Researchers using factor analysis tend to dismiss the significant ill fit of factor models by presuming that if their factor model is close-to-fitting, it is probably close to being properly causally specified. Close fit may indeed result from a model being close to properly causally specified, but close-fitting factor models can also be seriously…

In this article, an overview is given of four methods to perform factor score regression (FSR), namely regression FSR, Bartlett FSR, the bias avoiding method of Skrondal and Laake, and the bias correcting method of Croon. The bias correcting method is extended to include a reliable standard error. The four methods are compared with each other and…

The relationship between saturated path-analysis models and their fit to data is revisited. It is demonstrated that a saturated model need not fit perfectly or even well a given data set when fit to the raw data is examined, a criterion currently frequently overlooked by researchers utilizing path analysis modeling techniques. The potential of…

The use of causal indicators to formatively measure latent constructs appears to be on the rise, despite what appears to be a troubling lack of consistency in their application. Scholars in any discipline are responsible not only for advancing theoretical knowledge in their domain of study but also for addressing methodological issues that…

Typical validation studies on standard setting models, most notably the Angoff and modified Angoff models, have ignored construct development, a critical aspect associated with all conceptualizations of measurement processes. Stone compared the Angoff and objective standard setting (OSS) models and found that Angoff failed to define a legitimate…

When assessing latent mean differences, researchers frequently do not explore possible heterogeneity within their data sets. Sources of differences may be functions of a nested data structure or heterogeneity in the form of unobserved classes of observations defined by a difference in factor means. In this study, the use of multilevel structural…

This article proposes a multilevel modeling approach to study the general and specific attitudes formed in human learning behavior. Based on the premises of activity theory, it conceptualizes the unit of analysis for attitude measurement as a scalable and evolving activity system rather than a single action. Measurement issues related to this…

The Computer Anxiety Scale (CAS) measures the perceptions of individuals with respect to their anxiety toward computers. Although the CAS was developed a number of years ago, research has shown that its factor structure has remained stable. Recent cross-cultural studies using samples of college students from various countries have also shown that…

Presents KANT, a FORTRAN 77 software program that tests assumptions of multivariate normality in a data set. Based on the test developed by M. V. Mardia (1985), the KANT program is useful for those engaged in structural equation modeling with latent variables. (SLD)

A general linear model framework is used to suggest that structure coefficients ought to be interpreted in structural equation modeling confirmatory factor analysis (CFA) studies in which factors are correlated. Two heuristic data sets make the discussion concrete, and two additional studies illustrate the benefits of CFA structure coefficients.…

Methods are offered for conducting hypothesis testing associated with disattenuated validity coefficients to overcome limitations of some other suggested approaches. Through using classical test theory's notion of reliability in the form of structured path models, such hypothesis testing may be done with hierarchically related structural equation…

The potential for bias in reliability estimation and for errors in item selection when alpha or unit-weighted omega coefficients are used is explored under simulated conditions. Results suggest that composite reliability may be an assessment tool but should not be an item selection tool in structural equations. (SLD)

Methods by which structural models correct for the effects of attenuation due to measurement error are reviewed, and implications of such disattenuation for interpreting the results of structural equation models are considered. Recommendations are made for improving the practice of disattenuation, and caution is urged in drawing inferences based…

In this Monte Carlo study, the effects of four factors on structural equation modeling (SEM) fit indices and parameter estimates were investigated. The 14,400 samples generated were fitted to 3 SEM models with different degrees of model misspecification. Effects of data nonnormality, estimation method, and sample size are noted. (SLD)

The purpose of this investigation was to test the age-related measurement invariance and temporal stability of the 13-item version of Antonovsky's Sense of Coherence Scale (SOC). Multigroup structural equation modeling of longitudinal data from the Canadian National Population Health Survey was used to examine the measurement invariance across 3…