A theoretical and philosophical revision of the concept of fit in structural equation modeling and its relation to a confirmation bias is developed. The neutral character of fit indexes regarding this issue is argued, concluding that protection against confirmation bias relies on model modification strategy and scientist behavior. (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)

Problems found in the application of structural equation modeling to the theory of reasoned action are explored, and an alternative model specification is proposed that improves the fit of the data while leaving intact the structural part of the model being tested. Problems and the proposed alternative are illustrated. (SLD)

A Monte Carlo study evaluated the effectiveness of different factor analysis extraction and rotation methods for identifying the known population multiple-indicator measurement model. Results demonstrate that exploratory factor analysis can contribute to a useful heuristic strategy for model specification prior to cross-validation with…

Tested seven alternative models explaining correlated disturbance terms in survey research, testing each on seven datasets. Results show that the model that assumes unequal method effects offers the best explanation for the correlated disturbance terms, although other explanations cannot be ruled out entirely. (SLD)

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 didactic example is presented of the application of new developments in structural equation modeling that allow for the modeling of multilevel data. The method, a synthesis of methods developed by B. Muthen, is applied to the problem of validating indicators of science education quality in the United States. (SLD)

The use of Lagrange multiplier (LM) tests in specification searches and the efforts that involve the addition of extraneous parameters to models are discussed. Presented are a rationale and strategy for conducting specification searches in two stages that involve adding parameters to LM tests to maximize fit and then deleting parameters not needed…

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)

The Schmid-Leiman (J. Schmid and J. M. Leiman, 1957) decomposition of a hierarchical factor model converts the model to a constrained case of a bifactor model with orthogonal common factors that is equivalent to the hierarchical model. This article discusses the equivalence of the hierarchical and bifactor models. (Author/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…

Examines the use of sample weights in latent variable models in the case where a simple random sample is drawn from a population containing a mixture of strata through a bootstrap simulation study. Results show that ignoring weights can lead to serious bias in latent variable model parameters and reveal the advantages of using sample weights. (SLD)

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…