Used three approaches to understand the effect of the number of variables in the model on model fit in structural equation modeling through computer simulation. Developed a simple formula for the theoretical value of the comparative fit index. (SLD)

Considers the question of whether there may be infinitely many models equivalent to a hypothesized one, presenting an example of a set of infinitely many models equivalent to an a priori hypothesized covariance structure model. (SLD)

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)

Presents results of a simulation study in which the power of latent growth modeling (LGM) for detecting group differences in the growth trajectory parameters was assessed. Six major findings about LGM power are outlined. (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…

Used confirmatory factor analysis to evaluate the score integrity of LibQUALl+, an instrument to measure perceptions of library service quality. Results for 60,027 graduate and undergraduate students suggest that the model implied by LibQUAL is reasonable and invariant across independent samples and fits all three major subgroups of library users.…

Studied the construct validity of state and trait-flow responses and demonstrated confirmatory factor analysis (CFA) models useful for this study with a sample of 385 athletes. There was good support for the construct validity of Flow State Scale (S. Jackson and H. Marsh, 1996) responses, and the CFA approach appears useful. (SLD)

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)

This article presents relevant research on Bayesian methods and their major applications to modeling in an effort to lay out differences between the frequentist and Bayesian paradigms and to look at the practical implications of these differences. Before research is reviewed, basic tenets and methods of the Bayesian approach to modeling are…

Examined 20 goodness-of-fit indexes based on the minimum fit function using a simulation under the 2-group situation. Results support the use of the delta comparative fit index, delta Gamma hat, and delta McDonald's Noncentrality Index to evaluation measurement invariance. These three approaches are independent of model complexity and sample size.…

Discusses the utility of multilevel confirmatory factor analysis and hierarchical linear modeling methods in testing measurement models in which the underlying attribute may vary as a function of levels of observation. A real dataset is used to illustrate the two approaches and their comparability. (SLD)

The adequacy of "rule of thumb" conventional cutoff criteria and several alternatives for fit indices in covariance structure analysis was evaluated through simulation. Analyses suggest that, for all recommended fit indexes except one, a cutoff criterion greater than (or sometimes smaller than) the conventional rule of thumb is required…

We consider a general type of model for analyzing ordinal variables with covariate effects and 2 approaches for analyzing data for such models, the item response theory (IRT) approach and the PRELIS-LISREL (PLA) approach. We compare these 2 approaches on the basis of 2 examples, 1 involving only covariate effects directly on the ordinal variables…

This simulation investigates bias in trait factor loadings and intercorrelations when analyzing multitrait-multimethod (MTMM) data using the correlated uniqueness (CU) confirmatory factor analysis (CFA) model. A theoretical weakness of the CU model is the assumption of uncorrelated methods. However, previous simulation studies have shown little…

In addition to assessing the rate of change in outcome measures, it may be useful to test the significance of outcome changes during specific time periods within an entire observation period under study. While discussing the delta method and bootstrapping, this study demonstrates how to use these 2 methods to estimate the standard errors of the…