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Structural Equation Modeling | 38 |
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Green, Samuel B.; Thompson, Marilyn S.; Poirier, Jennifer – Structural Equation Modeling, 1999
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…
Descriptors: Goodness of Fit, Models

Millsap, Roger E. – Structural Equation Modeling, 2001
Different sets of uniqueness constraints may lead to different fit results when applied to the same data in confirmatory factor analysis. Provides several examples of this phenomenon in simulated data and describes reasons for the variation in fit results. Discusses the choice of uniqueness constraints under these circumstances. (SLD)
Descriptors: Goodness of Fit, Simulation

Raykov, Tenko – Structural Equation Modeling, 2001
Discusses a method, based on bootstrap methodology, for obtaining an approximate confidence interval for the difference in root mean square error of approximation of two structural equation models. Illustrates the method using a numerical example. (SLD)
Descriptors: Goodness of Fit, Structural Equation Models

Corten, Irmgard W.; Saris, Willem E.; Coenders, Germa; van der Veld, William; Aalberts, Chris E.; Kornelis, Charles – Structural Equation Modeling, 2002
Compared different models suggested for the analysis of multitrait multimethod (MTMM) experiments for their fit to 87 data sets collected in the United States. The fit of models based on polychoric correlations is much worse than the fit of models based on product moment correlations, but in both cases a model that assumes additive method effects…
Descriptors: Correlation, Goodness of Fit, Multitrait Multimethod Techniques

Cheung, Gordon W.; Rensvold, Roger B. – Structural Equation Modeling, 2002
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.…
Descriptors: Goodness of Fit, Models, Sample Size, Simulation

Raykov, Tenko; Penev, Spiridon – Structural Equation Modeling, 1998
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…
Descriptors: Goodness of Fit, Power (Statistics), Structural Equation Models

Lee, Sik-Yum; Shi, Jian-Qing – Structural Equation Modeling, 2000
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)
Descriptors: Bayesian Statistics, Goodness of Fit, Structural Equation Models

Ogasawara, Haruhiko – Structural Equation Modeling, 2001
Derives approximations to the distributions of goodness-of-fit indexes in structural equation modeling with the assumption of multivariate normality and slight misspecification of models. Also derives an approximation to the asymptotic covariance matrix for the fit indexes by using the delta method and develops approximations to the densities of…
Descriptors: Goodness of Fit, Statistical Distributions, Structural Equation Models

Wen, Zhonglin; Marsh, Herbert W.; Hau, Kit-Tai – Structural Equation Modeling, 2002
Points out two concerns with recent research by F. Li and others (2000) and T. Duncan and others (1999) that extended the structural equation model of latent interactions developed by K. Joreskog and F. Yang (1996) to latent growth modeling. Used mathematical derivation and a comparison of alternative models fitted to simulated data to develop a…
Descriptors: Goodness of Fit, Interaction, Simulation, Structural Equation Models
Kim, Kevin H. – Structural Equation Modeling, 2005
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…
Descriptors: Structural Equation Models, Sample Size, Goodness of Fit
The Equal Correlation Baseline Model for Comparative Fit Assessment in Structural Equation Modeling.

Rigdon, Edward E. – Structural Equation Modeling, 1998
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…
Descriptors: Comparative Analysis, Correlation, Goodness of Fit, Structural Equation Models

Marsh, Herbert W. – Structural Equation Modeling, 1998
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…
Descriptors: Comparative Analysis, Correlation, Goodness of Fit, Structural Equation Models

Kenny, David A.; McCoach, D. Betsy – Structural Equation Modeling, 2003
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)
Descriptors: Computer Simulation, Goodness of Fit, Models, Structural Equation Models

Hu, Li-tze; Bentler, Peter M. – Structural Equation Modeling, 1999
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…
Descriptors: Criteria, Evaluation Methods, Goodness of Fit, Models

Bandalos, Deborah L. – Structural Equation Modeling, 2002
Used simulation to study the effects of the practice of item parceling. Results indicate that certain types of item parceling can obfuscate a multidimensional factor structure in a way that acceptable values of fit indexes are found for a misspecified solution. Discusses why the use of parceling cannot be recommended when items are…
Descriptors: Estimation (Mathematics), Factor Structure, Goodness of Fit, Test Items