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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

Kumar, Ajith; Sharma, Subhash – Structural Equation Modeling, 1999
Demonstrates the advantages of Rao's Distance (C. Rao, 1949) over the root mean residual square for model comparisons using an analysis of a sample of multitrait-multimethod data. A simulation study shows that the true orderings of intermodel proximities are received with a fair degree of accuracy. (Author/SLD)
Descriptors: Comparative Analysis, Multitrait Multimethod Techniques, Simulation

Raykov, Tenko; Marcoulides, George A.; Boyd, Jeremy – Structural Equation Modeling, 2003
Illustrates how commonly available structural equation modeling programs can be used to conduct some basic matrix manipulations and generate multivariate normal data with given means and positive definite covariance matrix. Demonstrates the outlined procedure. (SLD)
Descriptors: Data Analysis, Matrices, Simulation, Structural Equation Models

Paxton, Pamela; Curran, Patrick J.; Bollen, Kenneth A.; Kirby, Jim; Chen, Feinian – Structural Equation Modeling, 2001
Illustrates the design and planning of Monte Carlo simulations, presenting nine steps in planning and performing a Monte Carlo analysis from developing a theoretically derived question of interest through summarizing the results. Uses a Monte Carlo simulation to illustrate many of the relevant points. (SLD)
Descriptors: Monte Carlo Methods, Research Design, Simulation, Statistical Analysis

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