Illustrates how structural equation modeling can be used to test the multidimensionality of a measure. Using data collected on a multidimensional measure, compares an oblique factor model with a higher order factor model, and shows how the oblique factor model fits the data better. (SLD)

How is affective change rated with positive adjectives such as good related to change rated with negative adjectives such as bad? Two nested perfect and imperfect forms of dynamic bipolarity are defined using latent change structural equation models based on tetrads of items. Perfect bipolarity means that latent change scores correlate -1.…

In previous research (Hu & Bentler, 1998, 1999), 2 conclusions were drawn: standardized root mean squared residual (SRMR) was the most sensitive to misspecified factor covariances, and a group of other fit indexes were most sensitive to misspecified factor loadings. Based on these findings, a 2-index strategy-that is, SRMR coupled with another…

A rule is presented to identify the model in structural equation modeling. This rule includes the null B and recursive rules as extreme cases. Proof is given for the theorem. (SLD)

Studied the measurement of acquiescence in balanced scales using a structural equation modeling approach with subsamples of 986 and 992 from the same population of Belgian adults interviewed about ethnic prejudice. The strong relation in both populations of the latent style factor with a variable "sum of agreements" supports the idea…

A Monte Carlo study is reported that shows the comparative performance of alternative approaches under deviations from their respective assumptions in the case of structural equation models with latent variables with attention restricted to point estimates of model parameters. The conditional polychoric correlations method is shown most robust…

The relationship between structural equation modeling (SEM) and canonical correlation analysis (CCA) is illustrated. The representation of CCA in SEM may provide interpretive information not available from conventional CCA. Hierarchically, the relationship suggests that SEM is a more general analytic approach. (SLD)

Discusses the difference in noncentrality parameters of nested structural equation models and their utility in evaluating statistical power associated with the pertinent restriction test. Asymptotic confidence intervals for that difference are presented. These intervals represent a useful adjunct to goodness-of-fit indexes in assessing constraints…

Provides a discussion of an alternative two-stage least squares (2SLS) technique to include interactions of latent variables in structural equation models. The method requires selection of instrumental variables, and rules for selection are presented. An empirical example and Statistical Analysis System programs are presented. (SLD)

Extends the LISREL model to incorporate fixed covariates at both the measurement and the structural equations of the model, establishing a Bayesian procedure with conjugate type prior distributions. Illustrates the efficiency of the algorithm and presents a goodness of fit statistic for assessing the proposed model. (SLD)

The relation among fit indexes, power, and sample size in structural equation modeling is examined. The noncentrality parameter is required to compute power. The 2 existing methods of computing power have estimated the noncentrality parameter by specifying an alternative hypothesis or alternative fit. These methods cannot be implemented easily and…

An alternative baseline model for comparative fit assessment of structural equation models is described, evaluated, and compared to the standard "null" baseline model. The new "equal correlation" model constrains all variables to have equal, rather than zero, correlations, but all variances are free. Advantages and limitations…

Discusses concerns with the model proposed by E. Rigdon for computing incremental fit indices in which all measured variables are equally correlated (as opposed to the traditional null model). Proposes retaining the traditional null model with emphasis on the comparative fit of alternative models within a nested sequence that could include the new…

Structural equation modeling is used in the simultaneous study of individual and group latent change patterns on several longitudinally assessed variables. The approach, which is based on a special case of the comprehensive latent curve analysis of W. Meredith and J. Tisak (1990), is illustrated with a two-group study. (SLD)

Reviews the use of structural equation modeling for providing an overall assessment of mediation, the mechanism that accounts for the relation between the predictor and the criterion. A strategy for supplemental details is presented that measures the magnitude of mediational effects. (SLD)