a model is given. (SLD)

This Monte Carlo study examined the validity of the chi-square test for model evaluation in different instances of misspecification and sample size. The usefulness of the chi-square difference statistic to compare competing structures and improvement in fit is also addressed. (Author/BS)

Reading ability, symbol-processing speed, and spatial reasoning ability were examined in families with reading disabled children and in control families. For both types of families, comparable moderate familial influences were found, which also accounted for phenotypic correlations between traits. Multivariate path analysis and other statistical…

Multivariate analytic techniques offer useful research methods that permit the experiential educator to test theoretical models, analyze the effects of several variables acting together, and predict the effects of one set of variables upon another set of variables. Several of these techniques are discussed, including analysis of variance, multiple…

Effects of aspirations, homework, and scores on standardized tests (endogenous variables) on teachers' grades and effects of exogenous variables of socioeconomic status and gender on endogenous variables were studied for 753 Israeli elementary school students. Complex effects are discussed. Teachers tended to grade students properly, according to…