Educational reform is most likely to be successful when teachers are knowledgeable about the intended reform, and when their concerns about the reform are understood and addressed. The Common Core State Standards (CCSS) is an effort to establish a set of nationwide expectations for students and teachers. This study examined teacher understanding…

Using LISREL, the only types of constraints allowed are fixing parameters at a constant value and constraining parameters to be equal. In this paper, two new concepts ("phantom" and "imaginary" latent variables) are introduced which allow fairly general equality and inequality constraints on factor loadings and structural model…

The usefulness of path analysis as a means of better understanding various linear models is demonstrated. First, two linear models are presented in matrix form using linear structural relations (LISREL) notation. The two models, regression and factor analysis, are shown to be identical although the research question and data matrix to which these…

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.…

Correlated Factors Modeling (CFM) is proposed as an alternative to LISREL and similar methods of estimating structural equations. CFM employs weak mathematics and is appropriate for a rapid, preliminary look at a model. The factors produced by CFM are exact linear components of their indicator variates. (Author/GDC)

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)

The overidentification of structural equation models with latent variables is discussed. The use of two- and three-indicator models is not recommended since such models do not allow a testing of the crucial assumption of unidimensionality among indicators in most cases. Models with four or more indicators may be more sensitive to departures from…

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)

Path analysis was used to reevaluate the analysis of covariance quasiexperimental study of the effectiveness of the Head Start program. Contrary to the original analysis, the alternative approach yields small positive estimates of effect. (Author/CTM)

The relationship of multiple linear regression to various multivariate statistical techniques is discussed. The importance of the standardized partial regression coefficient (beta weight) in multiple linear regression as it is applied in path, factor, LISREL, and discriminant analyses is emphasized. The multivariate methods discussed in this paper…

Using 559 fifth graders, measures were collected to assess multiple dimensions of academic self-attribution, self-concept, and inferred self-concept, and academic achievement. The specificity and predictability of the observed patterns of relations support the construct validity of interpretations based on both the self-attribution and…

The objective of this study was to review and integrate the various methodologies used in the study of individual growth (especially academic growth). This was accomplished by means of Joreskog's general model for the analysis of covariance structures, i.e., each of the disparate methodologies available from the literature was shown to be a…

Newman (1984) examined the causal relations between math self-concept and math achievement in an 8-year longitudinal study using Linear Structural Relations (LISREL) analyses. He concluded that math self-concept did not influence subsequent math achievement. However, the study suffered in that math self-concept was inferred from a single-item…