Confirmatory factor analysis was applied to test second- and higher-order factor models in the areas of structure of abilities, allometry, and the separation of specific and error variance estimates. The estimation of validity and reliability, second-order models within factor analysis models, and the concept of discriminability were also studied.…

To determine if the observed correlation between two variables can be "explained" by a third variable, a significance test on the partial correlation coefficient is often used. This can be misleading when the third variable is measured with error. This article shows how the problem can be partially overcome. (Author/BW)

The impact of misspecification on the estimation, testing, and improvement of structural equation models was assessed via a population study in which a prototypical latent variable model was misspecified. Results provide insights into the maximum likelihood estimator versus a limited two-stage least squares estimator in LISREL. (TJH)

The use of two-stage least squares (2SLS) for the estimation of feedback linkages is inappropriate for nonorthogonal data sets because 2SLS is extremely sensitive to multicollinearity. It is argued that what is needed is use of a different estimating criterion than the least squares criterion. Theoretically the variance normalization criterion has…

Uses the general linear model to develop an adjusted cumulative grade point average (GPA) that systematically models grading effects among courses. A validation study using 778 courses of 1,564 Stanford (California) University students shows an increase in predictability of the adjusted least-squares GPA over the unadjusted GPA. (SLD)