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Direct linkJackman, M. Grace-Anne; Leite, Walter L.; Cochrane, David J. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This Monte Carlo simulation study investigated methods of forming product indicators for the unconstrained approach for latent variable interaction estimation when the exogenous factors are measured by large and unequal numbers of indicators. Product indicators were created based on multiplying parcels of the larger scale by indicators of the…
Descriptors: Computation, Statistical Data, Structural Equation Models, Statistical Analysis
Bandalos, Deborah L. – Structural Equation Modeling: A Multidisciplinary Journal, 2008
This study examined the efficacy of 4 different parceling methods for modeling categorical data with 2, 3, and 4 categories and with normal, moderately nonnormal, and severely nonnormal distributions. The parceling methods investigated were isolated parceling in which items were parceled with other items sharing the same source of variance, and…
Descriptors: Structural Equation Models, Computation, Goodness of Fit, Classification
Dolan, Conor; van der Sluis, Sophie; Grasman, Raoul – Structural Equation Modeling: A Multidisciplinary Journal, 2005
We consider power calculation in structural equation modeling with data missing completely at random (MCAR). Muth?n and Muth?n (2002) recently demonstrated how power calculations with data MCAR can be carried out by means of a Monte Carlo study. Here we show that the method of Satorra and Saris (1985), which is based on the nonnull distribution of…
Descriptors: Computation, Monte Carlo Methods, Structural Equation Models, Statistical Analysis
